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DR. DAVID SERES: Hello again.

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I'm Dr. David Seres, and it is my absolute
honor to be your moderator for the second

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half of this session.

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Session two moving toward beyond the terminology
of malnutrition.

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I'm Professor of medicine in the Institute
of Human Nutrition and Director of Medical

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Nutrition and an associate clinical ethicist
at Columbia University Medical Center in New

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York.

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Just as, just to remind you, you'll note that
our oral presentations of our illustrious

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speakers are brief, their CVs are long, and
to maximize time for the presentations, we

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have posted their bios on the, in the speaker's
section, which you can find the controls for

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on the left side of your screen, along with
all of the other boxes you might want, including

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the Q&A box which we encourage you to use
to submit questions at the end.

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We have had some really robust discussions.

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We have a half an hour to pester our speakers
and get them to clarify the issues that they're

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presenting.

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Yesterday, we started with an introduction
to malnutrition, starting with the impact

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of those prior to illness from Nancy Rahman
from the Partnership for a Healthier America,

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and then Gordon Jensen gave us a bit of a
review of the history of malnutrition diagnostic

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criteria.

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We then moved into a presentation of the AHRQ report that really spurred this particular

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conference, along with many others.

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A presentation of a value project that was
done through the auspices of the American

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Society of Parenteral Enteral Nutrition in
which the financial consequences of malnutrition

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in the sick were discussed.

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We looked at quality of care interventions,
the economics of nutrition in health care.

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We talked about how to figure out what the
optimal number of dietitians were, and we

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talked about issues of of payments and reimbursement
in the hospital.

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We also talked about how people go about making
a diagnosis of malnutrition and systems that

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people have put into place, both with technology
and people to capture the diagnosis.

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And then we had a presentation on how lifestyle
interventions are reimbursed.

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And I will say that it was really a little
disheartening to find that a very brief visit

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to give somebody a medication was paid far
in a way better than a longer session for

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counseling.

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Then we moved into this session, the second
session.

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I will reintroduce this by saying that I think
that this particular topic is really the fundamental

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question surrounding our approach to malnutrition,
and that is what is it that we're talking

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about when we actually speak of malnutrition?

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Because a lot of us disagree to a degree in
what we mean.

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I, for one, will not use the expression that
to say, to describe somebody as malnourished

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if they have malnutrition, where others automatically
say that those who have malnutrition are malnourished.

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And my philosophy on this is that if somebody
is malnourished, then there has to be a new

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nourishment that will make them better.

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And in fact, a lot of our research has shown
that, that there, our interventions are either

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ineffective or that we're choosing the wrong
populations.

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And that's a lot of what was discussed in
the first part of this session, session two.

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We talked about the efforts to, the most recent
efforts to define malnutrition by GLIM and

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others.

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We talked about the fact that the diagnosis
of malnutrition is highly, highly validated

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to predict poorer outcomes.

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But we also have shown that the diagnosis
does not predict who will respond to nutrition

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intervention.

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And this is why there's a dichotomy of opinion
about whether or not people who have malnutrition

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are also malnourished.

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And this is what I feel is one of the most
important research questions that we can seek

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out because we had data presented to us that,
in fact, that if somebody has a high level

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of inflammation, and I will say as an aside
that a high level of inflammation will, is

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often times we think the cause of a lot of
what we use to distinguish people as having

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malnutrition.

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Regardless, that high amount of inflammation
predicted people not responding to any nutrition

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intervention in a randomized controlled trial
finally.

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And that the, all of the, excuse me, current
schemes the subjective global assessment types

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of pre-assessments of assessment of risk.

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Again, all are very predictive of outcomes
in general but are not predictive of who will

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respond to nutrition interventions.

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We then reviewed the micronutrient deficiencies
and their impact, the cause, consequences

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and treatment.

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And then we talked about the nutritionally
vulnerable and hidden hunger, which, again,

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talks about sort of those who are out of the
hospital and looked at some of the research

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that's going on, trying to see if interventions
in those populations improves health outcomes.

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So, excuse me, for this afternoon, or whatever
it happens to be for those of you who are

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watching this either another time zones or
not live, we're going to, we're going to talk

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now about what we as a team, the organizing
committee, sort of stumbled across the term

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that we'd like to coin, which is refractory
malnutrition, which is really what I am sort

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of describing, and what others are describing
when we say inflammation counters the nourishment

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effect, excuse me.

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Rose Ann DiMaria-Ghalili is going to be speaking
about nutrition and aging across the care

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continuum.

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Excuse me.

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Carrie Earthman will be speaking about body
composition and nutrition status.

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Professor Reid from Belfast will be speaking
about a really interesting project that is

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ongoing to try and define cachexia in patients
with advanced renal disease.

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Mary Platek will be speaking about cachexia
in cancer patients and specifically about

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the new ASCO guidelines.

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And then we'll have a discussion at the end.

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So with all of that, let's begin our talks.

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DR. ROSE ANN DIMARIA-GHALILI: Hello, everyone.

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My name is Rose Ann DiMaria-Ghalili.

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I am the senior associate dean for research
and professor of nursing at Drexel University

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College of Nursing and Health Professions.

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Today I will be presenting on nutrition and
older adults across the care continuum.

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These are my objectives.

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We are a super aging nation.

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By 2035, there will be more older adults than
children under the age of 18 years of age.

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And not only will there be more adults 65
and older, but older adults will be living

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longer.

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And by the year 2060, we will see unprecedented
growth in those 85 years of age and older.

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As individual's age, they are, will experience
risk factors from malnutrition.

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Some of these risk factors include physiological
risk factors, losses of all their changes

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in their sense of taste and smell, poor oral
health and loss of lean mass.

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Older adults who are also experienced are
more likely to experience one or more chronic

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conditions as they age.

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Some chronic conditions can lead to impairments
in their activities of daily living and their

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instrumental activities of daily living, which
can impact their ability to prepare or ingest

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food.

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As one ages, they may experience Alzheimer's
disease or dementia and impairment in cognitive

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status such as ADRT can impact swallowing,
appetite, behavioral issues, especially during

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mealtime, which can impact their food intake.

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And this slide here just shows you the percentage
of older adults in 2019 that had one or more

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physical functioning difficulties with their
physical functioning.

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Medications from chronic, prescribed medications
as a result of one or more chronic conditions

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can also impact dietary intake.

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Depression is common or increased in older
adults, and that can also cause decreased

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dietary intake, appetite and weight loss.

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Older adults, if they live alone, they may
lose their desire to cook because of loneliness.

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The appetite of widows decreases after the
loss of a spouse or significant other.

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And they may, if they live alone, they may
have not be, they may lack access to transportation

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to buy food, and that can also put them at
risk for malnutrition.

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We know that many older adults are on a limited
income and they may restrict the number of

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meals eaten per day or the dietary quality
of their meals because they have to struggle

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with food vs. medicine vs. utilities.

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And the environment in which one lives can
also be a risk factor for malnutrition.

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In one study that we did with southeast Pennsylvania,
we found that those who lived alone lived

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below the poverty level, experienced difficulties
with housing costs, used public transportation

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and housing services and receive food stamps
and didn't have the internet were more

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likely to be malnourished than those older
adults who didn't experience these environmental

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conditions.

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And so put this all together, if there's a
decrease in dietary intake, we will see increased

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risk for malnutrition.

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And when we put this all together, we know
that in older adults that experience poor

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nutritional status, who have inadequate intake
of their protein energy or micronutrient intake

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can lead to, this can lead to functional decline
and eventually lead to negative outcomes,

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poor recovery, disability and frailty.

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So, we say, what is the risk of malnutrition
across the care continuum?

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We know for older adults, we want older adults
to experience the most appropriate care in

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the most appropriate setting.

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And much of what we know in the literature
is what's happening in the hospital setting

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in terms of malnutrition risk and incidence
and prevalence or in some post-acute care

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settings.

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But on this continuum, you can see there's
lots of touch points in which we could provide

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care for older adults and we should be doing
nutrition screening and assessment.

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Over on the right, because older adults may
age and place in different settings aside

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from their home, they're, again, we need to
rethink this continuum of care and think about

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different opportunities for us to provide
nutrition screening and assessment for older

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adults.

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Now, much of what we know about the prevalence
of malnutrition in older adults is from the

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acute care setting.

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This is nationally representative data from
the Health Care Costs and Utilization Project

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in 2010 and in 2018.

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In 2010 of the, there were 1.2 million people
who had malnutrition, who were discharged

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from the hospital with malnutrition.

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The mean age of those who were malnourished
was 64.8 years of age, and 58.3 percent of older

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adults had a malnutrition diagnosis.

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Fast forward to 2018 and there is the same
similar trends.

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The mean age of those with malnutrition was
64.8 and older adults accounted for 59.5 percent

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of all those who had a malnutrition diagnosis
during the hospital stay.

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But that's the acute care setting.

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What happens?

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Many older adults live, are free living older
adults in the community.

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There's very little nationally representative
data that describes nutrition prevalence or

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malnutrition prevalence in older adults living
in the community.

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We ran some data from the National Health
and Ageing Trends Study, which is a nationally

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representative sample.

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This data was presented at the Gerontological
Society of America meeting and we're in the

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process of writing up this paper and what
we found was 19% of those 85 years of age

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and older were malnourished and 39% of community
dwelling older adults, 75 to 84 were malnourished.

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And so there is more malnutrition in the older
age groups in this setting.

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We also know that there is a gap in not only,
there is a gap in how prevalent malnutrition

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is in older adults across the care continuum,
including these transitions of care when people

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are transferred from the hospital to their
home and what are the best treatment options

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in each setting.

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So we need more research in this area.

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Another gap that we see is how to best differentiate
malnutrition from other tissue loss syndromes

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in older adults such as cachexia, sarcopenia,
and frailty and how to treat malnutrition

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when it co-occurs with these tissue loss syndromes.

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Another gap we see are what are the best guidelines
for clinical nutrition in hydration in older

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adults across the care continuum?

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Given that more than 50% of hospitalized patients
in the U.S. with the diagnosis of malnutrition

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are older adults, now is the time for us in
the US to develop age appropriate nutrition

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and hydration guidelines.

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The Europeans have done that. ESPAN has published
their guidelines in 2019.

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And lastly, how prepared is the health care
workforce to recognize and treat malnutrition

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in older adults?

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In 2008, the then Institute of Medicine published
a report on retooling for an aging America,

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building the health care workforce to really
shed light on this.

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But the call to action today is are we prepared
to address the unique needs of an aging society?

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Are age appropriate nutrition screening and
assessment tools routinely used?

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And are we prepared to implement interdisciplinary
interventions?

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So, in summary, nutrition plays an important
role in healthy aging.

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There are bio psychosocial risk factors that can
impact nutritional status in older adults.

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Malnutrition can negatively impact health
outcomes.

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What is needed is an interdisciplinary collaborative
approach to recognize and treat malnutrition

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in older adults.

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And there is a great need for further research
on the role of tailored nutritional interventions

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to promote healthy aging, to treat malnutrition
and other related syndromes and to promote

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quality of life across the care continuum.

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So with that, thank you, and I look forward
to your questions.

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DR. CARRIE EARTHMAN: Hello, I'm Carrie Earthman,
and I'm pleased to be here to talk to you

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about body composition tools and nutrition
assessment.

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I have nothing to disclose.

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In this session, we'll talk about CT, ultrasound
and bio impedance variables for clinical nutrition

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assessment and consider research needs and
future directions.

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It is now well recognized that muscle is a
central component of nutritional status, and

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muscle loss is associated with poor clinical
outcomes and poor functional status.

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Interventions targeting muscle aim to improve
both clinical and functional outcomes.

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We need ways of measuring muscle both in our
initial assessments and ideally so we can

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monitor response to our interventions.

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The most common techniques available to clinicians
include CT, ultrasound and bio impedance.

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In order to interpret the measurements of
muscle or its surrogates that we obtain by

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a particular method, we need to have appropriate
cut points that define low muscularity.

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These are typically derived based on healthy
population data, whereas the fifth or tenth

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percentile for a particular clinical population
based on clinical outcomes.

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It is imperative to recognize that low muscularity
cut points differ by body composition method,

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by device and by the algorithm or prediction
equation applied.

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Clinicians should know that selection of reference
cut points should match the assessment method

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for best results in interpreting the information
obtained.

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So first, let's talk about CT.

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The most widely studied CT generated variables
come from total abdominal muscle at the level

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of the lumbar three vertebra.

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There have been some studies looking at just
the psoas muscles at the same location and

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the pectoralis muscle from chest CTs.

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We can look at muscle area and extrapolated
whole body measures like skeletal muscle index

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00:19:37,330 --> 00:19:44,030
in terms of quantity measures and muscle density
reflected by mean Hounsfield units to indicate

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muscle quality.

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I'll just highlight a few of the recent studies
in ICU patients to exemplify the CT-derived

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variables that could be useful for nutrition
assessment and monitoring.

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CT of the total abdomen at the level of L3 can be used to assess total abdominal

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00:19:59,140 --> 00:20:04,640
muscle area, which predicts mortality and
other clinical outcomes in cancer, liver failure

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00:20:04,640 --> 00:20:05,990
and critical illness.

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00:20:05,990 --> 00:20:11,040
And from these studies we have reference cut
points now for low muscularity.

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Total abdominal muscle area is also superior
to SGA for identifying low muscularity in

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00:20:16,230 --> 00:20:21,280
ICU patients and can be used to track muscle
changes over an ICU stay.

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CT at the level of L3 can also be used
to evaluate the psoas major muscle area, and

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00:20:27,710 --> 00:20:33,080
this can be used to track muscle quantity
changes in pancreatic cancer and lower psoas

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00:20:33,080 --> 00:20:39,120
muscle density predicts 90-day mortality and
other adverse outcomes in trauma patients.

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00:20:39,120 --> 00:20:43,380
For any of the body composition variables
that might serve as nutrition biomarkers,

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00:20:43,380 --> 00:20:47,330
we typically start by looking at its ability
to predict clinical outcomes, and then we

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want to know if the variable can identify
low muscularity or malnutrition.

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00:20:51,059 --> 00:20:55,410
An important next step is to see how well
the variable can track changes in response

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00:20:55,410 --> 00:20:57,240
to nutrition interventions.

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00:20:57,240 --> 00:21:01,909
In terms of CT, the largest amount of data
has been generated around the use of total

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00:21:01,909 --> 00:21:05,580
abdominal muscle to predict clinical outcomes,
including mortality.

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00:21:05,580 --> 00:21:10,160
These primarily come from cancer patients
with a limited number of studies and patients

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00:21:10,160 --> 00:21:13,740
with critical illness and liver failure.

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00:21:13,740 --> 00:21:16,070
There's growing interest in the use of quality
measures.

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00:21:16,070 --> 00:21:21,020
For example, mean Hounsfield units, which
represents the density of the abdominal muscle

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00:21:21,020 --> 00:21:24,220
to predict outcomes like mortality.

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00:21:24,220 --> 00:21:29,590
Little or no data are available on the psoas
muscle also at the L3 or the pectoralis

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00:21:29,590 --> 00:21:32,650
muscles in the chest for any of these areas.

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00:21:32,650 --> 00:21:37,770
Tracking changes can be challenging because
CTs are not always repeated for follow ups.

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00:21:37,770 --> 00:21:40,570
Now let's talk about ultrasound.

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00:21:40,570 --> 00:21:44,720
Although three or more site protocols are
thought to produce the best results, the most

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00:21:44,720 --> 00:21:49,549
widely studied single site has been the quadriceps
muscles due to clinical feasibility.

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00:21:49,549 --> 00:21:55,010
Muscles can be quantified in terms of area
or thickness, and muscle quality can be assessed

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00:21:55,010 --> 00:21:59,730
by quantifying echogenicity of a defined area
through histogram analysis.

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00:21:59,730 --> 00:22:05,059
This is a similar concept to muscle density
done in CT.

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00:22:05,059 --> 00:22:08,929
So here's a snapshot of where we are with
ultrasound derived variables.

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00:22:08,929 --> 00:22:14,050
Quadriceps muscle thickness can differentiate
malnourished from normally nourished hospitalized

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00:22:14,050 --> 00:22:20,610
individuals and a 3-site muscle protocol
using the biceps, forearm and thigh can provide

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00:22:20,610 --> 00:22:26,669
reliable estimates of muscle changes during
ICU stays and during nutrition intervention.

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00:22:26,669 --> 00:22:30,950
Other studies have shown that the rectus femoris
cross-sectional area measures can track muscle

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00:22:30,950 --> 00:22:34,220
changes over a course of an ICU stay.

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00:22:34,220 --> 00:22:39,039
And then quadriceps muscle quality as assessed
by echogenicity has been shown to decrease

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00:22:39,039 --> 00:22:43,880
with diminished function and tissue necrosis
during an ICU stay.

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00:22:43,880 --> 00:22:48,770
We have some data on the use of total quadriceps
and rectus femoris thickness and quality

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00:22:48,770 --> 00:22:51,570
to predict poor outcomes in malnourished status.

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00:22:51,570 --> 00:22:54,720
But in general, we need more work on ultrasound.

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00:22:54,720 --> 00:22:59,890
The use of it is complicated by lack of consensus
on protocol, including sites to measure, and

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00:22:59,890 --> 00:23:04,340
which, if any, single site is best to use
to represent whole body, muscle and nutritional

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00:23:04,340 --> 00:23:05,909
status.

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00:23:05,909 --> 00:23:10,840
Commercially available ultrasound instruments
don't record the angle or anisotropy of your

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00:23:10,840 --> 00:23:15,779
measurement, and this is a concern for longitudinal
measures of muscle quality because echogenicity

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00:23:15,779 --> 00:23:20,600
or density measures are altered by the probe
not being 90 degrees to the muscle.

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00:23:20,600 --> 00:23:25,110
Furthermore, landmarking and visualization
of the muscle can be quite challenging in

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00:23:25,110 --> 00:23:29,330
individuals with extreme obesity and in those
with substantial edema.

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00:23:29,330 --> 00:23:33,890
Finally, it's not clear that it will be possible
to establish appropriate reference cut points

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00:23:33,890 --> 00:23:38,929
for muscle thickness or quality measures given
device and protocol differences.

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00:23:38,929 --> 00:23:41,970
Next, let's talk about bio impedance techniques.

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There are three primary categories of bio
impedance devices, including single frequency

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00:23:48,000 --> 00:23:54,150
bioelectrical impedance analysis, multi frequency
BIA, and bio impedance spectroscopy.

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A number of whole body and raw variables have
been proposed as nutrition biomarkers.

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00:23:57,970 --> 00:24:01,030
I've shown the most commonly studied ones.

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00:24:01,030 --> 00:24:04,760
The bars indicate which type of device can
generate the variable.

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00:24:04,760 --> 00:24:08,190
For example, BIS devices can generate all
of the whole body variables.

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00:24:08,190 --> 00:24:14,289
Similarly, raw variables are listed on the
right side of the slide in a similar fashion.

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00:24:14,289 --> 00:24:18,260
As shown on the previous slide, these are
some of the more promising whole body measures

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00:24:18,260 --> 00:24:20,580
and raw variables.

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00:24:20,580 --> 00:24:24,860
So here's a snapshot of some of the bio impedance
derived variables that have been used for

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00:24:24,860 --> 00:24:29,570
nutritional assessment in ICU and hospitalized
patients.

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00:24:29,570 --> 00:24:33,880
Appendicular skeletal muscle index and other
muscle indices by single frequency BIA equations

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00:24:33,880 --> 00:24:38,840
such as the Kyle or Janssen equation have
been shown to correlate with CT-derived muscle

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00:24:38,840 --> 00:24:41,010
mass in ICU patients.

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00:24:41,010 --> 00:24:46,659
Fat free mass by single frequency BIA using
the Kyle equation and 50 kilohertz phase angle

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00:24:46,659 --> 00:24:52,980
have been shown to agree with SGA and hospitalized
patients for identifying malnutrition.

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00:24:52,980 --> 00:24:57,570
Normally hydrated lean tissue by BIS has been
shown to correlate with CT abdominal muscle

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00:24:57,570 --> 00:25:01,539
area and tracks losses over an ICU stay.

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00:25:01,539 --> 00:25:07,149
Impedance ratio at 200 to over five kilohertz
and 50 kilohertz phase angle can differentiate

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00:25:07,149 --> 00:25:11,400
malnourished from nourished hospitalized patients
and are correlated with low muscle quantity

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00:25:11,400 --> 00:25:16,080
and quality by CT of the abdomen in ICU patients.

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00:25:16,080 --> 00:25:24,399
BIS-generated variables including higher characteristic
frequency resistance at infinity over zero

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00:25:24,399 --> 00:25:30,770
frequency and 200 to 5 kilohertz impedance
ratio and lower membrane capacitance and phase

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00:25:30,770 --> 00:25:36,380
angle were associated with worse clinical
outcomes and muscle function in ICU patients.

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00:25:36,380 --> 00:25:41,600
50 kilohertz phase angle is the most widely
studied raw bio impedance variable, followed

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00:25:41,600 --> 00:25:46,350
by whole body fat free mass generated by the
Kyle equation, which is a single frequency

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00:25:46,350 --> 00:25:48,080
BIA equation.

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00:25:48,080 --> 00:25:54,210
To a lesser extent, the 200 to 5 kilohertz
impedance ratio generated by multifrequency

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00:25:54,210 --> 00:25:59,720
or BIS devices has been shown to predict outcomes
and identify malnourished individuals in some

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00:25:59,720 --> 00:26:01,450
clinical populations.

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00:26:01,450 --> 00:26:06,100
Normally hydrated lean tissue generated by
one of the BIS algorithms applied in patients

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00:26:06,100 --> 00:26:11,370
on dialysis has been shown to predict outcomes
and nutritional status in that population.

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00:26:11,370 --> 00:26:16,409
There is growing interest in BIS-generated
variables, but more data are needed on all

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00:26:16,409 --> 00:26:20,899
of the bioimpedance-derived variables,
particularly to understand which ones might

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00:26:20,899 --> 00:26:26,280
be most useful to monitor response to interventions
in various clinical populations.

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00:26:26,280 --> 00:26:31,049
Reference cut points for interpretation of
measures are device and population specific

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00:26:31,049 --> 00:26:33,770
and data are lacking in most populations.

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00:26:33,770 --> 00:26:39,740
The GLIM Working group has called for greater
detail on what body composition measures should

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00:26:39,740 --> 00:26:44,659
be used and the specific cut points required
for determining low muscle mass.

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00:26:44,659 --> 00:26:47,150
So where do we go from here?

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00:26:47,150 --> 00:26:51,970
Clinical nutrition intervention studies can
help us validate the GLIM malnutrition diagnostic

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00:26:51,970 --> 00:26:57,730
criteria, specifically low muscularity or
muscle deficits, and further refine the methods

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00:26:57,730 --> 00:27:02,409
we can use to determine low muscle mass or
quality in clinical settings by capturing

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00:27:02,409 --> 00:27:04,120
muscle changes.

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00:27:04,120 --> 00:27:08,320
These studies should include reference measures
of body composition in addition to field methods.

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00:27:08,320 --> 00:27:13,720
And although it's not easy, it would be ideal
to include repeat measures so we can understand

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00:27:13,720 --> 00:27:20,669
the precision of a method so we can determine
if the change that it is measuring is real.

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00:27:20,669 --> 00:27:25,440
These intervention studies can help us establish
relevant cut points for various body composition

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00:27:25,440 --> 00:27:30,960
variables to define low muscle mass and/or
muscle quality, and to differentiate moderate

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00:27:30,960 --> 00:27:34,169
from severe malnutrition using muscle measures.

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00:27:34,169 --> 00:27:39,270
We need to know how should low muscularity
cut points best be defined. By reference method

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00:27:39,270 --> 00:27:45,470
muscle measures or malnutrition reference
standards, or by clinical outcomes?

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00:27:45,470 --> 00:27:50,610
We know that reference cut points are typically
specific to device in addition to ethnicity,

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00:27:50,610 --> 00:27:52,550
sex and age.

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00:27:52,550 --> 00:27:57,620
We could have whole body or isolated muscle
quantity or quality measures or simple variables

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00:27:57,620 --> 00:28:03,370
such as 50 kilohertz phase angle or BIS derived
variables that serve as biomarkers for muscle

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00:28:03,370 --> 00:28:05,340
health or nutritional status.

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00:28:05,340 --> 00:28:11,149
In summary, we know how important muscle is
to the assessment of nutritional status and

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00:28:11,149 --> 00:28:16,490
clinical outcomes, but it's not always easy
to measure and there are no direct ways of

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00:28:16,490 --> 00:28:17,620
getting at it.

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00:28:17,620 --> 00:28:23,309
Several CT, ultrasound, and bio impedance generated
variables are potential candidates to serve

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00:28:23,309 --> 00:28:26,799
as biomarkers of muscle health and thus nutritional
status.

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00:28:26,799 --> 00:28:31,880
A growing number of these have been shown
to predict clinical outcomes and to identify

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00:28:31,880 --> 00:28:34,440
malnutrition and low muscularity.

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00:28:34,440 --> 00:28:39,559
Fewer of them have been evaluated for their
ability to track changes in response to interventions.

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00:28:39,559 --> 00:28:44,419
Ultimately, precision and reliability need
to be evaluated in order to determine how

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00:28:44,419 --> 00:28:49,380
well a body composition derived biomarker
can detect meaningful changes in a given setting.

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00:28:49,380 --> 00:28:53,519
And we need to know which ones are worth the
time for clinicians to measure during nutrition

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00:28:53,519 --> 00:28:55,460
assessments.

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00:28:55,460 --> 00:28:59,760
Thank you for your attention.

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00:28:59,760 --> 00:29:15,100
DR. JOANNE REID: Hello and thank you for joining
this presentation on Renal Cachexia.

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00:29:15,100 --> 00:29:16,280
My name is Joanne Reid.

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00:29:16,280 --> 00:29:19,500
I work at the School of Nursing and Midwifery
and Queen's University in Belfast within the

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00:29:19,500 --> 00:29:24,280
United Kingdom, where I need a program of
research on renal cachexia.

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00:29:24,280 --> 00:29:30,740
To start with, I would like to thank the organizing
committee for the opportunity to present at

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00:29:30,740 --> 00:29:33,500
this virtual meeting.

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00:29:33,500 --> 00:29:37,970
Chronic kidney disease has become a global
health burden and it's associated with increased

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00:29:37,970 --> 00:29:40,220
morbidity and mortality.

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00:29:40,220 --> 00:29:45,090
And particular wasting is highly prevalent
in the later stages of illness.

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00:29:45,090 --> 00:29:48,980
Protein energy wasting syndrome and chronic
kidney disease was a term first developed

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00:29:48,980 --> 00:29:55,470
by the International Society of Renal Nutrition
and Metabolism, and it's defined as a state of decreased

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00:29:55,470 --> 00:30:00,740
body stores of protein and energy fuels which
occurs progressively under specific to chronic

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00:30:00,740 --> 00:30:03,270
kidney disease.

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00:30:03,270 --> 00:30:08,519
There's multiple terminology in relation to
malnutrition that has been identified, linked

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00:30:08,519 --> 00:30:11,260
to wasting and chronic kidney disease.

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00:30:11,260 --> 00:30:16,930
These include malnutrition, disease-related
malnutrition, protein energy wasting, cachexia,

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00:30:16,930 --> 00:30:19,770
sarcopenia and muscle wasting.

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00:30:19,770 --> 00:30:25,570
The etiology and the progression of renal
cachexia is complex and it's multifactorial,

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00:30:25,570 --> 00:30:33,510
and there is a need to have consistent terminology
which has been agreed when referring to renal

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00:30:33,510 --> 00:30:34,650
cachexia.

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00:30:34,650 --> 00:30:38,610
And that's really important because the treatment
approach for this needs to be specific to

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00:30:38,610 --> 00:30:43,940
reflect the multifactorial etiology of renal
cachexia.

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00:30:43,940 --> 00:30:48,279
The review shown here highlights that the
recent understanding of cachexia pathophysiology

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00:30:48,279 --> 00:30:52,919
during chronic kidney disease progression
suggests that protein energy wasting and cachexia

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00:30:52,919 --> 00:30:54,260
are closely related.

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00:30:54,260 --> 00:30:59,529
And that protein energy wasting corresponds
to the initial state of a continuous process

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00:30:59,529 --> 00:31:06,280
that leads onto cachexia implicating the same
metabolic pathways as in other chronic diseases.

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00:31:06,280 --> 00:31:12,370
The paper also advocates the application of
a uniform term such as kidney disease cachexia

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00:31:12,370 --> 00:31:16,240
to inform future research and practice.

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00:31:16,240 --> 00:31:20,870
In 2008, Belevence and colleagues developed
a consensus operational definition for cachexia

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00:31:20,870 --> 00:31:26,950
and chronic illness, and also associated clinical
features which are shown here.

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00:31:26,950 --> 00:31:31,950
Cachexia is known to increase morbidity and
mortality, and to date, there is no gold standard

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00:31:31,950 --> 00:31:33,610
treatment.

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00:31:33,610 --> 00:31:39,570
While malnutrition is often present in cachexia,
the clinical characteristic of cachexia is

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00:31:39,570 --> 00:31:42,399
that it cannot be treated with nutrition alone.

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00:31:42,399 --> 00:31:48,340
In terms of research gaps and opportunities
in relation to renal cachexia, we have led

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00:31:48,340 --> 00:31:53,000
national and international studies on this
area and the publications from that are shown

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00:31:53,000 --> 00:31:54,000
here.

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00:31:54,000 --> 00:31:57,419
Previous work has focused on the clinical
phenotype of renal cachexia, and also healthcare

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00:31:57,419 --> 00:31:59,669
professionals in the management of renal cachexia.

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00:31:59,669 --> 00:32:04,140
We're going to take a look at those in the
next few slides.

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00:32:04,140 --> 00:32:07,880
Our initial study sought to ascertain the
clinical phenotype of renal cachexia.

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00:32:07,880 --> 00:32:13,820
And we drew from the work of Evans et. al.,
shown in slide four to inform the inclusion

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00:32:13,820 --> 00:32:16,919
criteria for this study.

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00:32:16,919 --> 00:32:21,899
This was a longitudinal study of adult
hemodialysis patients who were attending two

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00:32:21,899 --> 00:32:24,950
nephrology units within the United Kingdom.

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00:32:24,950 --> 00:32:29,899
There are approximately 310 patients with
end stage renal disease receiving hemodialysis

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00:32:29,899 --> 00:32:33,110
who were cared for within those two nephrology
sites.

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00:32:33,110 --> 00:32:38,670
And we did a prospective sample size and we
recruited 106 patients who satisfied

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00:32:38,670 --> 00:32:43,850
an 80% confidence level limit and we followed
these participants for one year.

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00:32:43,850 --> 00:32:49,419
At baseline, we had 17 patients who were identified
as cachectic.

399
00:32:49,419 --> 00:32:54,020
You can see here the clinical characteristics
of the patients who were recruited into the

400
00:32:54,020 --> 00:32:55,020
study.

401
00:32:55,020 --> 00:32:58,679
And along the left hand side, we have those
clinical characteristics based on the Evans

402
00:32:58,679 --> 00:33:04,230
definition of cachexia previously shared,
with note to appetite were significantly lower

403
00:33:04,230 --> 00:33:09,250
in the cachectic population mental upper arm,
muscle circumference and handgrip strength

404
00:33:09,250 --> 00:33:11,720
were also lower and CRP was raised within
the cachectic group.

405
00:33:11,720 --> 00:33:20,760
We had 70 patients included in the final assessment
point at the end of month 12.

406
00:33:20,760 --> 00:33:22,620
Reasons for non-follow up included death,
withdrawal.

407
00:33:22,620 --> 00:33:30,029
We had three patients who started home peritoneal
dialysis and one who was lost to follow up.

408
00:33:30,029 --> 00:33:35,159
Of note, significant changes were seen in
handgrip strength, anorexia, fatigue at 12

409
00:33:35,159 --> 00:33:37,840
months for the 70 patients who remained within
the study.

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00:33:37,840 --> 00:33:44,679
And for the cachectic group, they showed significant
mean effect on time for handgrip strength,

411
00:33:44,679 --> 00:33:47,620
fatigue and anorexia.

412
00:33:47,620 --> 00:33:51,230
And looking at the multimethod study exploring
health care professionals awareness, understanding

413
00:33:51,230 --> 00:33:58,220
and current treatment practices in relation
to renal cachexia, we recruited 93 healthcare

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00:33:58,220 --> 00:34:01,260
professionals from 30 countries globally.

415
00:34:01,260 --> 00:34:06,950
Results from this study highlighted that renal
cachexia remains an underdiagnosed and undertreated

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00:34:06,950 --> 00:34:07,950
condition.

417
00:34:07,950 --> 00:34:12,070
But health care professionals deemed the most
important factors when treating renal cachexia

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00:34:12,070 --> 00:34:17,510
to be an improvement in quality of life and
also relief of family distress in relation

419
00:34:17,510 --> 00:34:18,889
to the syndrome.

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00:34:18,889 --> 00:34:23,570
Looking at the responses of the healthcare
professionals who took part within the study,

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00:34:23,570 --> 00:34:29,480
the most commonly reported symptoms of cachexia
were weight loss and also anorexia.

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00:34:29,480 --> 00:34:34,649
Primary factor leading to treatment for cachexia
being prescribed was recorded as weight loss

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00:34:34,649 --> 00:34:36,940
above 5%.

424
00:34:36,940 --> 00:34:41,790
The majority of participants reported that
if a patient had weight loss above 5% which

425
00:34:41,790 --> 00:34:44,419
was involuntary, that they would consider
them to be cachectic.

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00:34:44,419 --> 00:34:48,810
And when asked what improvements they would
like to see in relation to renal cachexia,

427
00:34:48,810 --> 00:34:55,149
68% of respondents highlighted the need for
a disease specific definition in relation

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00:34:55,149 --> 00:35:01,119
to renal cachexia to help identify patients
within their clinical practice.

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00:35:01,119 --> 00:35:07,670
For patients with or who are at risk of cachexia,
a comprehensive multimodal treatment strategy

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00:35:07,670 --> 00:35:11,710
is required to target the multifactorial etiology
of cachexia.

431
00:35:11,710 --> 00:35:16,080
And we conducted a critical review of the
literature looking at the current evidence

432
00:35:16,080 --> 00:35:17,589
in relation to this.

433
00:35:17,589 --> 00:35:23,119
Within this review, we included papers on
cancer, COPD and renal disease, and it's the

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00:35:23,119 --> 00:35:26,930
renal data that's presented here of the included
studies.

435
00:35:26,930 --> 00:35:32,760
Two of the four multimodal interventions for
CKD did not define criteria for severe wasting.

436
00:35:32,760 --> 00:35:38,780
And the remaining two studies used the protein
energy wasting definition that we discussed

437
00:35:38,780 --> 00:35:42,940
earlier that was developed by Danny Folk and
colleagues in 2008.

438
00:35:42,940 --> 00:35:45,130
However, even within that, there were differences.

439
00:35:45,130 --> 00:35:50,250
For example, one of the studies did not mention
reduced dietary intake as part of their criteria.

440
00:35:50,250 --> 00:35:54,980
Additionally, if you look at these studies,
you can see heterogeneity across the treatment

441
00:35:54,980 --> 00:35:58,380
characteristics and also the endpoints measured.

442
00:35:58,380 --> 00:36:04,670
Despite limitations of the study such as small
sample size, for example, these studies do

443
00:36:04,670 --> 00:36:08,030
show greater improved endpoints when combining
treatment modalities.

444
00:36:08,030 --> 00:36:13,599
But what they also demonstrate is
that we need larger and we need better parred

445
00:36:13,599 --> 00:36:19,380
studies and that we also need increased research
collaborations to optimize future trials of

446
00:36:19,380 --> 00:36:23,060
multimodal interventions within this area.

447
00:36:23,060 --> 00:36:29,010
Following on from our critical review sought
to develop a multimodal intervention which

448
00:36:29,010 --> 00:36:35,200
had components of anti-inflammatory agents,
exercise and also dietary counseling.

449
00:36:35,200 --> 00:36:40,760
Importantly, we also incorporated psychosocial
support, which none of the studies included

450
00:36:40,760 --> 00:36:42,700
and the critical review reported on.

451
00:36:42,700 --> 00:36:47,760
However, we do know from current and previous
research that there is a need to address the

452
00:36:47,760 --> 00:36:53,340
emotional and also the social context around
reduced appetite that's seen in cachexia as

453
00:36:53,340 --> 00:36:56,870
they can impact on distress and anxiety.

454
00:36:56,870 --> 00:37:02,579
So, we developed this multimodal intervention
around a theory of change.

455
00:37:02,579 --> 00:37:09,130
This slide represents the Theory of Change
map for our proposed intervention, our multimodal

456
00:37:09,130 --> 00:37:13,650
intervention, including anti-inflammatory
dietary, counseling and exercise intervention

457
00:37:13,650 --> 00:37:19,869
components, which you can see here highlighted
within the intervention stage.

458
00:37:19,869 --> 00:37:25,290
We used input from stakeholders from various
backgrounds to help inform the development

459
00:37:25,290 --> 00:37:31,300
of this map, and they included personal and
public involvement representatives as well

460
00:37:31,300 --> 00:37:35,829
as nephrology health care professionals, our
own previous research in this program of work

461
00:37:35,829 --> 00:37:41,180
that we've shown previously on slide five
and also international literature within this

462
00:37:41,180 --> 00:37:42,180
area.

463
00:37:42,180 --> 00:37:47,250
So, where are we currently in relation to
research gaps and opportunities in relation

464
00:37:47,250 --> 00:37:48,290
to renal cachexia?

465
00:37:48,290 --> 00:37:53,369
Well, we are currently undertaking a qualitative
study based on phenomenology to explore the

466
00:37:53,369 --> 00:37:58,280
lived experience of renal cachexia with both
patients and their informal carers.

467
00:37:58,280 --> 00:38:00,350
That data hasn't been previously reported.

468
00:38:00,350 --> 00:38:05,500
We'd also like to undertake a Cochrane review
of the evidence in relation to multimodal

469
00:38:05,500 --> 00:38:07,880
interventions for cachexia management.

470
00:38:07,880 --> 00:38:14,079
And what we would like to do is continue to
develop the evidence base to inform a multi-site

471
00:38:14,079 --> 00:38:18,230
randomized controlled trial for multimodal
intervention and renal cachexia.

472
00:38:18,230 --> 00:38:25,819
I'd like to acknowledge our current international
interdisciplinary working group and funders

473
00:38:25,819 --> 00:38:32,570
who have been involved in our program of research
in relation to renal cachexia.

474
00:38:32,570 --> 00:38:38,540
Thank you for your company during this presentation
and I look forward to seeing you in the panel

475
00:38:38,540 --> 00:38:39,540
discussion.

476
00:38:39,540 --> 00:38:44,990
DR. MARY PLATEK: Hi, and thank you for the
opportunity to provide a summary of the ASCO

477
00:38:44,990 --> 00:38:50,820
Cancer Cachexia Guidelines that were published
in 2020.

478
00:38:50,820 --> 00:38:57,510
Our purpose was to provide evidence-based
guidance on the optimal approach for treating

479
00:38:57,510 --> 00:39:00,250
cachexia in patients with advanced cancer.

480
00:39:00,250 --> 00:39:07,110
Based on several published resources, we defined
cachexia as a multifactorial syndrome that

481
00:39:07,110 --> 00:39:13,560
is characterized by a variety of clinical
features, such as loss of appetite, weight,

482
00:39:13,560 --> 00:39:20,450
skeletal muscle fatigue, functional decline,
increased treatment related toxicity, poor

483
00:39:20,450 --> 00:39:24,480
quality of life, and inferior survival.

484
00:39:24,480 --> 00:39:34,589
Among patients with advanced cancer, cachexia
is noted in about 50% of the population, despite

485
00:39:34,589 --> 00:39:37,460
the type of malignancy.

486
00:39:37,460 --> 00:39:45,770
Historically, the screening of, assessment
of, and management for cancer cachexia has

487
00:39:45,770 --> 00:39:48,740
been beyond challenging.

488
00:39:48,740 --> 00:40:01,650
The methodology for the guideline is established
by the ASCO clinical practice guideline committee involving

489
00:40:01,650 --> 00:40:07,010
systematic literature review, expert panel
to critically review the evidence and interpret

490
00:40:07,010 --> 00:40:13,040
the evidence, and then a guideline that must
be approved by ASCO.

491
00:40:13,040 --> 00:40:21,079
Our target population for the review were
adult patients with advanced cancer and with

492
00:40:21,079 --> 00:40:23,619
a loss of appetite, body weight and/or lean
body mass.

493
00:40:23,619 --> 00:40:29,630
The audience for the guideline are clinicians
providing care for these patients as well

494
00:40:29,630 --> 00:40:35,540
as the patients themselves and the caregivers.

495
00:40:35,540 --> 00:40:42,369
Three clinical questions were established
for this review, using the target population

496
00:40:42,369 --> 00:40:50,099
do nutritional interventions, question one,
pharmacologic interventions, question two

497
00:40:50,099 --> 00:40:58,560
and or other interventions such as exercise
improve weight, lean body, mass appetite,

498
00:40:58,560 --> 00:41:05,370
physical function, or quality of life in these
patients?

499
00:41:05,370 --> 00:41:08,920
We searched only for randomized controlled
trials.

500
00:41:08,920 --> 00:41:12,360
This search brought in 1,374 papers.

501
00:41:12,360 --> 00:41:22,349
After initial screening we had 134 papers
to thoroughly review, leaving 36 papers to

502
00:41:22,349 --> 00:41:29,010
be included in this guideline, 20 of whom
were systematic reviews of randomized controlled

503
00:41:29,010 --> 00:41:31,080
trials.

504
00:41:31,080 --> 00:41:37,480
For clinical question number one, the impact
of nutrition interventions, we recommend that

505
00:41:37,480 --> 00:41:44,690
clinicians may refer their patients to a registered
dietitian for both assessment and counseling,

506
00:41:44,690 --> 00:41:50,020
sessions should include both the patient and
the caregiver, there should be a focus on

507
00:41:50,020 --> 00:41:57,990
practical and safe advice for feeding and
advice against those fad diets or things unproven,

508
00:41:57,990 --> 00:42:05,300
such as extreme dieting, education should
be provided to these patients for high protein,

509
00:42:05,300 --> 00:42:11,310
high calorie and nutrient dense types of foods.

510
00:42:11,310 --> 00:42:15,690
The strength of the recommendation was moderate,
as noted on a slide.

511
00:42:15,690 --> 00:42:19,890
In the evidence, quality it was rated low.

512
00:42:19,890 --> 00:42:26,670
For the entire group of nutrition interventions,
the best evidence was for dietary counseling.

513
00:42:26,670 --> 00:42:36,240
Unfortunately, in most trials, the definition
for dietary counseling details were very,

514
00:42:36,240 --> 00:42:38,690
very vague.

515
00:42:38,690 --> 00:42:47,950
Additionally, for nutrition interventions,
in particular, nutrition support should not

516
00:42:47,950 --> 00:42:51,820
be routinely offered to manage cachexia.

517
00:42:51,820 --> 00:42:59,460
A short term trial of parenteral in nutrition
might be offered to a very select group of

518
00:42:59,460 --> 00:43:10,839
patients, such as those who have a reversible
bowel obstruction and short bowel syndrome, etc.

519
00:43:10,839 --> 00:43:17,300
Discontinuation of previous types of nutrition
support near the end of life and the end of

520
00:43:17,300 --> 00:43:20,109
life is appropriate.

521
00:43:20,109 --> 00:43:25,010
Nutrition support should remain to be on an
individual basis.

522
00:43:25,010 --> 00:43:31,100
There is no recommendation for omega-3
fatty acids, vitamins, minerals, other particular

523
00:43:31,100 --> 00:43:36,559
dietary supplements because the evidence was
lacking.

524
00:43:36,559 --> 00:43:46,150
Next, we investigated pharmacologic interventions
and up to the time of this systematic review,

525
00:43:46,150 --> 00:43:52,260
evidence was insufficient to strongly endorse
any pharmacologic agent.

526
00:43:52,260 --> 00:44:00,380
To improve outcomes, clinicians could choose
not to offer medications for the treatment

527
00:44:00,380 --> 00:44:02,220
of cancer cachexia.

528
00:44:02,220 --> 00:44:12,040
There are currently no FDA-approved medications
for the indication of cancer cachexia.

529
00:44:12,040 --> 00:44:22,210
However, based on the evidence, it was recommended
that clinicians could offer a short term trial

530
00:44:22,210 --> 00:44:29,770
of progesterone analogue or corticosteroid
to their patients experiencing the loss of

531
00:44:29,770 --> 00:44:35,200
appetite and/or body weight, and the choice
of the agent and the duration of the treatment

532
00:44:35,200 --> 00:44:40,650
would depend on the treatment goals that were
developed for the patient.

533
00:44:40,650 --> 00:44:47,230
And lastly, the third question looked at other
interventions; for example, exercise.

534
00:44:47,230 --> 00:44:53,020
It could have been combined with nutrition
or pharmacologic, but we were looking at other

535
00:44:53,020 --> 00:44:59,030
interventions, and outside of the context
of a clinical trial, there really is no recommendation

536
00:44:59,030 --> 00:45:05,079
that could be made for other interventions,
such as exercise for the management of those

537
00:45:05,079 --> 00:45:08,079
who present with cancer cachexia.

538
00:45:08,079 --> 00:45:17,170
Based on our work and our discussions with
the expert group, we wanted to highlight the

539
00:45:17,170 --> 00:45:24,460
importance of communication in our approaches
to cancer cachexia.

540
00:45:24,460 --> 00:45:31,660
So, communication involving the patient, the
caregiver and the clinician, it's a highly

541
00:45:31,660 --> 00:45:36,660
stressful stage and it's important to have
good communication.

542
00:45:36,660 --> 00:45:41,980
Here are some key points that could be helpful,
and those are listed here on the slide under

543
00:45:41,980 --> 00:45:49,470
bullet number two, these were previously published
as well as referring to a registered dietitian

544
00:45:49,470 --> 00:45:55,820
to provide the patients and the caregivers
with more opportunity to discuss their concerns

545
00:45:55,820 --> 00:46:00,040
and challenges.

546
00:46:00,040 --> 00:46:06,570
We also include information in our guideline
about cost considerations that, for those

547
00:46:06,570 --> 00:46:15,540
patients that are paying higher out-of-pocket
costs, that might be a barrier for them to

548
00:46:15,540 --> 00:46:26,150
comply with the treatment, that cost for various
types of medications very, very markedly depending

549
00:46:26,150 --> 00:46:30,839
upon negotiated discounts and rebates.

550
00:46:30,839 --> 00:46:36,609
And that when it's practical and when it's
reasonable to use a less expensive alternative,

551
00:46:36,609 --> 00:46:40,559
that might be something to be considered.

552
00:46:40,559 --> 00:46:48,160
And that this should all be discussed as part
of shared decision making.

553
00:46:48,160 --> 00:46:53,380
The major limitations noted from investigating
this clinical research include the use of

554
00:46:53,380 --> 00:47:00,960
highly varied definitions, heterogeneous endpoints
and a lack of integrated biomarkers.

555
00:47:00,960 --> 00:47:07,590
The most recent definitions of cancer cachexia
do not capture the clinical impact of this

556
00:47:07,590 --> 00:47:09,710
syndrome.

557
00:47:09,710 --> 00:47:15,920
Future research could focus on a number of
endpoints as well as an assessment of changes

558
00:47:15,920 --> 00:47:19,470
in patient reported outcomes.

559
00:47:19,470 --> 00:47:27,420
Additionally, cancer cachexia research should
be identifying and validating novel biomarkers.

560
00:47:27,420 --> 00:47:32,660
Currently there are multiple clinical trials
evaluating novel pharmacologic agents for

561
00:47:32,660 --> 00:47:40,380
this treatment, for the treatment of cancer
cachexia and so those results are pending.

562
00:47:40,380 --> 00:47:49,890
And lastly, another area of future research
interest might involve evaluating an earlier

563
00:47:49,890 --> 00:47:56,820
nutritional interventions in patients that
have metastatic cancer.

564
00:47:56,820 --> 00:48:04,530
Additional information may be found on the
ASCO.org site for clinicians and patient information

565
00:48:04,530 --> 00:48:10,569
is available at cancer.net.

566
00:48:10,569 --> 00:48:17,630
This is a listing of the expert panel that
was involved in this work and references follow

567
00:48:17,630 --> 00:48:19,660
on this slide deck.

568
00:48:19,660 --> 00:48:29,270
I thank you all for your attention.

569
00:48:29,270 --> 00:48:38,079
DR. DAVID SERES: Wonderful presentations.

570
00:48:38,079 --> 00:48:41,030
We have a number of questions.

571
00:48:41,030 --> 00:48:44,780
Oh, good, there is Mary.

572
00:48:44,780 --> 00:48:47,290
The first one was going to be for you.

573
00:48:47,290 --> 00:48:49,690
Thank you.

574
00:48:49,690 --> 00:48:54,760
One of the themes that's come out of this
conference, and especially in this part of

575
00:48:54,760 --> 00:49:02,359
the session, we were talking about refractory
nutrition and certainly the way that the ASCO

576
00:49:02,359 --> 00:49:09,570
guidelines have presented, it would seem,
given the similarities between cachexia and

577
00:49:09,570 --> 00:49:16,609
malnutrition, that you are sort of saying
that malnutrition in patients with cancer

578
00:49:16,609 --> 00:49:21,190
is a refractory malnutrition.

579
00:49:21,190 --> 00:49:26,309
I'm wondering if there's been any work done
on looking at the cancer types, specifically

580
00:49:26,309 --> 00:49:29,230
those that are inflammatory versus those that
are not.

581
00:49:29,230 --> 00:49:35,970
We have experience taking care of patients
with sarcomas that live for years versus patients

582
00:49:35,970 --> 00:49:40,880
with, you know, an adenocarcinoma of the pancreas
living for months.

583
00:49:40,880 --> 00:49:46,270
And one would assume that the patients who
have the longer longevity might benefit from

584
00:49:46,270 --> 00:49:48,190
nutrition support.

585
00:49:48,190 --> 00:49:49,369
Any thoughts on that?

586
00:49:49,369 --> 00:49:57,430
(RECORDING PLAYS) One would assume that patients
who have a longer longevity. (RECORDING ENDS)

587
00:49:57,430 --> 00:50:03,260
DR. MARY PLATEK: For some reason I have bad
audio, does anybody else?

588
00:50:03,260 --> 00:50:04,260
No?

589
00:50:04,260 --> 00:50:07,660
DR. DAVID SERES: And my voice just echoed (INAUDIBLE).

590
00:50:07,660 --> 00:50:21,910
(RECORDING PLAYS) And my voice just echoed
(INAUDIBLE). (RECORDING ENDS)

591
00:50:21,910 --> 00:50:29,350
DR. MARY PLATEK: I have an answer, but I've got double
things going on here.

592
00:50:29,350 --> 00:50:33,780
So, maybe move on from me and maybe someone
can help me with my audio?

593
00:50:33,780 --> 00:50:36,549
I'm really sorry.

594
00:50:36,549 --> 00:50:44,890
DR. DAVID SERES: Mute your speaker or your mic, I mean.

595
00:50:44,890 --> 00:50:48,660
Mute your mic. OK.

596
00:50:48,660 --> 00:50:57,620
So, actually it's sort of a related question
and, Dr. Reid, you can talk about this with us.

597
00:50:57,620 --> 00:51:02,430
Do you think we're going to find different
kinds of cachexia, that there are different

598
00:51:02,430 --> 00:51:09,270
mechanisms or that there's something different
between disease states? You know, should we

599
00:51:09,270 --> 00:51:16,510
try and come up with a universal definition
of cachexia or should we stick with going

600
00:51:16,510 --> 00:51:20,559
with disease specific definitions?

601
00:51:20,559 --> 00:51:21,790
What are your thoughts there?

602
00:51:21,790 --> 00:51:25,010
DR. JOANNE REID: Thanks so much, David.

603
00:51:25,010 --> 00:51:31,530
I think that it's great to have a universal definition
of cachexia and chronic illness as a jumping

604
00:51:31,530 --> 00:51:32,530
off point.

605
00:51:32,530 --> 00:51:36,561
And that work was really important because
it helped them refine checking who was in

606
00:51:36,561 --> 00:51:41,230
the cancer population, a cancer cachexia specific
definition.

607
00:51:41,230 --> 00:51:45,750
But my personal view is that it is really
important to look at that definition across

608
00:51:45,750 --> 00:51:46,790
different diseases.

609
00:51:46,790 --> 00:51:51,700
So, for example, within a cancer cachexia
population you'd expect to CRP over five.

610
00:51:51,700 --> 00:51:57,670
Well, if you think about cachexia in patients
who have hemodialysis, who are receiving hemodialysis,

611
00:51:57,670 --> 00:52:01,890
their CRPs are all going to be over five due
to the fact that they're receiving hemodialysis.

612
00:52:01,890 --> 00:52:06,970
And if you think about the hemoglobin, so
the cancer population, looking at that definition,

613
00:52:06,970 --> 00:52:13,140
if you're looking for a hemoglobin less than
12, again because of active anemia management,

614
00:52:13,140 --> 00:52:19,630
because they're receiving hemodialysis, those
populations will have a hemoglobin less than 12.

615
00:52:19,630 --> 00:52:23,890
So, it is really important, I think, that
we can discern differences across disease

616
00:52:23,890 --> 00:52:26,510
groupings so that we identify these patients.

617
00:52:26,510 --> 00:52:29,760
It creates greater homogeneity, especially
even if we were looking out from the trials

618
00:52:29,760 --> 00:52:35,170
and specifically in relation to treatment
modalities, so that we're treating patients

619
00:52:35,170 --> 00:52:41,790
who have cachexia and can have specific treatment
modalities depending on their rates of the

620
00:52:41,790 --> 00:52:44,400
characteristics or rates of inflammation,
for example.

621
00:52:44,400 --> 00:52:49,369
So, yes, I do think it's really important
that we continue to move forward with disease-specific

622
00:52:49,369 --> 00:52:50,369
definitions.

623
00:52:50,369 --> 00:52:54,380
DR. DAVID SERES: Alright. Dr. Platek, you want to try again?

624
00:52:54,380 --> 00:52:56,890
DR. MARY E. PLATEK: Yeah, I think I'm OK, right?

625
00:52:56,890 --> 00:52:57,890
DR. DAVID SERES: Yes.

626
00:52:57,890 --> 00:52:59,200
DR. MARY E. PLATEK: Don't ask me what's going
on.

627
00:52:59,200 --> 00:53:04,130
It was like I was on Mars, but I was on Earth.

628
00:53:04,130 --> 00:53:05,130
In any case...

629
00:53:05,130 --> 00:53:08,080
DR. DAVID SERES: Why don't you address that question
and then go back to the previous.

630
00:53:08,080 --> 00:53:12,200
DR. MARY E. PLATEK: Yeah, and I'll probably have
to quickly.

631
00:53:12,200 --> 00:53:18,390
So, I think, so here's the deal, I mean, I've
been looking at this area forever.

632
00:53:18,390 --> 00:53:27,150
I've done a deep dive like a scoping review,
nothing published, looking at what are really

633
00:53:27,150 --> 00:53:35,420
the differences between disease-related cachexia
or even disease-related malnutrition.

634
00:53:35,420 --> 00:53:44,411
And we haven't moved forward and in the papers
that I've reviewed with these reports, it's

635
00:53:44,411 --> 00:53:45,869
a wasting syndrome.

636
00:53:45,869 --> 00:53:51,660
So, I'm not saying and I completely get the
differences with renal disease versus liver

637
00:53:51,660 --> 00:53:57,750
disease because we're talking about different
organs, in some cases, some organ systems

638
00:53:57,750 --> 00:54:00,000
are working, in other cases they aren't.

639
00:54:00,000 --> 00:54:05,220
So indeed, the intervention has to be specific.

640
00:54:05,220 --> 00:54:15,069
But to identify could we not consider a global
definition for cachexia like we are considering

641
00:54:15,069 --> 00:54:16,810
for malnutrition?

642
00:54:16,810 --> 00:54:22,460
And that whole idea of where cachexia
assists with malnutrition, where malnutrition

643
00:54:22,460 --> 00:54:25,869
assits with cachexia, that's another discussion.

644
00:54:25,869 --> 00:54:35,900
But to move forward in identification, could
we not do that with complete respect that

645
00:54:35,900 --> 00:54:42,049
there could be some nuances between diseases,
certainly in the intervention?

646
00:54:42,049 --> 00:54:50,250
But if so, in that respect, I'd have to say
that I would like to see a global move towards

647
00:54:50,250 --> 00:55:00,099
identifying cachexia because, you know, the
papers we reviewed with the ASCO committee,

648
00:55:00,099 --> 00:55:07,270
there wasn't a lot to glean from those as
far as information for moving forward.

649
00:55:07,270 --> 00:55:14,510
DR. DAVID SERES: So, it sounds like you would like a
universal sort of pathway to a syndrome that

650
00:55:14,510 --> 00:55:16,490
may have other inputs from other directions.

651
00:55:16,490 --> 00:55:18,130
DR. MARY E. PLATEK: Yeah.

652
00:55:18,130 --> 00:55:23,140
DR. DAVID SERES:  And I think that universal pathway will have
something to do with systemic inflammation,

653
00:55:23,140 --> 00:55:25,119
if I'd hazard a guess.

654
00:55:25,119 --> 00:55:26,119
Yeah.

655
00:55:26,119 --> 00:55:31,880
So, the question I had asked earlier, which
sort of ties into that, which is there any

656
00:55:31,880 --> 00:55:36,980
understanding of cancer type and its impact
on whether or not malnutrition develops?

657
00:55:36,980 --> 00:55:42,620
And specifically, I said that in inflammatory
cancers there's probably a...

658
00:55:42,620 --> 00:55:52,099
Oh, I got distracted, I lost my train of thought.

659
00:55:52,099 --> 00:55:56,500
Anyway, so there's probably a difference between
inflammatory and non-inflammatory cancers

660
00:55:56,500 --> 00:56:01,400
in terms of whether or not they develop cachexia
in the first place, but that there's certainly

661
00:56:01,400 --> 00:56:07,270
benefit for long survivors who have non-inflammatory
cancers from being nourished.

662
00:56:07,270 --> 00:56:09,049
At least that's what physiology would teach
us.

663
00:56:09,049 --> 00:56:10,049
Anyway, go on.

664
00:56:10,049 --> 00:56:11,049
I'm sorry.

665
00:56:11,049 --> 00:56:12,049
DR. MARY E. PLATEK: Yes.

666
00:56:12,049 --> 00:56:13,049
And I completely agree with that.

667
00:56:13,049 --> 00:56:18,831
And I think the best that we can say today,
because definitions were that were used in

668
00:56:18,831 --> 00:56:29,150
the papers that we reviewed were either vague
or different, that those with more an inflammatory

669
00:56:29,150 --> 00:56:35,190
component, they were the how we identified
cachexia in those papers, you know, there

670
00:56:35,190 --> 00:56:39,710
were certain cancers that had higher prevalence
of cachexia.

671
00:56:39,710 --> 00:56:45,560
So, there weren't many papers, for example,
for breast cancer survivors.

672
00:56:45,560 --> 00:56:51,849
But, you know, I'm going to stop myself there
as well because you can look at these differences

673
00:56:51,849 --> 00:56:58,209
in cancer types and you can think of the physiology,
but then you have to think of the stage and

674
00:56:58,209 --> 00:57:06,740
the treatment, because the treatment will
also change what we see in a patient, what the presentation is.

675
00:57:06,740 --> 00:57:10,970
DR. DAVID SERES: OK, great. Thank you.

676
00:57:10,970 --> 00:57:18,940
Dr. DiMaria-Ghalili, you talked a lot about
doing nutrition screening and the importance

677
00:57:18,940 --> 00:57:26,030
of doing so in the elderly, given the prevalence
and the fact and sort of the under identification.

678
00:57:26,030 --> 00:57:33,060
I'm wondering if there's been any data to
assert that the screening process and the

679
00:57:33,060 --> 00:57:40,240
assessment process then alters outcomes when
interventions are applied based on them.

680
00:57:40,240 --> 00:57:45,440
One of the themes of yesterday's talk was
that a lot of the assessment tools used in

681
00:57:45,440 --> 00:57:51,079
the hospital in particular, to determine nutrition
risk don't predict who's going to respond to

682
00:57:51,079 --> 00:57:52,559
nourishment.

683
00:57:52,559 --> 00:58:00,640
But I also imagine that in these populations
a multidisciplinary approach goes beyond nutrition.

684
00:58:00,640 --> 00:58:02,539
Anyway, your comments.

685
00:58:02,539 --> 00:58:08,109
DR. ROSE DIMARIA-GHALILI: Well, I think it's really
important to think about nutrition screening

686
00:58:08,109 --> 00:58:15,079
in older adults using age appropriate tools,
number one, because there are a lot of risk

687
00:58:15,079 --> 00:58:21,740
factors that could be targeted by not only
nutritional interventions, but social interventions.

688
00:58:21,740 --> 00:58:30,770
Like do people, you know, are we giving them
the services that they need to age in place

689
00:58:30,770 --> 00:58:31,770
appropriately?

690
00:58:31,770 --> 00:58:35,849
And that has to be part of our intervention
criteria when we're getting ready to move

691
00:58:35,849 --> 00:58:42,250
people from the hospital to the home, and
also when primary care practitioners are actually

692
00:58:42,250 --> 00:58:44,970
doing their assessment on older adults.

693
00:58:44,970 --> 00:58:49,280
So, it's just not the nutritional component
but also the social component as well.

694
00:58:49,280 --> 00:58:57,700
So, I think for us, in order to really target
outcomes, we need to make sure that the interventions

695
00:58:57,700 --> 00:59:02,160
are appropriate for the age group, number
one.

696
00:59:02,160 --> 00:59:03,420
DR. DAVID SERES: OK.

697
00:59:03,420 --> 00:59:05,329
A lot more to come.

698
00:59:05,329 --> 00:59:12,260
And there is a question that I'll ask you
too. I don't know if you're in the Moonshot

699
00:59:12,260 --> 00:59:17,510
discussion, but if you could look at Charlotte's
questions, you want know which, many studies

700
00:59:17,510 --> 00:59:19,049
were would you would pick?

701
00:59:19,049 --> 00:59:23,210
And if you could let us know, we'll make sure
it represented that in that discussion.

702
00:59:23,210 --> 00:59:28,240
DR. ROSE ANN DIMARIA-GHALILI: Well...well just to dovetail on what
everyone else just commented on, I think that

703
00:59:28,240 --> 00:59:34,410
the critical piece, especially for aging,
is that these tissue loss syndromes are going to

704
00:59:34,410 --> 00:59:35,610
occur simultaneously.

705
00:59:35,610 --> 00:59:41,119
So, we need to be able to differentiate and
figure out how to develop the best

706
00:59:41,119 --> 00:59:44,440
multimodal interventions in this population.

707
00:59:44,440 --> 00:59:45,680
DR. DAVID SERES: Yeah.

708
00:59:45,680 --> 00:59:51,890
And I would hazard a guess that, you know,
as we understand the longer term consequences

709
00:59:51,890 --> 01:00:00,260
of hospital illness is now termed frailty,
we're going to find out that frailty isn't too

710
01:00:00,260 --> 01:00:06,069
different from cachexia and from malnutrition,
as we've defined each of those separately,

711
01:00:06,069 --> 01:00:08,280
and that they all need multimodal intervention.

712
01:00:08,280 --> 01:00:14,380
Dr. Earthman, you had a number of very specific
questions, and let me try and summarize them

713
01:00:14,380 --> 01:00:16,430
quickly:

714
01:00:16,430 --> 01:00:18,020
Why didn't you talk about DEXA?

715
01:00:18,020 --> 01:00:20,020
DR. CARRIE EARTHMAN: OK.

716
01:00:20,020 --> 01:00:26,799
Well, I didn't talk about DEXA because for
clinicians, you know, most of us are looking

717
01:00:26,799 --> 01:00:33,130
at bedside techniques, you know, in terms
of the ease of use and access and that kind

718
01:00:33,130 --> 01:00:34,130
of thing.

719
01:00:34,130 --> 01:00:38,849
So, globally, you know, a lot of clinician
researchers and, you know, in their research

720
01:00:38,849 --> 01:00:43,619
studies, but also just in bedside assessment,
you know, we're talking about using techniques

721
01:00:43,619 --> 01:00:49,660
like bioimpedance, the most commonly used
is by far and away single frequency BIA.

722
01:00:49,660 --> 01:00:53,460
But ultrasound is on the rise and people are
also thinking about using CT.

723
01:00:53,460 --> 01:00:58,670
So, yeah, DEXA, if you have access to DEXA,
I would consider it, you know, one of our

724
01:00:58,670 --> 01:00:59,670
reference standards.

725
01:00:59,670 --> 01:01:04,799
And if we can get DEXA in our studies, where
we're looking at bedside techniques, that'd

726
01:01:04,799 --> 01:01:05,920
be great, right?

727
01:01:05,920 --> 01:01:12,400
So, it's a, you know, I agree DEXA is very
good data, but it's not available for many

728
01:01:12,400 --> 01:01:14,940
clinicians, you know?

729
01:01:14,940 --> 01:01:18,569
DR. DAVID SERES: We have like a research center that's
devoted, that happens to have one...

730
01:01:18,569 --> 01:01:20,569
DR. CARRIE EARTHMAN: Yeah.

731
01:01:20,569 --> 01:01:25,310
DR. DAVID SERES: The University of Texas at Austin,
a colleague of mine just told me they have

732
01:01:25,310 --> 01:01:27,490
one and they're very excited to be using it.

733
01:01:27,490 --> 01:01:29,490
DR. CARRIE EARTHMAN: Yeah.

734
01:01:29,490 --> 01:01:32,240
And like, you know, some places where, you
know, they've got active, you know, body composition

735
01:01:32,240 --> 01:01:37,270
assessment as kind of standard in their protocols,
then they might get that.

736
01:01:37,270 --> 01:01:41,839
But for many people, it's not really something
that is easily achievable.

737
01:01:41,839 --> 01:01:49,670
DR. DAVID SERES: So, there were several questions that
boiled down to what are the pros and cons

738
01:01:49,670 --> 01:01:50,670
of each method.

739
01:01:50,670 --> 01:01:56,690
You know, I know that there are issues with
BIA and fluid shifts and so forth, and I don't

740
01:01:56,690 --> 01:02:03,110
know that you can really give a full course
on this in about 30 seconds, but give it a try.

741
01:02:03,110 --> 01:02:11,000
DR. CARRIE EARTHMAN: Like asking to do a 10 minute talk
on three techniques, it was too much, I realize. Yeah.

742
01:02:11,000 --> 01:02:15,410
So, I think the thing is there is no one perfect
method, obviously and part of it is what people

743
01:02:15,410 --> 01:02:16,960
have access to.

744
01:02:16,960 --> 01:02:22,809
So, what I always try to just have people
understand is that every method has limitations

745
01:02:22,809 --> 01:02:26,040
that you just need to be aware of.

746
01:02:26,040 --> 01:02:30,990
There are bioimpedance techniques just to
start with, with that by impedance spectroscopy

747
01:02:30,990 --> 01:02:38,569
devices that are multi-spectral, you know,
offer more than single-frequency BIA in terms

748
01:02:38,569 --> 01:02:45,579
of differentiating fluid compartments and
kind of accounting for some of the limitations

749
01:02:45,579 --> 01:02:51,910
or challenges that are presented when you
use a really simple linear regression derived

750
01:02:51,910 --> 01:02:56,020
equation that you would apply with a single
frequency measure, for example.

751
01:02:56,020 --> 01:03:01,859
So, there are nuances and bioimpedance has
come a long way bioimpedance spectroscopy

752
01:03:01,859 --> 01:03:04,670
being used quite a lot in dialysis patients.

753
01:03:04,670 --> 01:03:08,559
So, I think that's something to just keep
in mind.

754
01:03:08,559 --> 01:03:11,220
Ultrasound is wonderful in many ways.

755
01:03:11,220 --> 01:03:17,440
It's so prevalent, you know, ubiquitous, the
devices are around, people can learn how to

756
01:03:17,440 --> 01:03:18,440
do them.

757
01:03:18,440 --> 01:03:23,700
The difficulties with any of these that I'm
hoping when we talk about Moonshot studies,

758
01:03:23,700 --> 01:03:32,059
that the ideal is to understand your technician
who's taking these measures, the precision

759
01:03:32,059 --> 01:03:37,240
of your measurements, so that you can understand
whether you are precise enough to actually

760
01:03:37,240 --> 01:03:42,000
detect changes and to know what that percent
change, minimal detectable change is.

761
01:03:42,000 --> 01:03:44,020
And that's a huge challenge.

762
01:03:44,020 --> 01:03:47,880
All of the clinician researchers I talked
to around the world doing these types of studies,

763
01:03:47,880 --> 01:03:53,170
it's really challenging to do multiple measures,
you know, in a sick population, especially

764
01:03:53,170 --> 01:03:55,839
if you're in ICU or hospital patients.

765
01:03:55,839 --> 01:04:00,789
But that would be an ideal to have if we can
understand, you know, what our repeatability

766
01:04:00,789 --> 01:04:03,599
and the precision of our measures are.

767
01:04:03,599 --> 01:04:05,520
I'll leave it at that.

768
01:04:05,520 --> 01:04:07,589
I'm sure I didn't fully answer that question.

769
01:04:07,589 --> 01:04:15,799
DR. DAVID SERES: Well, it's an entire semester course
for anybody who's really devoted to measuring

770
01:04:15,799 --> 01:04:17,069
body composition.

771
01:04:17,069 --> 01:04:22,460
I mean, there are all sorts of other techniques,
total body potassium, underwater weighing,

772
01:04:22,460 --> 01:04:28,380
you know, there's an entire literature for
the person who asked the question.

773
01:04:28,380 --> 01:04:33,230
And it's a fascinating one; the history of
it is really quite interesting.

774
01:04:33,230 --> 01:04:41,559
I will also say that coming up in a subsequent
session, there are going to be discussions

775
01:04:41,559 --> 01:04:48,539
of using biochemical markers, including D3-creatinine.

776
01:04:48,539 --> 01:04:57,560
There's a wonderful validation of that as
a way of looking at muscle mass, it correlates

777
01:04:57,560 --> 01:05:01,029
with MRI and so forth and Bill Evans is going to
talk about that.

778
01:05:01,029 --> 01:05:04,010
Thank you, Christopher, for reminding me.

779
01:05:04,010 --> 01:05:10,299
Anyway, so for the audience, please stay tuned
and tune in to those.

780
01:05:10,299 --> 01:05:18,829
So, you actually raise a question or a good
segway into a question that I'll ask all of

781
01:05:18,829 --> 01:05:21,130
you to think about and answer.

782
01:05:21,130 --> 01:05:29,319
And that is, you know, we've been pretty clear
that in our current approach to malnutrition,

783
01:05:29,319 --> 01:05:35,020
we're not very effective at treating it and
I would hazard to guess that that's in part

784
01:05:35,020 --> 01:05:41,829
because of the, you know, in the hospital,
the patients who have malnutrition and are

785
01:05:41,829 --> 01:05:45,809
refractory or those who are highly inflamed
and they're just not getting medically better

786
01:05:45,809 --> 01:05:54,730
and we don't really know what the long term
consequences of hospital starvation is.

787
01:05:54,730 --> 01:06:02,560
But setting that aside, do you think that
perhaps there's a role to predicting whatever

788
01:06:02,560 --> 01:06:05,329
this syndrome is, malnutrition?

789
01:06:05,329 --> 01:06:14,170
Picking it up really early and seeing if there's
early interventions, nutritional interventions

790
01:06:14,170 --> 01:06:21,000
or otherwise that could be applied earlier
to prevent it from getting to that point where

791
01:06:21,000 --> 01:06:22,789
it really is refractory?

792
01:06:22,789 --> 01:06:23,789
Any thoughts about that?

793
01:06:23,789 --> 01:06:28,339
Is that in any work that you're aware of?

794
01:06:28,339 --> 01:06:31,440
DR. MARY E. PLATEK: In a couple of comments.

795
01:06:31,440 --> 01:06:42,050
I think we know from, you know, most of the
literature is not from randomized controlled

796
01:06:42,050 --> 01:06:54,240
trials, but some from very good observational
data we know that if you have a certain cancer

797
01:06:54,240 --> 01:07:02,010
type, for example, GI, head, neck, lung, OK?

798
01:07:02,010 --> 01:07:10,740
That those are associated with poor nutritional
status and those people, if not intervened,

799
01:07:10,740 --> 01:07:11,950
will do poorly.

800
01:07:11,950 --> 01:07:18,579
We also know any cancer type that has multi
modality treatment, right?

801
01:07:18,579 --> 01:07:24,799
So, you could pick almost anything and let's
say you have an induction chemo and you have

802
01:07:24,799 --> 01:07:31,829
a surgery and then you have a radiation treatment,
you will do poorly and your nutritional status

803
01:07:31,829 --> 01:07:34,390
will decline.

804
01:07:34,390 --> 01:07:44,130
Also, if you add in older age and certain
lifestyle behaviors before, those are usually

805
01:07:44,130 --> 01:07:45,130
associated.

806
01:07:45,130 --> 01:07:49,619
So, based on associations, there are some
points where we could predict that.

807
01:07:49,619 --> 01:07:57,770
And since we've decided on certain of our
surgeries, for example, oh my goodness.

808
01:07:57,770 --> 01:08:04,390
So, now I'm going to forget what I was just
reading last night, bladder cancer, excuse me.

809
01:08:04,390 --> 01:08:10,400
So, if you have invasive bladder cancer, that
population just from reading, so off the top

810
01:08:10,400 --> 01:08:12,150
of my head looks older.

811
01:08:12,150 --> 01:08:19,890
I did do cohort observational where it did
malnutrition risk, their malnutrition risk

812
01:08:19,890 --> 01:08:29,440
was pretty high based on the NRS 2002
and those people who were targeted at high

813
01:08:29,440 --> 01:08:34,470
nutritional risk did, you know, have more
complications surgically just based out of

814
01:08:34,470 --> 01:08:36,319
the small study that I had done.

815
01:08:36,319 --> 01:08:42,359
So, we do have points where we could pick
right people and we could intervene earlier.

816
01:08:42,359 --> 01:08:45,140
We are doing some of that with surgical patients,
right?

817
01:08:45,140 --> 01:08:50,560
We're getting in there and we're doing supplementation
before and we have some protocols for that,

818
01:08:50,560 --> 01:08:54,270
getting them on a treadmill or whatever the
case may be before.

819
01:08:54,270 --> 01:09:01,279
So, I think there are ways to predict and
time will tell the difference what needs to

820
01:09:01,279 --> 01:09:05,219
be changed in models that we can actually
take a look at.

821
01:09:05,219 --> 01:09:11,210
DR. DAVID SERES: In other words, that would be a good
target for research.

822
01:09:11,210 --> 01:09:12,259
Yeah.

823
01:09:12,259 --> 01:09:16,569
And that's really the focus of this conference.

824
01:09:16,569 --> 01:09:25,150
A quick comment and, you know, the terminology
that, that we keep throwing around here is

825
01:09:25,150 --> 01:09:31,449
intentionally, as far as I'm concerned, confusing
because my hope is that we come to a better

826
01:09:31,449 --> 01:09:36,130
consensus about this in terms of coming up,
you know, what is cachexia?

827
01:09:36,130 --> 01:09:37,290
What is malnutrition?

828
01:09:37,290 --> 01:09:40,140
What is malnourishment.

829
01:09:40,140 --> 01:09:45,150
And I'll comment that several of our speakers
use the terms interchangeably.

830
01:09:45,150 --> 01:09:51,900
And I'd urge everyone to think about when
they describe patients as being malnourished,

831
01:09:51,900 --> 01:09:55,330
do they mean it?

832
01:09:55,330 --> 01:09:58,370
And somebody help me come up with a different term
for malnutrition.

833
01:09:58,370 --> 01:10:04,170
As I've said before, when when said Gordon Jensen
first presented ASPEN AND guidelines at

834
01:10:04,170 --> 01:10:06,260
ASPEN...hundreds of people in the room, I raised my
hand.

835
01:10:06,260 --> 01:10:08,530
hand and said, "Hey, Gordon, can we call it
something else?

836
01:10:08,530 --> 01:10:10,719
Can we call it Matilda?

837
01:10:10,719 --> 01:10:12,739
Anything other than malnutrition?

838
01:10:12,739 --> 01:10:16,730
Because people who have malnutrition may or
may not be malnourished."

839
01:10:16,730 --> 01:10:23,719
And that didn't go over very well, and I've
not been very popular ever since.

840
01:10:23,719 --> 01:10:24,719
Alright.

841
01:10:24,719 --> 01:10:29,690
Dr. Reid, can you just quickly go over what
is in the multi-modal intervention that you

842
01:10:29,690 --> 01:10:33,850
are applying and maybe a little reason?

843
01:10:33,850 --> 01:10:36,310
DR. JOANNA REID: Yeah.

844
01:10:36,310 --> 01:10:41,530
So...sorry I've got a minute.

845
01:10:41,530 --> 01:10:46,541
It's based around the ideology of cachexia
and there's three core components to it.

846
01:10:46,541 --> 01:10:52,000
So, one is resistance training to try and
help sustain or rebuild some of the muscle

847
01:10:52,000 --> 01:10:53,000
mass.

848
01:10:53,000 --> 01:10:54,880
And the third is an anti-inflammatory agent.

849
01:10:54,880 --> 01:10:56,960
So, we're using fatty fish oils in relation to that.

850
01:10:56,960 --> 01:11:01,330
And the third component then is dietary counseling.

851
01:11:01,330 --> 01:11:07,070
And one of the things that we do, particularly
with the hemodialysis population, is that

852
01:11:07,070 --> 01:11:11,850
they are multimorbid and quite frequently
they're seeing a renal dietician, a cardiac

853
01:11:11,850 --> 01:11:14,580
dietician and several other disease specific
definitions.

854
01:11:14,580 --> 01:11:18,780
And there's a lot of confusion around what
their diet is.

855
01:11:18,780 --> 01:11:22,960
So, what we want to provide is a global assessment
and a tailored nutritional plan, focusing

856
01:11:22,960 --> 01:11:25,071
particularly on protein and protein intake.

857
01:11:25,071 --> 01:11:31,830
And alongside all of that then are these psychological
components and psychological support that

858
01:11:31,830 --> 01:11:37,370
we really want to give to this particular
patient cohort so that they will not only

859
01:11:37,370 --> 01:11:40,489
take part within the study, but also remain
within the study.

860
01:11:40,489 --> 01:11:45,480
And we've seen great benefit of doing that
in our earlier study, which is the longitudinal

861
01:11:45,480 --> 01:11:47,790
study looking at cachexia.

862
01:11:47,790 --> 01:11:48,940
DR. DAVID SERES: Excellent.

863
01:11:48,940 --> 01:11:49,940
Alright.

864
01:11:49,940 --> 01:11:51,989
Listen, thank you all very much.

865
01:11:51,989 --> 01:11:54,421
I'm afraid we're out of time.

866
01:11:54,421 --> 01:12:01,219
I'd love to spend the entire day talking with
you, but unfortunately, that can't happen.

867
01:12:01,219 --> 01:12:11,449
We're going to take a little break right now
until, let's see 1, Oops, sorry, I opened

868
01:12:11,449 --> 01:12:14,780
the wrong thing.

869
01:12:14,780 --> 01:12:21,739
The break is until 1:25 and we'll see you
back then.

870
01:12:21,739 --> 01:12:24,380
Thank you all.

871
01:12:24,380 --> 01:12:33,080
DR. GAIL CRESCI: Hello and welcome to Session
three on Measuring Malnutrition Methods and

872
01:12:33,080 --> 01:12:34,080
Tools.

873
01:12:34,080 --> 01:12:38,360
My name is Gail Cresci and I'm an associate
professor in the Cleveland Clinic, Lerner

874
01:12:38,360 --> 01:12:43,810
College of Medicine of Case Western Reserve
University, and full staff in the Department

875
01:12:43,810 --> 01:12:48,820
of Pediatric Gastroenterology and Inflammation
and Immunity at the Cleveland Clinic in Cleveland,

876
01:12:48,820 --> 01:12:49,820
Ohio.

877
01:12:49,820 --> 01:12:54,900
I am also the immediate past president of
the American Society for Parenteral and Enteral

878
01:12:54,900 --> 01:12:56,440
Nutrition.

879
01:12:56,440 --> 01:12:59,710
I will be your moderator for this session.

880
01:12:59,710 --> 01:13:06,270
We have a phenomenal panel of experts presenting
on this topic today. For detailed information

881
01:13:06,270 --> 01:13:08,410
regarding their impressive backgrounds,

882
01:13:08,410 --> 01:13:15,190
please refer to the speaker tab that you can
find on the left column and this page.

883
01:13:15,190 --> 01:13:17,710
And it's the third icon down.

884
01:13:17,710 --> 01:13:24,600
Or you can go to the main page for this site
and you will also find it under the speakers tab.

885
01:13:24,600 --> 01:13:27,090
This session is broken into two parts.

886
01:13:27,090 --> 01:13:33,120
In part one, we will hear about the strengths
and caveats of current biomarkers and tools

887
01:13:33,120 --> 01:13:35,460
used to assess malnutrition.

888
01:13:35,460 --> 01:13:42,199
Dr. David Evans will discuss visceral proteins
and Dr. Alison Steiber will present physical

889
01:13:42,199 --> 01:13:44,660
and composite measurements.

890
01:13:44,660 --> 01:13:50,860
The second part we will learn about emerging
biomarkers and tools for measuring malnutrition.

891
01:13:50,860 --> 01:13:57,000
Dr. William Evans will present on deuterium creatinine
dilution method for muscle composition.

892
01:13:57,000 --> 01:14:03,460
Dr. Tom Ziegler will provide an overview on
the use of metabolomics for potential utility

893
01:14:03,460 --> 01:14:05,730
in nutrition and metabolic support.

894
01:14:05,730 --> 01:14:11,710
Dr. Kenneth Christopher will follow with more
discussion on metabolomics in the clinical

895
01:14:11,710 --> 01:14:18,100
setting, Dr. Raed Dweik will discuss the use
of breath analysis of volatile organic compounds

896
01:14:18,100 --> 01:14:21,620
in clinical diseases, including malnutrition.

897
01:14:21,620 --> 01:14:27,250
Lastly, we will hear from Dr. John Alverdi
regarding the gut microbiome and malnutrition

898
01:14:27,250 --> 01:14:29,980
in critical illness.

899
01:14:29,980 --> 01:14:37,159
The presentations will be followed by a live
question and answer period with the speakers.

900
01:14:37,159 --> 01:14:42,520
During the session, please share your questions
for the presenters in the chat box.

901
01:14:42,520 --> 01:14:48,080
We will try to address as many questions as
we can during this session.

902
01:14:48,080 --> 01:14:52,470
So here we go.

903
01:14:52,470 --> 01:15:02,480
DR. DAVID EVANS: It's a privilege to be here speaking
with you today about albumin and prealbumin

904
01:15:02,480 --> 01:15:06,590
and their current role in practice.

905
01:15:06,590 --> 01:15:08,460
These are my disclosures.

906
01:15:08,460 --> 01:15:13,659
Certainly, albumin and prealbumin are often
misunderstood and misapplied.

907
01:15:13,659 --> 01:15:17,550
And when I'm making rounds at the hospital
and the residents will often told me that

908
01:15:17,550 --> 01:15:24,290
they sent some nutrition labs and they mean
of course albumin and prealbumin. And, you know

909
01:15:24,290 --> 01:15:29,520
this is an area that really challenges results
on a regular basis and our nutrition support

910
01:15:29,520 --> 01:15:35,190
team often gets a call that goes something like this;
Mr. Jones' Albumin or prealbumin is

911
01:15:35,190 --> 01:15:36,460
very low.

912
01:15:36,460 --> 01:15:42,840
Can we increase the prescribed, you know,
amino acids in the TPN or make some other

913
01:15:42,840 --> 01:15:48,420
intervention to try to improve the nutrition
support?

914
01:15:48,420 --> 01:15:54,050
So this was a challenge and ASPEN was very
well aware of this challenge and their malnutrition

915
01:15:54,050 --> 01:15:59,780
committee formed a group to develop a position
paper.

916
01:15:59,780 --> 01:16:05,949
And the key point of this position paper was
that albumin and prealbumin are not components

917
01:16:05,949 --> 01:16:11,630
of currently accepted definitions of malnutrition
and that they shouldn't be misapplied.

918
01:16:11,630 --> 01:16:21,390
I think the key perception or misperception out there is that
albumin and prealbumin would be proxy measures

919
01:16:21,390 --> 01:16:26,510
of total body protein or total muscle mass.

920
01:16:26,510 --> 01:16:34,120
And, you know, we needed to dispel this and
make it clear that even if total lean body

921
01:16:34,120 --> 01:16:39,620
mass is changing, but the serum albumin and prealbumin typically aren't.

922
01:16:39,620 --> 01:16:46,100
And so there are several kind of lines of
reasoning that supported this finding and recommendation.

923
01:16:46,100 --> 01:16:53,270
So first, albumin and prealbumin in healthy
patients, even when starving, typically do

924
01:16:53,270 --> 01:16:59,630
not decline until the patient's body mass
index was dropped down to 12 or the starvations

925
01:16:59,630 --> 01:17:02,929
are gone for six weeks or more.

926
01:17:02,929 --> 01:17:09,010
They do not decline in elderly malnourished
patients as well.

927
01:17:09,010 --> 01:17:17,290
Their levels do not really correlate with
dietary intake, and that's been shown in both

928
01:17:17,290 --> 01:17:24,659
inpatient and critical care settings and albumin
and prealbumin levels don't correlate with

929
01:17:24,659 --> 01:17:28,949
restrictive eating disorders such as anorexia
nervosa either.

930
01:17:28,949 --> 01:17:35,889
So really the average patient at home starving
themselves or whatever can't shift that level

931
01:17:35,889 --> 01:17:37,840
particularly.

932
01:17:37,840 --> 01:17:43,159
But what we do know is that serum concentrations
of albumin and prealbumin do decline in the

933
01:17:43,159 --> 01:17:45,030
presence of inflammation.

934
01:17:45,030 --> 01:17:47,940
And this is pretty well known and pretty well
understood.

935
01:17:47,940 --> 01:17:51,660
And it's really regardless of the underlying
nutritional status.

936
01:17:51,660 --> 01:17:55,680
So we typically refer to these as negative
acute phase reactants.

937
01:17:55,680 --> 01:18:06,250
And what happens is the liver reprioritizes
its protein synthesis and as a result of being

938
01:18:06,250 --> 01:18:14,330
stimulated by IL-6 and inflammatory cytokines
and the signals that inflammation is present.

939
01:18:14,330 --> 01:18:20,889
What happens is the liver shifts its production
away from albumin and prealbumin to C-reactive

940
01:18:20,889 --> 01:18:30,190
protein serum amyloid proteins, fibrinogen
mannose, lectin-binding proteins, and complement.

941
01:18:30,190 --> 01:18:38,949
And so as that shift occurs, certainly albumin
and prealbumin are going to go down.

942
01:18:38,949 --> 01:18:41,460
There's another process at play. In inflammation,

943
01:18:41,460 --> 01:18:49,320
there's increased capillary permeability and
albumin and prealbumin moved to the interstitial

944
01:18:49,320 --> 01:18:55,300
third space and albumin functions as an antioxidant
in that extracellular space.

945
01:18:55,300 --> 01:19:00,820
So, it really has kind of an almost evolutionary
purpose when it does that.

946
01:19:00,820 --> 01:19:07,170
So really, they must be recognized as inflammatory
markers associated with nutrition risk rather

947
01:19:07,170 --> 01:19:13,780
than in the context of a nutrition assessment
as being, you know, malnutrition per say.

948
01:19:13,780 --> 01:19:18,940
And so this was really one of the key points
of our position paper.

949
01:19:18,940 --> 01:19:23,480
And certainly, this makes sense in the setting
of, you know, what now have been around for

950
01:19:23,480 --> 01:19:30,810
about 10 years. The etiology-based malnutrition
diagnoses, where really, "Is inflammation present,

951
01:19:30,810 --> 01:19:38,290
yes or no?" lies at the heart of the decision
tree determining what that nutrition diagnosis is.

952
01:19:38,290 --> 01:19:43,310
And inflammation may limit the effectiveness
of nutrition interventions in the settings.

953
01:19:43,310 --> 01:19:49,020
So, we'll talk a lot about nutrition risk in this
talk.

954
01:19:49,020 --> 01:19:54,659
And, you know, I think there may not really
be a consensus definition around that.

955
01:19:54,659 --> 01:19:59,350
When I'm talking about nutrition risk, I'm
typically talking about a patient who is at

956
01:19:59,350 --> 01:20:05,600
risk for a poor outcome without the delivery
of adequate nutrition support.

957
01:20:05,600 --> 01:20:11,850
Certainly, nutritionally at risk has been
defined by kind of standardized diagnostic

958
01:20:11,850 --> 01:20:18,040
criteria, including, you know, one or more
of the following categories that I won't read

959
01:20:18,040 --> 01:20:22,440
off similar to a malnutrition diagnosis.

960
01:20:22,440 --> 01:20:27,420
But this idea of nutrition risk is powerful
and it takes several angles.

961
01:20:27,420 --> 01:20:32,960
One is, is that we know that albumin or prealbumin
on their own are powerful screening tools.

962
01:20:32,960 --> 01:20:39,040
Albumin in particular for surgical complications,
Going back to the 80s and 90s, this has been well

963
01:20:39,040 --> 01:20:40,580
examined.

964
01:20:40,580 --> 01:20:46,409
The VA preoperative risk assessment study
looked at 87,000 patients and concluded that

965
01:20:46,409 --> 01:20:53,000
preoperative albumin levels were the single
best predictor of overall operative risk.

966
01:20:53,000 --> 01:20:59,830
They looked at several high-risk operations
and really determined that a cut point of

967
01:20:59,830 --> 01:21:05,810
approximately 3.5 anything less than that
3.5 grams per deciliter was associated with

968
01:21:05,810 --> 01:21:08,690
increased postoperative mortality.

969
01:21:08,690 --> 01:21:15,500
And furthermore, there were also increases
in postoperative pneumonias and anastomotic

970
01:21:15,500 --> 01:21:19,940
leaks, abscesses, respiratory failure, and
then, you know, need increased utilization,

971
01:21:19,940 --> 01:21:24,980
such as the intensive care unit, the length
of stay in the hospital or the need and the

972
01:21:24,980 --> 01:21:29,390
use of postoperative parenteral nutrition.

973
01:21:29,390 --> 01:21:32,820
So clearly a screening tool like that was
very valuable.

974
01:21:32,820 --> 01:21:38,909
And in fact, albumin has been implemented
into in the NSQIP risk calculator, which is

975
01:21:38,909 --> 01:21:43,360
going to be one of our standardized surgical risk
tools.

976
01:21:43,360 --> 01:21:50,730
It's very widely accepted and the ASPEN guidelines
have really used albumin as one of the four

977
01:21:50,730 --> 01:21:58,500
key criteria, including also, you know, weight
loss, low BMI or an SGA of C, as you know,

978
01:21:58,500 --> 01:22:03,430
really one of the four reasons to stop and
pause and say, "You know, who is going to need

979
01:22:03,430 --> 01:22:10,110
preoperative enteral or parenteral support
in order to have a successful surgical outcome?"

980
01:22:10,110 --> 01:22:16,429
The concept of nutrition risk can be quite
quantitative, as in this example from the

981
01:22:16,429 --> 01:22:22,750
critical care setting where NUTRIC scores
are used to identify nutrition risk, and those

982
01:22:22,750 --> 01:22:29,950
patients with high NUTRIC scores are much
more sensitive to feeding and have a much

983
01:22:29,950 --> 01:22:36,659
higher survival when fed well versus underfed
compared to patients with low NUTRIC scores

984
01:22:36,659 --> 01:22:42,410
who have low nutrition risk and do not appear
to be as sensitive to feeding,

985
01:22:42,410 --> 01:22:49,850
whether it is underfeeding or full feeding.
Not just are outcomes often not as good in

986
01:22:49,850 --> 01:22:51,750
patients that are at high nutrition risk.

987
01:22:51,750 --> 01:22:56,770
But we see that even postoperatively they're
less likely to meet their energy targets,

988
01:22:56,770 --> 01:23:01,570
more likely to need nutrition support, more
likely to have a delayed return to solid food,

989
01:23:01,570 --> 01:23:06,960
less mobility, and a longer recovery of activities
of daily living.

990
01:23:06,960 --> 01:23:13,000
When providing nutrition support, we commonly
monitor albumin and prealbumin levels, but

991
01:23:13,000 --> 01:23:15,810
their role really remains undefined.

992
01:23:15,810 --> 01:23:22,199
When I see them normalize, I tend to assume
that this represents resolution of inflammation

993
01:23:22,199 --> 01:23:28,310
or reduction of the nutrition risk, a transition
from catabolism to anabolism, and probably

994
01:23:28,310 --> 01:23:33,000
in most patients, lower calorie and protein
requirements.

995
01:23:33,000 --> 01:23:38,530
We also know that with recovery, the albumin
goes up and the C-reactive protein goes down.

996
01:23:38,530 --> 01:23:45,139
We also know that extra feeding does not improve
prealbumin levels and in critically ill patients.

997
01:23:45,139 --> 01:23:51,790
Whether calories are just appropriately or
underdosed, the prealbumin does not change.

998
01:23:51,790 --> 01:23:59,100
This was the same with albumin in the EDEN
ARDS trial where trophic versus full

999
01:23:59,100 --> 01:24:04,040
feeding in ARDS for seven days did not result
in achange.

1000
01:24:04,040 --> 01:24:09,690
Albumin and prealbumin monitoring though
are still in the ASPEN guidance for Home PN

1001
01:24:09,690 --> 01:24:16,180
monitoring, and I believe that they can be
useful providing some insight into fluid status

1002
01:24:16,180 --> 01:24:20,880
inflammatory processes where the patient's
medical condition was directly quoted here.

1003
01:24:20,880 --> 01:24:27,780
Certainly, in my practice I think that I see
the transition from catabolism to anabolism

1004
01:24:27,780 --> 01:24:32,681
and the resolution of inflammation by looking
at the wound, looking at the patient, looking

1005
01:24:32,681 --> 01:24:34,580
at their functional status.

1006
01:24:34,580 --> 01:24:41,119
We see the wound,the fistula close the wound
granulate, the skin grafts successfully take

1007
01:24:41,119 --> 01:24:43,000
as in this patient example.

1008
01:24:43,000 --> 01:24:49,889
And in this example we see the necrosis debrided
away the wound granulates well, and we see

1009
01:24:49,889 --> 01:24:51,870
the inflammation resolving.

1010
01:24:51,870 --> 01:24:54,230
So thank you for your time.

1011
01:24:54,230 --> 01:24:56,750
DR. ALISON STEIBER: Good afternoon.

1012
01:24:56,750 --> 01:25:02,580
I am Dr. Allison Steiber, and today I will
be speaking briefly on composite measures

1013
01:25:02,580 --> 01:25:04,139
for the diagnosis of malnutrition.

1014
01:25:04,139 --> 01:25:09,139
I want to thank the NIH and the Office of
Nutrition Research for hosting this workshop

1015
01:25:09,139 --> 01:25:16,850
and for highlighting research and practice
in the area of hospital malnutrition.

1016
01:25:16,850 --> 01:25:21,580
Individual nutrition indicators vary in their
capacity to comprehensively assess nutrition

1017
01:25:21,580 --> 01:25:27,460
status and have been shown to predict different
outcomes, with no single indicator shown to

1018
01:25:27,460 --> 01:25:32,489
determine whether a person will respond or
not to a specific nutrition intervention.

1019
01:25:32,489 --> 01:25:39,410
In hospital patients nutrition status is not
only about alteration of an imbalance and

1020
01:25:39,410 --> 01:25:45,290
nutrient intake which might be modified by
abnormal absorption or utilization, but is

1021
01:25:45,290 --> 01:25:52,080
also influenced by disease, trauma, sepsis
and fever, which induce the impact of inflammation

1022
01:25:52,080 --> 01:25:55,040
and oxidative stress.

1023
01:25:55,040 --> 01:25:58,460
This figure shows the confounding influence
of inflammation.

1024
01:25:58,460 --> 01:26:05,040
If we use an ecological approach to understanding
nutrition, then macro and micronutrients,

1025
01:26:05,040 --> 01:26:09,690
fluid, and multiple other factors need to
be taken into consideration when conducting

1026
01:26:09,690 --> 01:26:11,650
a nutrition assessment.

1027
01:26:11,650 --> 01:26:16,100
Currently, none of the validated composite
measures do this comprehensively.

1028
01:26:16,100 --> 01:26:23,960
It has been hypothesized that in the hospital
patient, a composite of nutrition indicators

1029
01:26:23,960 --> 01:26:27,139
is more likely to predict an outcome than
any single variable.

1030
01:26:27,139 --> 01:26:32,570
Currently in the field of nutrition there
are a number of composite tools used to screen

1031
01:26:32,570 --> 01:26:39,081
for risk of malnutrition and to diagnose malnutrition,
and examples of some of those are on the screen

1032
01:26:39,081 --> 01:26:40,220
today.

1033
01:26:40,220 --> 01:26:45,369
For example, we have the Subjective Global
Assessment that was first published by Dr.

1034
01:26:45,369 --> 01:26:48,420
Detsky et. al. in 1986 and in 1987.

1035
01:26:48,420 --> 01:26:54,739
We have the patient-generated subjective global
assessment and of course, the Academy ASPEN

1036
01:26:54,739 --> 01:26:57,440
indicators for malnutrition.

1037
01:26:57,440 --> 01:27:03,000
These tools have undergone varying degrees
of validation in different populations.

1038
01:27:03,000 --> 01:27:08,940
Some of those populations are the hospitalized
patients who are there for surgery, such as

1039
01:27:08,940 --> 01:27:10,830
studied by Detsky.

1040
01:27:10,830 --> 01:27:14,840
Some are the patients with chronic kidney
disease receiving hemodialysis, such as the

1041
01:27:14,840 --> 01:27:18,330
study that we did a number of years ago.

1042
01:27:18,330 --> 01:27:20,212
And there are studies with patients with different
types of cancer.

1043
01:27:20,212 --> 01:27:28,639
And this systematic review and meta-analysis
is just an example of examining those studies.

1044
01:27:28,639 --> 01:27:33,280
Another example of a composite diagnostic
tool is the nutrition-focused physical exam.

1045
01:27:33,280 --> 01:27:39,060
It is a comprehensive exam with a goal to
assess the patient from head to toe for different

1046
01:27:39,060 --> 01:27:45,520
areas of subcutaneous fat loss or muscle wasting,
in addition to assessing for signs and symptoms

1047
01:27:45,520 --> 01:27:47,290
of micronutrient deficiencies.

1048
01:27:47,290 --> 01:27:55,450
They also look at fluid accumulation or hydration
status, functional status utilizing the Handgrip

1049
01:27:55,450 --> 01:27:56,909
Dynamometer.

1050
01:27:56,909 --> 01:28:03,659
Unfortunately, this method has yet to be validated.

1051
01:28:03,659 --> 01:28:10,389
In 2012, White et. al. published a paper describing
a method for diagnosing malnutrition different

1052
01:28:10,389 --> 01:28:12,750
than the methods that I previously showed
you.

1053
01:28:12,750 --> 01:28:18,330
This method focuses on inflammation as an
ideology and is context specific.

1054
01:28:18,330 --> 01:28:25,980
The tool was developed using a consensus process,
and thus we needed to validate it.

1055
01:28:25,980 --> 01:28:31,159
So the Academy of Nutrition Dietetics Research
Team secured funding from Abbott Nutrition

1056
01:28:31,159 --> 01:28:35,502
to conduct a feasibility study that would
test methods for validating the malnutrition

1057
01:28:35,502 --> 01:28:36,950
diagnostic tool.

1058
01:28:36,950 --> 01:28:43,570
The results of this pilot were published in
2016 and inform a larger study funded through

1059
01:28:43,570 --> 01:28:46,940
the Academy's Foundation.

1060
01:28:46,940 --> 01:28:54,119
The goal of this larger study was to examine
both the validity of the AAIM tool and staffing

1061
01:28:54,119 --> 01:28:56,170
requirements for hospital dieticians.

1062
01:28:56,170 --> 01:29:01,380
You heard some of that staffing data by Dr.
Hand earlier in the workshop.

1063
01:29:01,380 --> 01:29:07,250
The sample I will be discussing today is the
adult AAIM data and later in the early life

1064
01:29:07,250 --> 01:29:13,350
section, this workshop you will hear Dr. Beth Jimenez
discuss the pediatric data.

1065
01:29:13,350 --> 01:29:21,490
You can see in the reddish box that the original
adult AAIM sample size goal was 600 with a

1066
01:29:21,490 --> 01:29:24,530
1-to-1 ratio for malnutrition risk.

1067
01:29:24,530 --> 01:29:29,600
Eventually, we will examine the nutrition-focused
physical exam and other diagnostic tools in

1068
01:29:29,600 --> 01:29:31,760
comparison to the outcomes.

1069
01:29:31,760 --> 01:29:36,080
But for today, I am just showing data from
the original AAIM tool.

1070
01:29:36,080 --> 01:29:40,990
If you look at the green box for outcomes,
you can see that we have multiple levels of

1071
01:29:40,990 --> 01:29:41,990
outcomes.

1072
01:29:41,990 --> 01:29:47,159
We have the dietician-reported nutrition outcomes,
we have medical outcomes and the disease severity

1073
01:29:47,159 --> 01:29:54,230
indicators Charlson Comorbidity Index, and
the MS-DRG relative weight.

1074
01:29:54,230 --> 01:29:59,790
Using some of this data, we developed a 90-day
composite score which includes both ER

1075
01:29:59,790 --> 01:30:05,510
visits and admission within the 90-day period.

1076
01:30:05,510 --> 01:30:14,110
For the larger study we considered inflammation,
disease severity, ICU presence of stay, socio-demographics

1077
01:30:14,110 --> 01:30:16,920
and body size to be potential confounders.

1078
01:30:16,920 --> 01:30:24,620
And we use length of stay readmission and
ER visits as previously noted, as our outcomes.

1079
01:30:24,620 --> 01:30:31,320
This figure shows recruitment for the project,
but additionally, to the full study it focuses

1080
01:30:31,320 --> 01:30:32,630
on the AAIM subgroup.

1081
01:30:32,630 --> 01:30:36,469
And that's what I'll be showing you some data
from today.

1082
01:30:36,469 --> 01:30:42,389
To be noted is we have pending data from six
different sites for their 90-day outcomes.

1083
01:30:42,389 --> 01:30:49,280
Thus, I will show you data from 26 different
sites and 213 patients.

1084
01:30:49,280 --> 01:30:53,710
I would like to note that we think that this
is one of the first studies to look at malnutrition

1085
01:30:53,710 --> 01:30:59,659
diagnosis and include data from over 25 different
studies.

1086
01:30:59,659 --> 01:31:01,920
The patient characteristics are shown here.

1087
01:31:01,920 --> 01:31:07,950
I'm not going to walk through all the data due
to time, but I really wanted to show the types

1088
01:31:07,950 --> 01:31:09,550
of data that we collected.

1089
01:31:09,550 --> 01:31:14,739
This particular study collected huge amounts
of data both on the facility and on the individual

1090
01:31:14,739 --> 01:31:17,440
dietitian and of course, on the patient.

1091
01:31:17,440 --> 01:31:22,560
Of note is the median age of the patients
of 65 and a relatively equal distribution

1092
01:31:22,560 --> 01:31:26,440
by education level.

1093
01:31:26,440 --> 01:31:30,770
This is about the patient medical characteristics,
including nutrition.

1094
01:31:30,770 --> 01:31:35,210
You can see on the first line that we are
looking at malnutrition screening tool, which

1095
01:31:35,210 --> 01:31:41,340
is how they determined whether the person was
at risk or not for that 1-to-1 distribution.

1096
01:31:41,340 --> 01:31:49,250
Our median number was a two and for MST a
two indicates moderate risk, which is logical

1097
01:31:49,250 --> 01:31:54,370
because then when the dieticians use the AAIM
tool, you can see the distribution.

1098
01:31:54,370 --> 01:32:01,320
44% had no malnutrition, 26 had moderate and
30 had severe malnutrition.

1099
01:32:01,320 --> 01:32:07,940
As you can see, we also collected data and
a variety of other medical characteristics.

1100
01:32:07,940 --> 01:32:11,940
In the next couple of slides, I will show
the models that were developed to examine

1101
01:32:11,940 --> 01:32:20,040
predictive validity for the two primary outcomes
90-day composite score and length of stay.

1102
01:32:20,040 --> 01:32:26,690
This first model was developed using a multilevel
model, which included random effects for the

1103
01:32:26,690 --> 01:32:27,690
different sites.

1104
01:32:27,690 --> 01:32:31,010
These data are still preliminary but exciting.

1105
01:32:31,010 --> 01:32:38,300
The current data shows that there is an independent,
significantly higher incidence of the 90-day

1106
01:32:38,300 --> 01:32:45,480
composite outcome for individuals with severe
malnutrition as diagnosed with the AAIM tool.

1107
01:32:45,480 --> 01:32:50,889
It also shows that for individuals with a
higher Charlson Comorbidity Index, there's

1108
01:32:50,889 --> 01:32:59,870
an independent, significant association and
for women versus men and finally for Native

1109
01:32:59,870 --> 01:33:08,330
American and Alaskan natives and black individuals
when compared to white individuals.

1110
01:33:08,330 --> 01:33:16,699
For the outcome length of stay a multilevel
generalized linear model was developed and

1111
01:33:16,699 --> 01:33:20,409
assessed, which includes the random effects
of sites.

1112
01:33:20,409 --> 01:33:27,330
In this model, we have found independent significantly
longer length of stay for individuals with

1113
01:33:27,330 --> 01:33:35,080
moderate or severe malnutrition diagnosis
for individuals who are living with obesity

1114
01:33:35,080 --> 01:33:41,350
versus normal weight and for individuals with
a MS-DRG relative weight.

1115
01:33:41,350 --> 01:33:47,750
Well, both of these models for the 90 day
composite score and the length of stay are

1116
01:33:47,750 --> 01:33:54,730
exciting and seem to indicate that the diagnostic
tool AAIM has predictive validity for poor

1117
01:33:54,730 --> 01:33:57,070
outcomes in the hospital setting.

1118
01:33:57,070 --> 01:34:03,610
More data will be added to these models and
further analyses done to confirm these findings.

1119
01:34:03,610 --> 01:34:12,630
There are many opportunities for further research
to better understand how we can feasibly diagnose

1120
01:34:12,630 --> 01:34:16,320
malnutrition in both the hospital setting
and others.

1121
01:34:16,320 --> 01:34:21,739
First, we need to validate tools that are
commonly used, and as I indicated, nutrition-focused

1122
01:34:21,739 --> 01:34:25,429
physical exam is a commonly used tool which
has not been validated.

1123
01:34:25,429 --> 01:34:32,030
It is one of the few tools that also assesses
micronutrient deficiencies and thus even more

1124
01:34:32,030 --> 01:34:35,480
important, that tool has validation.

1125
01:34:35,480 --> 01:34:40,460
But even bigger than that, regardless of tool,
we need to understand does malnutrition as

1126
01:34:40,460 --> 01:34:44,890
diagnosed resolve with different nutrition
interventions?

1127
01:34:44,890 --> 01:34:51,250
Do all patients who are identified as malnourished
respond similarly to any specific intervention?

1128
01:34:51,250 --> 01:34:55,960
And what other factors need to be considered
when predicting response?

1129
01:34:55,960 --> 01:35:02,060
Is this tool valid, reliable, and feasible
in outpatient community and low-resource settings?

1130
01:35:02,060 --> 01:35:07,679
And finally, what is the implementability
of diagnosis with a composite measure, whether

1131
01:35:07,679 --> 01:35:12,720
ours another one, in all settings with
different levels of nutrition practitioners?

1132
01:35:12,720 --> 01:35:14,500
Thank you.

1133
01:35:14,500 --> 01:35:20,520
DR. WILLIAM EVANS: Thank you very much for allowing
me to speak at this important meeting.

1134
01:35:20,520 --> 01:35:26,440
Today, I'll be talking about a new method
to directly and accurately measure the amount

1135
01:35:26,440 --> 01:35:28,750
of skeletal muscle mass.

1136
01:35:28,750 --> 01:35:31,730
It's non-invasive and it's direct.

1137
01:35:31,730 --> 01:35:37,940
And the first thing that's important to say
is that the assessment of lean body mass is

1138
01:35:37,940 --> 01:35:43,150
not muscle mass, although we've used lean
body mass as a surrogate for muscle for many

1139
01:35:43,150 --> 01:35:44,150
years.

1140
01:35:44,150 --> 01:35:50,409
And that has provided, I think, inaccurate
information about the nature of changes in

1141
01:35:50,409 --> 01:35:55,110
muscle mass and its relationship to outcomes.

1142
01:35:55,110 --> 01:36:02,420
We use deuterated or stable isotope labeled
creatine as our tracer.

1143
01:36:02,420 --> 01:36:07,159
Important to say, first of all, that about
98% of all the creatine in your body is in

1144
01:36:07,159 --> 01:36:08,159
skeletal muscle.

1145
01:36:08,159 --> 01:36:13,020
And yet muscle has no capacity to synthesize
creatine.

1146
01:36:13,020 --> 01:36:15,920
It's made in the liver and the kidney.

1147
01:36:15,920 --> 01:36:21,639
It's transported against a huge concentration
gradient, and then it's turned over by the

1148
01:36:21,639 --> 01:36:28,140
conversion of creatine to creatinine which
is then rapidly lost in urine.

1149
01:36:28,140 --> 01:36:33,480
So in our method, we use a single oral tracer
dose of deuterated creatine.

1150
01:36:33,480 --> 01:36:38,770
In adults, it's about 30 to 60 milligrams.

1151
01:36:38,770 --> 01:36:43,280
It's absorbed, distributed, and then actively
transported into muscle.

1152
01:36:43,280 --> 01:36:47,239
So it's distributed to all skeletal muscles.

1153
01:36:47,239 --> 01:36:55,820
The conversion of creatinine to I'm sorry
of creatine to creatinine at the rate of about

1154
01:36:55,820 --> 01:37:04,060
1.7% allows us then to simply sample a urine,
a single spot urine, measure the enrichment

1155
01:37:04,060 --> 01:37:11,619
of creatinine, and then know what the intramyocellular
dilution or enrichment of creatine is and

1156
01:37:11,619 --> 01:37:12,850
calculate skeletal muscle mass.

1157
01:37:12,850 --> 01:37:14,170
The measurement is done by mass spec.

1158
01:37:14,170 --> 01:37:24,290
Important to note that creatine and creatine
phosphate is co-located with the contractile

1159
01:37:24,290 --> 01:37:25,679
component of muscle.

1160
01:37:25,679 --> 01:37:29,390
So we think that it's a measurement of functional
muscle mass.

1161
01:37:29,390 --> 01:37:35,460
It's undiluted by fibrotic tissue or fat.

1162
01:37:35,460 --> 01:37:41,989
Our initial validation study, we measured
the creatine dilution muscle mass against

1163
01:37:41,989 --> 01:37:43,760
whole-body MRI.

1164
01:37:43,760 --> 01:37:48,190
You can see we had young men, older men, older
women, and postmenopausal women.

1165
01:37:48,190 --> 01:37:53,690
And what you can see here is a pretty strong
relationship between these two measurements.

1166
01:37:53,690 --> 01:37:58,810
Importantly, following right along the line
of identity, indicating that they're measuring

1167
01:37:58,810 --> 01:38:03,260
something that's very, very similar.

1168
01:38:03,260 --> 01:38:10,350
We were fortunate to collaborate with Dr.
Peggy Cawthon, we wrote an NIH grant that

1169
01:38:10,350 --> 01:38:15,780
was funded so we could introduce the method
into the cohort, the MrOS cohort, which is

1170
01:38:15,780 --> 01:38:20,650
a cohort of older men who are now over the
age of 80.

1171
01:38:20,650 --> 01:38:28,969
We're able to obtain 1,322 usable samples
in this initial analysis, and I'll show you

1172
01:38:28,969 --> 01:38:30,869
some of those results.

1173
01:38:30,869 --> 01:38:37,020
The first thing to say is that when we look
at the relationship between total body muscle

1174
01:38:37,020 --> 01:38:42,960
mass, and total body lean mass by DXA, you
can see that it's only a moderate relationship,

1175
01:38:42,960 --> 01:38:48,110
and certainly does not fall along the line
of identity.

1176
01:38:48,110 --> 01:38:55,150
We see no relationship between muscle mass,
and DXA appendicular lean mass, which is used

1177
01:38:55,150 --> 01:39:01,020
frequently as perhaps, a better surrogate
measurement of muscle mass, we see no relationship

1178
01:39:01,020 --> 01:39:03,230
at all.

1179
01:39:03,230 --> 01:39:11,290
We can also see in this study where we superimpose
our measurement on DXA measurement and DXA

1180
01:39:11,290 --> 01:39:16,119
appendicular lean mass body composition in
all 1,300 men.

1181
01:39:16,119 --> 01:39:25,679
The muscle mass values are dark blue, they're
ranked from the most to the least over here,

1182
01:39:25,679 --> 01:39:32,410
and what you can see is that the dark blue + light
blue = lean body mass.

1183
01:39:32,410 --> 01:39:37,720
So, there is a tremendous amount of what we
call residual lean mass, non-muscle lean mass,

1184
01:39:37,720 --> 01:39:44,260
that's part of the measurement of DXA lean
mass. The yellow dots here are appendicular

1185
01:39:44,260 --> 01:39:45,260
lean mass.

1186
01:39:45,260 --> 01:39:48,619
Now, does it make a difference?

1187
01:39:48,619 --> 01:39:55,590
Well, in this study, we can see that our measurement
of time to complete chair stands strongly

1188
01:39:55,590 --> 01:40:01,639
related to how much muscle they'd have, with
no relationship with appendicular lean mass,

1189
01:40:01,639 --> 01:40:07,290
a strong relationship to time to complete
a 400-meter walk, a strong relationship with

1190
01:40:07,290 --> 01:40:14,550
a short physical performance battery, and
then a strong relationship with force production,

1191
01:40:14,550 --> 01:40:19,989
no relationship at all with appendicular lean
mass measured by DXA.

1192
01:40:19,989 --> 01:40:27,440
We looked at mortality, and you can see with
multivariate analysis, there was a pretty

1193
01:40:27,440 --> 01:40:36,909
strong relationship between the loss of muscle,
the amount of muscle, and risk of mortality,

1194
01:40:36,909 --> 01:40:44,400
with no significant relationship with lean
mass, or appendicular lean mass.

1195
01:40:44,400 --> 01:40:50,369
I'll show you some data that we have looking
at changes in muscle mass over time. In this

1196
01:40:50,369 --> 01:40:54,590
population we were able to get a sample of
40 older men.

1197
01:40:54,590 --> 01:41:03,570
We measured them about a year and a half apart,
their age was about 83 at the start of the

1198
01:41:03,570 --> 01:41:04,570
study.

1199
01:41:04,570 --> 01:41:09,300
We also measured whole body DXA, grip strength,
walking speed, and I'll show you some of those

1200
01:41:09,300 --> 01:41:10,300
results.

1201
01:41:10,300 --> 01:41:17,060
So, the first thing to say, over a year and
a half, there was no change in lean mass,

1202
01:41:17,060 --> 01:41:23,280
appendicular lean mass, or appendicular lean
mass divided by height, or weight, and yet there was

1203
01:41:23,280 --> 01:41:31,110
what we think is a substantial loss of muscle
mass measured by D3Cr, or muscle mass, as

1204
01:41:31,110 --> 01:41:33,130
a percentage of body weight.

1205
01:41:33,130 --> 01:41:37,999
Interestingly, there was no change in weight
over that period of time, so it appears that

1206
01:41:37,999 --> 01:41:43,520
the principal component of body composition
that was changing was muscle mass.

1207
01:41:43,520 --> 01:41:50,120
What you can see also is that there was a
significant loss of grip strength and a slowing

1208
01:41:50,120 --> 01:41:51,170
of walking speed.

1209
01:41:51,170 --> 01:41:57,210
And if you didn't have a measurement of muscle
mass, you only had lean mass, your conclusion

1210
01:41:57,210 --> 01:42:04,270
might be that the loss in function was not
due to any changes in mass, but only due to

1211
01:42:04,270 --> 01:42:10,489
some change in intrinsic, as unexplained,
quality of muscle.

1212
01:42:10,489 --> 01:42:21,690
Recently, I wrote a commentary in the Journal
of Parenteral Enteral Nutrition where I stated

1213
01:42:21,690 --> 01:42:25,590
my position that lean body mass should not
be used as a surrogate measurement of muscle

1214
01:42:25,590 --> 01:42:26,590
mass.

1215
01:42:26,590 --> 01:42:34,490
Lean body mass is highly responsive to changes
in water content, for example, that I think

1216
01:42:34,490 --> 01:42:38,790
can hide significant changes in muscle mass.

1217
01:42:38,790 --> 01:42:46,990
And our recent studies in randomized controlled
trials examining the effect of severe energy

1218
01:42:46,990 --> 01:42:54,280
restriction, we see that DXA and D3Cr showed
disparate results, and right now we think

1219
01:42:54,280 --> 01:43:04,190
that any changes in body water content, or
even fibrotic content, will show up as changes

1220
01:43:04,190 --> 01:43:07,160
in muscle mass, or functional muscle mass.

1221
01:43:07,160 --> 01:43:13,739
Skeletal muscle is a highly plastic tissue,
which changes rapidly due to diet, energy,

1222
01:43:13,739 --> 01:43:21,790
and protein restriction, or increased protein
and energy, and those that are already malnourished.

1223
01:43:21,790 --> 01:43:29,619
Inactivity, or immobilization, exercise, hypogonadism,
and inflammation, can all affect skeletal

1224
01:43:29,619 --> 01:43:31,560
muscle mass.

1225
01:43:31,560 --> 01:43:39,510
Importantly, this method is now being incorporated
into a number of longitudinal cohort studies.

1226
01:43:39,510 --> 01:43:47,050
As I said, we have incorporated this into
the Osteoporotic Fractures

1227
01:43:47,050 --> 01:43:49,030
in Men, the MrOS Study.

1228
01:43:49,030 --> 01:43:53,680
We were recently funded to incorporate this
method into the Women's Health Initiative,

1229
01:43:53,680 --> 01:44:00,010
the Life and Longevity After Cancer trial,
in which we have more than 6,000 participants.

1230
01:44:00,010 --> 01:44:06,300
The Tobago Longitudinal Aging Study in which
we'll be able to measure changes in Caribbean

1231
01:44:06,300 --> 01:44:11,880
Africans, the Study of Muscle Mobility, and
Aging, the Framingham Heart

1232
01:44:11,880 --> 01:44:17,510
Study just incorporated this method into that
study.

1233
01:44:17,510 --> 01:44:25,849
We have a new grant looking at components
of cellular senescence in muscle, and matching

1234
01:44:25,849 --> 01:44:28,480
it to changes in muscle mass.

1235
01:44:28,480 --> 01:44:34,860
We have a number of studies in patients with
cancer. We think that changes in muscle mass

1236
01:44:34,860 --> 01:44:39,250
may be a powerful predictor of disease progression.

1237
01:44:39,250 --> 01:44:45,840
We have now, data in women with breast, ovarian,
colorectal, and in patients with multiple

1238
01:44:45,840 --> 01:44:52,040
myeloma, we have a large study looking at
older cancer survivors.

1239
01:44:52,040 --> 01:45:00,190
We also have funded studies to look at longitudinal
changes in boys with Duchenne dystrophy, and

1240
01:45:00,190 --> 01:45:08,560
our funded data from the Bill and Melinda
Gates Foundation has allowed us to validate

1241
01:45:08,560 --> 01:45:09,610
this method in neonates, infants, and children.

1242
01:45:09,610 --> 01:45:15,230
We recently completed a study looking at muscle
mass in malnourished four-year-old children

1243
01:45:15,230 --> 01:45:16,230
in Bangladesh.

1244
01:45:16,230 --> 01:45:23,980
So, it's important to say that this method
is non-invasive, it's safe, requires only

1245
01:45:23,980 --> 01:45:29,909
a single spot fasting urine, and provides
a direct assessment of functional muscle mass.

1246
01:45:29,909 --> 01:45:30,909
Thank you very much.

1247
01:45:30,909 --> 01:45:35,060
DR. THOMAS R. ZIEGLER: Hello, I'd like to thank
the organizers so much for inviting me to

1248
01:45:35,060 --> 01:45:40,410
give this talk on nutritional metabolomics
and its potential utility in nutrition and

1249
01:45:40,410 --> 01:45:42,710
metabolic support today.

1250
01:45:42,710 --> 01:45:47,710
I'd like to first talk about research gaps
in malnutrition and catabolic states from

1251
01:45:47,710 --> 01:45:50,480
which metabolomics may be useful.

1252
01:45:50,480 --> 01:45:56,690
First of all, malnutrition is often difficult
to identify, especially in hospital and post-hospital

1253
01:45:56,690 --> 01:45:58,120
settings.

1254
01:45:58,120 --> 01:46:03,740
Further, determining micronutrient and protein-energy
status is often uncertain.

1255
01:46:03,740 --> 01:46:09,410
And optimal doses of protein, energy, fat,
and micronutrients in many clinical conditions

1256
01:46:09,410 --> 01:46:11,500
remain unclear.

1257
01:46:11,500 --> 01:46:17,790
Further, biomarkers for improving, or worsening,
nutritional status are needed.

1258
01:46:17,790 --> 01:46:23,310
And a better understanding of nutritional
pathophysiology is needed in many disease

1259
01:46:23,310 --> 01:46:24,660
states.

1260
01:46:24,660 --> 01:46:31,860
Now, metabolomics which is profiling small
molecules in biologic systems is useful to

1261
01:46:31,860 --> 01:46:35,520
explore nutrition-related pathophysiology.

1262
01:46:35,520 --> 01:46:41,420
It allows us to measure the core nutritional
metabolome, and the non-nutritive chemicals

1263
01:46:41,420 --> 01:46:44,200
in diet, as shown here.

1264
01:46:44,200 --> 01:46:52,500
We can also assess the metabolites that are
derived from the gut microbiome, which is largely

1265
01:46:52,500 --> 01:46:58,240
uncharacterized but may represent 10-20% of
the plasma metabolome.

1266
01:46:58,240 --> 01:47:04,699
As well as supplements, pharmaceuticals and
their derivatives, commercial products, and

1267
01:47:04,699 --> 01:47:07,500
environmental chemicals.

1268
01:47:07,500 --> 01:47:17,619
Now, this KEGG map shows the breadth of what
high-resolution metabolomics can allow us

1269
01:47:17,619 --> 01:47:27,740
to explore, including lipid metabolism, carbohydrate
metabolism on the top, on the bottom, energy

1270
01:47:27,740 --> 01:47:30,380
metabolism, xenobiotic metabolism, etc.

1271
01:47:30,380 --> 01:47:36,040
And currently, we can measure over 20,000
metabolites in individual plasma samples spanning

1272
01:47:36,040 --> 01:47:38,830
the known human metabolic pathways.

1273
01:47:38,830 --> 01:47:47,489
Now, for high-resolution metabolomics, we
use various approaches, targeted HRM can focus

1274
01:47:47,489 --> 01:47:55,280
on a predefined list of metabolites such as
amino acids shown here, untargeted or discovery

1275
01:47:55,280 --> 01:48:01,390
high-resolution metabolomics, looks at all
detected metabolic features, or metabolites.

1276
01:48:01,390 --> 01:48:06,440
And the third thing is, pathway and network
analysis, which can map metabolic features,

1277
01:48:06,440 --> 01:48:11,850
or metabolites, to biological pathways, and
identify interconnections.

1278
01:48:11,850 --> 01:48:18,260
In reality, it's common for all three of these
approaches to be used in a metabolomics study.

1279
01:48:18,260 --> 01:48:26,030
This is the workflow for plasma high-resolution
metabolomics in the Dean Jones lab at Emory.

1280
01:48:26,030 --> 01:48:31,640
I'm not going to go through the details, this
has been well worked out over the past decade,

1281
01:48:31,640 --> 01:48:33,949
and it's a now very robust system.

1282
01:48:33,949 --> 01:48:40,619
But we basically use high-resolution mass
spectrometry instruments, dual chromatography

1283
01:48:40,619 --> 01:48:46,810
with HILIC positive, and C18 negative columns,
sophisticated data extraction and quality

1284
01:48:46,810 --> 01:48:53,119
evaluations, and then Biostatistics and Bioinformatics
programs that are built in.

1285
01:48:53,119 --> 01:49:00,290
And then finally, we do a program called Mummichog
for network and pathway analysis and are able

1286
01:49:00,290 --> 01:49:06,780
to confirm our metabolites using reference
standardization or Tandem MS.

1287
01:49:06,780 --> 01:49:13,540
Now, metabolome-wide association studies,
or MWAS is the study of the associations between

1288
01:49:13,540 --> 01:49:18,580
a measured variable or phenotype of interest
and all detected metabolites.

1289
01:49:18,580 --> 01:49:23,810
We can correlate metabolites that we detect,
for example in plasma, with specific clinical,

1290
01:49:23,810 --> 01:49:25,420
and phenotypic variables.

1291
01:49:25,420 --> 01:49:30,170
And this list is highly relevant to nutritional
metabolomics.

1292
01:49:30,170 --> 01:49:38,900
For example number one, we can correlate metabolomic
changes to, for example, subgroups of survivors

1293
01:49:38,900 --> 01:49:39,920
compared to nonsurvivors.

1294
01:49:39,920 --> 01:49:49,260
Further down, we can look at body composition,
exploring links with lean mass, bone, and fat.

1295
01:49:49,260 --> 01:49:54,870
We can look at respiratory quotient links
with metabolomic analysis, and we can correlate

1296
01:49:54,870 --> 01:50:01,850
the human metabolome with functional endpoints
such as FEV1, a key marker of lung function,

1297
01:50:01,850 --> 01:50:08,060
or handgrip strength, as well as several other
aspects as shown here.

1298
01:50:08,060 --> 01:50:14,380
Now, I'd like to show the utility of plasma
metabolomics in body composition analysis,

1299
01:50:14,380 --> 01:50:20,881
and here, a graduate student in our lab, Moriah
Bellissimo explored the link with lean mass

1300
01:50:20,881 --> 01:50:29,250
index, and we studied working adults from
Emory who were clinically stable, not hospitalized

1301
01:50:29,250 --> 01:50:34,860
within the past year, no uncontrolled chronic
diseases, or acute diseases.

1302
01:50:34,860 --> 01:50:41,310
And we looked at 180 participants, we had
plasma high-resolution metabolomics done using

1303
01:50:41,310 --> 01:50:44,790
the workflow I showed earlier.

1304
01:50:44,790 --> 01:50:50,100
We looked at fasting blood draws, which is
important because diet, or food intake, can

1305
01:50:50,100 --> 01:50:52,579
obviously affect the metabolome.

1306
01:50:52,579 --> 01:50:58,290
We did body composition by DEXA and calculated
the lean mass index with the equation shown

1307
01:50:58,290 --> 01:51:04,040
there, and did reference standardization to
quantitate targeted amino acids and linked

1308
01:51:04,040 --> 01:51:06,600
metabolites.

1309
01:51:06,600 --> 01:51:13,630
In this Mummichog plot, you can see that we
identified the dots which are 5,360 total

1310
01:51:13,630 --> 01:51:16,760
metabolic features, or metabolites, in this
particular experiment.

1311
01:51:16,760 --> 01:51:25,091
93 of the features were related to lean mass
index using very stringent FDR criteria, or

1312
01:51:25,091 --> 01:51:31,099
false discovery rate criteria, with the line
shown there, and then several hundred over 500

1313
01:51:31,099 --> 01:51:38,260
to be exact, were statistically significant
using raw p-values as shown in the lower line.

1314
01:51:38,260 --> 01:51:43,900
The dots indicate that the blue metabolites
are positively related to the lean mass index,

1315
01:51:43,900 --> 01:51:51,130
and the red metabolites were negatively related
on a continuous variable analysis.

1316
01:51:51,130 --> 01:51:57,870
We took these 500-plus metabolites and incorporated
them into the software program, and found

1317
01:51:57,870 --> 01:52:03,510
that diverse metabolic pathways were linked
to lean mass index in this population.

1318
01:52:03,510 --> 01:52:12,310
The horizontal blue bars are the statistical
significance shown, and then the metabolic

1319
01:52:12,310 --> 01:52:18,340
pathways that were significant are all outlined
on the left side, you can see the arrows showing

1320
01:52:18,340 --> 01:52:25,110
that a number of amino acid metabolic pathways,
including branched chain amino acids, etc.,

1321
01:52:25,110 --> 01:52:29,000
were significantly linked to lean mass index.

1322
01:52:29,000 --> 01:52:35,620
We also found that butyrate metabolism, purine
metabolism, and niacin metabolism were also

1323
01:52:35,620 --> 01:52:38,850
linked to lean mass index in this experiment.

1324
01:52:38,850 --> 01:52:47,270
We did network analysis in these data which
links metabolites that are most strongly associated

1325
01:52:47,270 --> 01:52:52,639
with each other, and we found that there was
a network that was derived from branched-chain

1326
01:52:52,639 --> 01:52:58,900
amino acids, phenylalanine, glutamate, and
tryptophan metabolism, highlighted here.

1327
01:52:58,900 --> 01:53:05,130
But we also found a number of gut microbiome-derived
metabolites, including indoles, phenylpyruvate,

1328
01:53:05,130 --> 01:53:10,710
etc., which we found quite interesting because
it's something that's not been previously

1329
01:53:10,710 --> 01:53:11,710
well-described.

1330
01:53:11,710 --> 01:53:20,690
So, moving on to another example of nutritional
metabolomics, this is 33 healthy adults who

1331
01:53:20,690 --> 01:53:26,239
had indirect calorimetry done at fasting,
and we used the same workflow that I showed

1332
01:53:26,239 --> 01:53:33,260
earlier, and we have two columns C18 on the
left, and HILIC on the right.

1333
01:53:33,260 --> 01:53:39,940
And you can see in this bubble plot that,
a whole range of metabolic pathways are linked

1334
01:53:39,940 --> 01:53:48,060
to the respiratory quotient value, tyrosine
metabolism, pyrimidine metabolism, and several

1335
01:53:48,060 --> 01:53:55,900
lipid metabolic pathways, including glycerolphospholipid,
bile acid synthesis, butyrate metabolism,

1336
01:53:55,900 --> 01:54:02,830
all linked to respiratory quotient in healthy
adults at fasting.

1337
01:54:02,830 --> 01:54:08,190
Another example is linking metabolomics data
to relevant nutritional outcomes.

1338
01:54:08,190 --> 01:54:14,579
This was a study I did with my colleague Jessica
A. Alvarez, and others, in patients with cystic

1339
01:54:14,579 --> 01:54:21,330
fibrosis admitted within 48 hours for hospitalization
due to a pulmonary exacerbation.

1340
01:54:21,330 --> 01:54:28,020
And they were age 29 on average, roughly balanced
by sex, and their FEV1, or their lung function,

1341
01:54:28,020 --> 01:54:31,000
was about half of what it should be.

1342
01:54:31,000 --> 01:54:39,260
And here we did a study using similar methods
as I showed you, to link lung function associated

1343
01:54:39,260 --> 01:54:43,540
with nutrient-related metabolic pathways using
plasma metabolomics.

1344
01:54:43,540 --> 01:54:50,119
And, you can see here in the arrows, a number
of amino acid pathways were significantly

1345
01:54:50,119 --> 01:54:53,530
linked to FEV1 using this methodology.

1346
01:54:53,530 --> 01:55:00,679
We also found a number of lipid-related pathways
that were linked to FEV1, including on top

1347
01:55:00,679 --> 01:55:07,870
glycerolphospholipid, next linoleic metabolism,
lower down omega-6 fatty acid metabolism,

1348
01:55:07,870 --> 01:55:08,870
etc.

1349
01:55:08,870 --> 01:55:18,639
The last example is using high-resolution
metabolomics to explore micronutrient status

1350
01:55:18,639 --> 01:55:20,530
in a particular patient population.

1351
01:55:20,530 --> 01:55:26,210
Here we looked at with my colleague Kürşat
Gundogan from Turkey, adults who were admitted

1352
01:55:26,210 --> 01:55:28,639
to a single ICU.

1353
01:55:28,639 --> 01:55:34,930
We obtained plasma on ICU admission for thiamine
pyrophosphate, TPP, the active form of thiamin,

1354
01:55:34,930 --> 01:55:39,000
and we did the concomitant high-resolution
metabolomics.

1355
01:55:39,000 --> 01:55:46,031
We adjusted the HRM data for age, sex, BMI,
and APACHE II score, or illness severity, on

1356
01:55:46,031 --> 01:55:48,500
ICU admission.

1357
01:55:48,500 --> 01:55:53,870
And this is also a Mummichog plot, we've colored
it a little bit different way, but we found

1358
01:55:53,870 --> 01:56:01,770
there were broad associations of plasma TPP
with metabolism in these critically ill adults

1359
01:56:01,770 --> 01:56:06,670
that were as a function of thiamine status,
we did a TPP MWAS, if you will.

1360
01:56:06,670 --> 01:56:13,099
And you can see that glucose metabolism, including
pentose phosphate pathway, lipid metabolism

1361
01:56:13,099 --> 01:56:18,800
including, you know, linoleic metabolism,
further down vitamin metabolism including

1362
01:56:18,800 --> 01:56:29,660
niacin metabolism, were all linked to the
level of TPP on admission to the ICU.

1363
01:56:29,660 --> 01:56:34,830
I think significant utility of metabolomics
in nutrition, and obesity research, we can

1364
01:56:34,830 --> 01:56:39,870
gain pathophysiologic insight into complex
diseases.

1365
01:56:39,870 --> 01:56:44,770
We can use metabolomics to link metabolites
and their link to metabolic pathways with

1366
01:56:44,770 --> 01:56:50,750
clinical outcomes such as survival, non-survival,
time on the ventilator, etc., to inform

1367
01:56:50,750 --> 01:56:52,619
targeted nutritional interventions.

1368
01:56:52,619 --> 01:56:59,020
We can explore metabolic responses to specific
nutritional interventions.

1369
01:56:59,020 --> 01:57:06,210
We can generate hypotheses for later targeted
studies, and we can identify potential biomarkers

1370
01:57:06,210 --> 01:57:10,010
for disease onset, progression, and resolution.

1371
01:57:10,010 --> 01:57:18,310
We can also use this data, and available open
access programs, to explore the host metabolome

1372
01:57:18,310 --> 01:57:23,950
in response to various situations with other
omics, including the gut microbiome.

1373
01:57:23,950 --> 01:57:30,449
And finally, we can use metabolomics, I believe,
in the future to optimize nutritional therapies

1374
01:57:30,449 --> 01:57:35,090
in individuals or precision medicine, or precision
nutrition.

1375
01:57:35,090 --> 01:57:37,030
Thank you very much.

1376
01:57:37,030 --> 01:57:43,719
DR. KENNETH CHRISTOPHER: Hello, my name is Kenneth
Christopher, I'm delighted to have the opportunity

1377
01:57:43,719 --> 01:57:49,500
to present to you, on BMI metabolomics, Making
the Complex Simple.

1378
01:57:49,500 --> 01:57:56,650
In terms of my disclosures, I don't accept
honoraria, nor do consulting work for the

1379
01:57:56,650 --> 01:58:01,750
pharmaceutical or device industries, and this
work was funded by the National Institutes

1380
01:58:01,750 --> 01:58:02,980
of Health.

1381
01:58:02,980 --> 01:58:10,300
In terms of how to study metabolomics, first,
we have sample collection, then the actual

1382
01:58:10,300 --> 01:58:19,210
sample is analyzed using mass spectrophotometry
where one can separate and identify the different

1383
01:58:19,210 --> 01:58:22,290
metabolites that are identifiable.

1384
01:58:22,290 --> 01:58:27,050
And then the third step is data analysis,
and data analysis can be data visualization

1385
01:58:27,050 --> 01:58:32,980
to help you see patterns, it can be things
like logistic, or linear regression, to see

1386
01:58:32,980 --> 01:58:40,300
patterns over time in terms of adjusting for
common features like age and severity of illness,

1387
01:58:40,300 --> 01:58:41,300
etc.

1388
01:58:41,300 --> 01:58:45,130
This particular project that we're going to
talk about comes from a randomized controlled

1389
01:58:45,130 --> 01:58:52,230
trial that was published in 2014, that randomized
patients to high-dose vitamin D, this, as

1390
01:58:52,230 --> 01:58:55,910
in most critical illness trials, was a neutral
trial.

1391
01:58:55,910 --> 01:59:01,060
The way that this particular study that we're
going to talk about was designed, patients were

1392
01:59:01,060 --> 01:59:05,510
enrolled who had a vitamin D less than 20
ng/mL.

1393
01:59:05,510 --> 01:59:11,210
They received either high-dose vitamin D,
or they received placebo, and lucky for me,

1394
01:59:11,210 --> 01:59:17,140
blood was collected on days zero, three, and
seven, along with all of the clinical trial

1395
01:59:17,140 --> 01:59:19,250
covariates, and outcomes.

1396
01:59:19,250 --> 01:59:28,350
I had those particular blood samples analyzed
for metabolites, we analyzed 983 metabolites

1397
01:59:28,350 --> 01:59:29,670
in each sample.

1398
01:59:29,670 --> 01:59:35,909
What I wanted to focus on today is looking
at the differences in terms of patients who

1399
01:59:35,909 --> 01:59:43,580
do or do not have excess adipose tissue by
proxy, measured by body mass index.

1400
01:59:43,580 --> 01:59:50,760
So, the question that we asked was, does individual
metabolite abundance, say the amount of each

1401
01:59:50,760 --> 01:59:57,090
metabolite in one's bloodstream at a particular
time, in critically ill patients with BMI

1402
01:59:57,090 --> 01:59:58,790
greater than, or equal to 30?

1403
01:59:58,790 --> 02:00:02,980
Does that differ in those who have a normal
body mass index?

1404
02:00:02,980 --> 02:00:10,469
So, we have the normal body mass index, and
metabolomics, and we have the equal to or

1405
02:00:10,469 --> 02:00:13,329
over 30 BMI metabolomics analyzed.

1406
02:00:13,329 --> 02:00:19,230
And the idea is to compare those two and see
if we can find a consistent pattern with the

1407
02:00:19,230 --> 02:00:23,644
large number of samples we have, and the large
number of patients.

1408
02:00:23,644 --> 02:00:29,000
The hypothesis was that critically ill patients
with BMI greater or equal to 30 will have

1409
02:00:29,000 --> 02:00:36,060
differential metabolomics, meaning that their
metabolome in terms of all of the metabolites

1410
02:00:36,060 --> 02:00:40,619
together will differ in terms of the BMI groups.

1411
02:00:40,619 --> 02:00:47,329
I thought specifically energy utilization
would be different simply because of the large

1412
02:00:47,329 --> 02:00:55,080
number of, like the lipolysis of potential cells
in terms of adipose tissue, that could respond

1413
02:00:55,080 --> 02:00:56,970
to these stress hormones.

1414
02:00:56,970 --> 02:01:00,110
And this is, again, in comparison to patients
who have a normal BMI.

1415
02:01:00,110 --> 02:01:06,869
You see, the exposure was patients who had
BMI greater than 30, the comparator was a

1416
02:01:06,869 --> 02:01:15,159
normal BMI, and the outcome was the individual
metabolite abundance of 983 individual outcomes

1417
02:01:15,159 --> 02:01:19,500
in terms of looking at each one of these metabolites.

1418
02:01:19,500 --> 02:01:24,990
And so the overall design, we have our different
patient groups, all of the patients had a

1419
02:01:24,990 --> 02:01:30,980
critical illness, the patients were all randomized
to either high-dose vitamin D, or placebo,

1420
02:01:30,980 --> 02:01:37,860
plasma was obtained on all patients in the
time points of days zero, three, and seven,

1421
02:01:37,860 --> 02:01:41,500
and metabolomics was run on all of the plasma
samples.

1422
02:01:41,500 --> 02:01:48,639
And so metabolite identification, and the
relative abundance, could be determined for

1423
02:01:48,639 --> 02:01:54,060
each metabolite, each one of the 983 metabolites.

1424
02:01:54,060 --> 02:01:59,260
In terms of the baseline characteristics,
it's very similar to the actual baseline trial

1425
02:01:59,260 --> 02:02:06,370
where in terms of our differences between
patients with normal BMI, and BMI greater

1426
02:02:06,370 --> 02:02:13,159
than 30, a 28-day mortality was statistically
different with the percentage of normal being

1427
02:02:13,159 --> 02:02:21,139
28, and the BMI greater than 30, being 16%,
otherwise, the cohorts were relatively matched.

1428
02:02:21,139 --> 02:02:25,909
Looking at unadjusted analyses at day three,
and the question is, what is the metabolic

1429
02:02:25,909 --> 02:02:27,480
difference between the two groups?

1430
02:02:27,480 --> 02:02:32,829
And we used a technique called Orthogonal
Projections to Latent Structures Discriminant

1431
02:02:32,829 --> 02:02:37,110
Analysis, and I'll show you that particular
analysis result.

1432
02:02:37,110 --> 02:02:43,220
These particular score plots, we call them OPLS-DA score
plots, well, let us ask the question: Are

1433
02:02:43,220 --> 02:02:46,219
the two groups different metabolically?

1434
02:02:46,219 --> 02:02:51,860
What it does is it sums up all of the metabolites
into one spot, so the spot will be the patient,

1435
02:02:51,860 --> 02:02:54,690
I'll show you the graphic in a second.

1436
02:02:54,690 --> 02:02:59,440
We also looked at the Variable Importance
Plot, and this is figuring out which of the

1437
02:02:59,440 --> 02:03:05,829
983 metabolites are the most important for
difference in this particular score plot.

1438
02:03:05,829 --> 02:03:10,370
So, we will see differences between the two
groups, the question is, which individual

1439
02:03:10,370 --> 02:03:13,889
metabolites are most important for that difference?

1440
02:03:13,889 --> 02:03:19,460
And then looking at what's called an S-plot,
which helps us identify which individual metabolites

1441
02:03:19,460 --> 02:03:23,489
are potentially of interest. A little bit
different way of looking at the data.

1442
02:03:23,489 --> 02:03:29,829
So, in terms of this OPLS score plot, what
it does essentially is, it takes this multi-dimensional

1443
02:03:29,829 --> 02:03:32,579
metabolome if you will.

1444
02:03:32,579 --> 02:03:36,469
It shines a light through it and ends up with
a two-dimensional type of figure, and it allows

1445
02:03:36,469 --> 02:03:40,699
us to try to figure out, number one, are there
differences in the groups?

1446
02:03:40,699 --> 02:03:47,809
And then look into whether or not those particular
metabolites make up for those particular differences.

1447
02:03:47,809 --> 02:03:51,909
Which metabolites are responsible for the
two groups being separated?

1448
02:03:51,909 --> 02:03:58,909
And so this is an example where we have normal-weight
patients in green and the obese patients in

1449
02:03:58,909 --> 02:04:00,090
the blue.

1450
02:04:00,090 --> 02:04:04,400
Each dot is a summation of all the 983 metabolites.

1451
02:04:04,400 --> 02:04:08,579
It is the individual's metabolome.

1452
02:04:08,579 --> 02:04:14,050
And what I've done is I have subtracted the
colors on each one with the next slide so

1453
02:04:14,050 --> 02:04:15,460
you can see the differences.

1454
02:04:15,460 --> 02:04:20,500
And so if we look at the normal weight patients,
those are all in the green, I've subtracted the

1455
02:04:20,500 --> 02:04:27,619
blue and then we look at the blue patients
or the overweight patients, you can see that

1456
02:04:27,619 --> 02:04:33,329
those particular patients are on different
sides of this particular circle indicating

1457
02:04:33,329 --> 02:04:41,790
that there is separation at day three in terms
of obese patients versus normal weight patients

1458
02:04:41,790 --> 02:04:47,889
in the way all of their metabolites respond
to their illness.

1459
02:04:47,889 --> 02:04:54,090
Looking at the VIP scores and this is the
variable in terms of the projection, which

1460
02:04:54,090 --> 02:05:00,190
metabolites are the most important for separating
the two groups in terms of the individuals

1461
02:05:00,190 --> 02:05:03,440
themselves, which metabolites are high or
low?

1462
02:05:03,440 --> 02:05:10,460
And in this particular analysis, we can see
that most of the metabolites that are responsible

1463
02:05:10,460 --> 02:05:16,230
for the differences between the two groups
are things called diacylglycerol and also

1464
02:05:16,230 --> 02:05:19,329
long-chain acylcarnitines.

1465
02:05:19,329 --> 02:05:23,219
This is the S-plot where we're looking at
feature importance, a little bit different

1466
02:05:23,219 --> 02:05:25,139
way of looking at the data.

1467
02:05:25,139 --> 02:05:30,800
And if we look at the absolute extremes at
the top and the bottom of the S, if you will,

1468
02:05:30,800 --> 02:05:37,010
we have diacylglycerol and then long-chain
acylcarnitines, those pop out and at the other

1469
02:05:37,010 --> 02:05:39,020
end we have androgens.

1470
02:05:39,020 --> 02:05:44,770
So our first obstacle where human variability
is a problem, and we only have 254 patients,

1471
02:05:44,770 --> 02:05:47,020
we need a large sample size.

1472
02:05:47,020 --> 02:05:50,530
Our repeat sampling actually increases study
power.

1473
02:05:50,530 --> 02:05:52,659
The number two, the repeat sampling is a problem.

1474
02:05:52,659 --> 02:05:53,659
It's not independent.

1475
02:05:53,659 --> 02:05:59,679
And so we use a special model called Linear
Mixed Model that accounts for this non-independence

1476
02:05:59,679 --> 02:06:05,900
between samples using the patient identity
as a particular way of accounting for that.

1477
02:06:05,900 --> 02:06:11,080
Age and sex and severity of illness probably
account for some of our observations.

1478
02:06:11,080 --> 02:06:15,800
Sure, we adjust for all of those particular
pieces.

1479
02:06:15,800 --> 02:06:17,730
And then what about this intervention?

1480
02:06:17,730 --> 02:06:22,989
We also adjust for the response to intervention
because we have 25 OHD levels, which

1481
02:06:22,989 --> 02:06:27,570
would be the proxy for how patients responded
to the intervention.

1482
02:06:27,570 --> 02:06:33,820
And then this repeated measure issue, we correct
for what's called multiplicity using a False

1483
02:06:33,820 --> 02:06:35,150
Discovery Rate adjustment.

1484
02:06:35,150 --> 02:06:41,530
And what that does it's the rate that metabolites
that are called significant are actually not

1485
02:06:41,530 --> 02:06:42,530
significant.

1486
02:06:42,530 --> 02:06:47,239
So it's a penalization.

1487
02:06:47,239 --> 02:06:50,020
And so our P-value that we're looking at is
no longer 0.05.

1488
02:06:50,020 --> 02:06:55,030
So, the solution again for this multiplicity
is Linear Mixed Models.

1489
02:06:55,030 --> 02:07:01,040
This is a slide of the metabolites that were
increased with obesity.

1490
02:07:01,040 --> 02:07:06,469
And what we see is we see a large number of
metabolites all from the diacylglycerol family.

1491
02:07:06,469 --> 02:07:11,280
And we also can find that same pattern with
the long-chain acylcarnitines.

1492
02:07:11,280 --> 02:07:16,500
So, that's our adjusted analysis with day
zero, three and seven data.

1493
02:07:16,500 --> 02:07:23,090
And the highlights now are the diacylglycerol,
again, involved in immune cell activation,

1494
02:07:23,090 --> 02:07:24,369
regulation and function.

1495
02:07:24,369 --> 02:07:30,809
And then the long-chain acylcarnitines where
elevated fatty acid supply from high lipolysis

1496
02:07:30,809 --> 02:07:33,849
exceeds mitochondrial oxidative capacity.

1497
02:07:33,849 --> 02:07:39,940
And so in summary, we have significant metabolomic
differences that exist between obese critically

1498
02:07:39,940 --> 02:07:43,770
ill patients compared to those with normal
BMI.

1499
02:07:43,770 --> 02:07:49,500
We have an elevation of diacylglycerol and
we have an increase in long-chain acylcarnitines.

1500
02:07:49,500 --> 02:07:50,699
Thank you very much for your attention.

1501
02:07:50,699 --> 02:07:53,179
I look forward to your questions.

1502
02:07:53,179 --> 02:07:54,830
DR. RAED A.DWEIK: Hello, everyone.

1503
02:07:54,830 --> 02:08:00,530
I'm Raed Dweik, chairman of the Respiratory
Institute at the Cleveland Clinic.

1504
02:08:00,530 --> 02:08:06,229
And I'm pleased to be here today to talk to
you about breath analysis to identify malnutrition

1505
02:08:06,229 --> 02:08:07,760
in clinical settings.

1506
02:08:07,760 --> 02:08:14,059
While it is thought that breath analysis is
a recent advance in medicine, it actually

1507
02:08:14,059 --> 02:08:21,699
is as old as medicine itself when Hippocrates
identified in his Treatise on breath aroma

1508
02:08:21,699 --> 02:08:24,750
and disease, fetor oris and fetor hepaticus.

1509
02:08:24,750 --> 02:08:29,140
Several other advances in our understanding
of physiology and medicine we have breath

1510
02:08:29,140 --> 02:08:35,139
analysis, including the identification that
respiration consumes oxygen and eliminates

1511
02:08:35,139 --> 02:08:41,139
carbon dioxide, that diabetics emit acetone
and exhale breath and our ability to isolate

1512
02:08:41,139 --> 02:08:46,389
alcohol from breath, which is the basis of
current law enforcement testing.

1513
02:08:46,389 --> 02:08:53,160
But I think arguably the 21st century has
experienced an explosion in our understanding

1514
02:08:53,160 --> 02:08:59,079
of breath analysis due to major advancements
in technology.

1515
02:08:59,079 --> 02:09:01,540
So what is in our breath?

1516
02:09:01,540 --> 02:09:07,090
While we all recognize that our breath contains
oxygen, which we inhale and carbon dioxide

1517
02:09:07,090 --> 02:09:12,470
which we exhale, predominantly our breath
is nitrogen like the atmosphere.

1518
02:09:12,470 --> 02:09:15,900
And once we exhale it, it's fully saturated
with water.

1519
02:09:15,900 --> 02:09:23,389
But I want to point you to the fact that our
breath also contains small amounts of compounds

1520
02:09:23,389 --> 02:09:29,090
like alkanes, aldehydes and ketones, etc.,
that are known collectively as volatile organic

1521
02:09:29,090 --> 02:09:30,090
compounds.

1522
02:09:30,090 --> 02:09:36,710
While these represent only 1% or less of the
breath, they have significant implications

1523
02:09:36,710 --> 02:09:42,329
for understanding health and disease, and
they are present in very small amounts, sometimes

1524
02:09:42,329 --> 02:09:47,980
in parts per million or even parts per billion
range.

1525
02:09:47,980 --> 02:09:52,440
So, technological advancements is what allowed
us to be able to detect these compounds in

1526
02:09:52,440 --> 02:09:53,500
exhale breath.

1527
02:09:53,500 --> 02:09:59,110
And the table here shows the different methods
that currently available to analyze the breath.

1528
02:09:59,110 --> 02:10:03,690
But I want to point you to the right side of
the slide here, to the fact that all of these

1529
02:10:03,690 --> 02:10:08,290
really fall under two general categories,
either electronic nose, which is part of a

1530
02:10:08,290 --> 02:10:12,800
larger group known as the sensor arrays or
mass spectrometry.

1531
02:10:12,800 --> 02:10:16,340
And they're completely different approaches
to analyzing the breath.

1532
02:10:16,340 --> 02:10:21,980
The electronic nose functions in a very similar
fashion to the human nose where it recognizes

1533
02:10:21,980 --> 02:10:22,980
patterns.

1534
02:10:22,980 --> 02:10:24,400
And it once it's trained on a smell, it can
recognize it.

1535
02:10:24,400 --> 02:10:30,210
So like even if I blindfold you and give you
an orange to smell, you know it's an orange,

1536
02:10:30,210 --> 02:10:34,489
but I've given you something that you never
smelled before, you either would not know

1537
02:10:34,489 --> 02:10:37,150
or would guess wrongly.

1538
02:10:37,150 --> 02:10:43,199
Mass spectrometry, on the other hand, analyzes
all the compounds and the peaks in exhaled breath

1539
02:10:43,199 --> 02:10:45,989
but unable to recognize patterns.

1540
02:10:45,989 --> 02:10:51,909
So, the way we approach breath analysis is
really to combine the best of both these worlds

1541
02:10:51,909 --> 02:10:58,230
in that we look at mass spectrometry, which
is our main method of analysis, but analyze

1542
02:10:58,230 --> 02:11:06,190
the data in a pattern recognition approach
like the electronic nose would do.

1543
02:11:06,190 --> 02:11:11,320
Utilizing this best of both worlds approach, 
we are able to identify many disease states,

1544
02:11:11,320 --> 02:11:18,770
including lung cancer, different liver diseases,
as well as kidney disease and renal failure.

1545
02:11:18,770 --> 02:11:24,260
These I refer to as the low hanging fruit
since patients with liver disease or kidney

1546
02:11:24,260 --> 02:11:30,530
disease are known to have an abnormal smell
to their breath.

1547
02:11:30,530 --> 02:11:34,960
But we were, so that did not surprise us that
we were pleased that we were able to identify

1548
02:11:34,960 --> 02:11:38,160
and quantify the breath of these patients.

1549
02:11:38,160 --> 02:11:42,910
We were surprised, however, to be able to
identify that patients with heart failure,

1550
02:11:42,910 --> 02:11:47,440
which usually have a bland breath and also
have a distinct breath print.

1551
02:11:47,440 --> 02:11:53,869
And you can see in this particular study the
patients with heart failure in the blue and

1552
02:11:53,869 --> 02:11:59,929
green dots here have a distinct breath print
compared to those who are controls in red.

1553
02:11:59,929 --> 02:12:04,030
We were surprised by this finding to the point
that we repeated it twice, and that's why

1554
02:12:04,030 --> 02:12:10,190
there are green dots and blue dots to represent
two different cohorts of patients done separately

1555
02:12:10,190 --> 02:12:12,860
to make sure that our findings are correct.

1556
02:12:12,860 --> 02:12:18,000
Once we were able to identify the breath print
of heart failure, we really started looking

1557
02:12:18,000 --> 02:12:19,329
into many disease states.

1558
02:12:19,329 --> 02:12:25,150
And the way I think of it now, as the breath
being the headspace of the blood, anything,

1559
02:12:25,150 --> 02:12:29,659
any compound that is in the blood that is
potentially volatile at room or body temperature

1560
02:12:29,659 --> 02:12:34,630
can be identified in the breath and can help
identify different disease states.

1561
02:12:34,630 --> 02:12:39,329
One area I focused my research on and my clinical
expertise in pulmonary hypertension and in

1562
02:12:39,329 --> 02:12:45,579
those patients, like patients with heart failure,
they really do not have a particular breath

1563
02:12:45,579 --> 02:12:52,570
smell, but we were able to identify their
breath print as shown here in this graph compared

1564
02:12:52,570 --> 02:12:53,570
to controls.

1565
02:12:53,570 --> 02:12:57,020
And again, we repeated this twice to make
sure that is accurate.

1566
02:12:57,020 --> 02:13:01,940
So in addition to this pattern recognition,
we're able to identify certain compounds that

1567
02:13:01,940 --> 02:13:07,639
are elevated in pulmonary hypertension patients
you see in the red graphs here compared to

1568
02:13:07,639 --> 02:13:09,820
controls in the blue.

1569
02:13:09,820 --> 02:13:17,909
So, you know, we were pleased to find out
that we were able to identify multiple breathprints

1570
02:13:17,909 --> 02:13:19,329
for multiple disease states.

1571
02:13:19,329 --> 02:13:23,389
We still have many challenges that we have
to overcome for breath analysis to become

1572
02:13:23,389 --> 02:13:25,429
mainstream in testing.

1573
02:13:25,429 --> 02:13:26,860
One of them is the mouth.

1574
02:13:26,860 --> 02:13:31,100
Of course, all breath analysis is done through
the mouth, and you can see if there are any

1575
02:13:31,100 --> 02:13:36,429
particular volatiles coming from the mouth
we have to deal with those as well.

1576
02:13:36,429 --> 02:13:42,829
The medications we take affect our breath print,
the microbiome or the gut bacteria produce

1577
02:13:42,829 --> 02:13:46,559
many compounds that can be detected in the
blood and the breath.

1578
02:13:46,559 --> 02:13:48,330
And importantly, the environment.

1579
02:13:48,330 --> 02:13:51,389
We are sampling vessels as we walk around.

1580
02:13:51,389 --> 02:13:57,659
We are inhaling whatever our environment has,
and once breath is analyzed and exhaled, we

1581
02:13:57,659 --> 02:14:00,460
can detect these compounds in the breath as
well.

1582
02:14:00,460 --> 02:14:06,910
For the sake of today's presentation, diet
also is a major contributor to our breath print.

1583
02:14:06,910 --> 02:14:12,309
And while here I'm proposing it as a challenge,
and the rest of the presentation, I'm going to

1584
02:14:12,309 --> 02:14:19,090
talk to how we started looking at the breath prints
as a way maybe to identify the nutritional

1585
02:14:19,090 --> 02:14:21,020
status of individuals.

1586
02:14:21,020 --> 02:14:27,309
This is when we partnered with Dr. John Kirwan
and Jacob Mey to look at the breath print

1587
02:14:27,309 --> 02:14:32,639
of patients with pulmonary arterial hypertension,
a disease that we studied extensively to see

1588
02:14:32,639 --> 02:14:37,329
if we can also identify a nutritional status
in these patients.

1589
02:14:37,329 --> 02:14:41,970
We collaborated with our nutrition department
and multiple dietitians in the Cleveland Clinic

1590
02:14:41,970 --> 02:14:46,770
to be able to look back in the medical records
of those patients we had breath prints on

1591
02:14:46,770 --> 02:14:51,260
and to see if we can also identify their nutrition
status.

1592
02:14:51,260 --> 02:14:56,250
So this is a diagram showing how we identified
these patients.

1593
02:14:56,250 --> 02:15:00,099
We are going through multiple inclusion and
exclusion criteria.

1594
02:15:00,099 --> 02:15:06,739
We identified 74 patients to be assigned into
PAH with malnutrition, or without malnutrition

1595
02:15:06,739 --> 02:15:09,580
and controls, with or without malnutrition.

1596
02:15:09,580 --> 02:15:17,600
And the ICD 10 diagnostic codes for malnutrition
are listed here for your interest.

1597
02:15:17,600 --> 02:15:22,099
The patient characteristics, I'm going to focus
on the PAH, patients without the majority

1598
02:15:22,099 --> 02:15:23,280
of the patients here.

1599
02:15:23,280 --> 02:15:24,909
They're similar in age.

1600
02:15:24,909 --> 02:15:29,040
They're predominantly female because pulmonary
hypertension predominantly affects females.

1601
02:15:29,040 --> 02:15:36,840
And the BMI was quite similar between PAH
with or without malnutrition.

1602
02:15:36,840 --> 02:15:42,521
And the time from breath data collection to
the nutrition assessment was anywhere from

1603
02:15:42,521 --> 02:15:49,460
30 days to 47 days, which is within a reasonable
timeframe.

1604
02:15:49,460 --> 02:15:52,230
What we found is really a couple of things.

1605
02:15:52,230 --> 02:15:57,520
One, it was reassuring to find out that still
the breast print of patients with pulmonary

1606
02:15:57,520 --> 02:16:03,750
hypertension identified in red is quite distinct
from those who don't have pulmonary hypertension

1607
02:16:03,750 --> 02:16:04,929
or controls in green.

1608
02:16:04,929 --> 02:16:09,719
There's only minor overlap with two patients,
individuals without pulmonary hypertension

1609
02:16:09,719 --> 02:16:11,889
identified with pulmonary hypertension.

1610
02:16:11,889 --> 02:16:17,540
But of course the more exciting finding here
is what you see here represented in black

1611
02:16:17,540 --> 02:16:23,520
dots are these patients with pulmonary hypertension
who have malnutrition, which ended up having

1612
02:16:23,520 --> 02:16:28,720
a distinct breath print from those with pulmonary
hypertension without malnutrition and from

1613
02:16:28,720 --> 02:16:29,720
controls.

1614
02:16:29,720 --> 02:16:35,440
Furthermore, if you looked at the right graph,
we were able to identify certain compounds

1615
02:16:35,440 --> 02:16:40,830
like ammonia and octene which are lower in
PAH with malnutrition compared with those

1616
02:16:40,830 --> 02:16:42,460
without malnutrition.

1617
02:16:42,460 --> 02:16:52,179
So if you use this data to construct an ROC
curve, we were able to have a curve with an

1618
02:16:52,179 --> 02:16:56,630
area under the curve of .85, which is a high
degree of sensitivity and specificity.

1619
02:16:56,630 --> 02:17:01,980
So I'm really, very excited about the results
of this proof of concept study.

1620
02:17:01,980 --> 02:17:09,349
Many challenges remain, and of course, the
breath matrix remains complex as you see it

1621
02:17:09,349 --> 02:17:10,950
on the right side here.

1622
02:17:10,950 --> 02:17:16,019
We are able to identify many disease states
to the point we are close to kind of use the

1623
02:17:16,019 --> 02:17:20,840
traffic light analogy of red, you have the
disease or the particular state, you're looking

1624
02:17:20,840 --> 02:17:25,450
at the green, the patient doesn't have it
and yellow is indeterminate.

1625
02:17:25,450 --> 02:17:30,559
But still, the technology we use to do this
is the mass spectrometry, which is very complex

1626
02:17:30,559 --> 02:17:32,969
and requires extensive analysis.

1627
02:17:32,969 --> 02:17:36,979
The promise of breath analysis however is
similar to what many people think when they

1628
02:17:36,979 --> 02:17:43,490
think breath analysis is the point of care
testing for alcohol that is used by law enforcement.

1629
02:17:43,490 --> 02:17:48,819
And I can see probably in the near future
how with more advancement in technology, like

1630
02:17:48,819 --> 02:17:54,319
certain attachments, sensor attachments can
be used in combination with devices like iPhones

1631
02:17:54,319 --> 02:18:01,700
to identify breath prints of certain health
status or disease states.

1632
02:18:01,700 --> 02:18:07,479
So, key takeaways from today are that human
breath contains thousands of volatile organic

1633
02:18:07,479 --> 02:18:08,479
compounds.

1634
02:18:08,479 --> 02:18:13,939
Advances in technology allowed us to explore
the complex matrix and breath analysis of

1635
02:18:13,939 --> 02:18:18,750
volatile organic compounds can identify breath prints
of health and disease.

1636
02:18:18,750 --> 02:18:22,639
And in the proof of concept study I showed
you today, we were able to provide the first

1637
02:18:22,639 --> 02:18:28,880
evidence that breath print is altered in malnutrition
and breath analysis, thus is a promising approach

1638
02:18:28,880 --> 02:18:30,979
to determine nutritional status.

1639
02:18:30,979 --> 02:18:33,080
Thank you for the opportunity to talk to you
today.

1640
02:18:33,080 --> 02:18:35,590
Have a great day.

1641
02:18:35,590 --> 02:18:39,599
DR. JOHN ALVERDY: Hello, my name is Dr. John Alverdy.

1642
02:18:39,599 --> 02:18:45,550
I first would like to thank the NIH, in particular
Dr. Christopher Lynch, Dr. Charlotte Pratt

1643
02:18:45,550 --> 02:18:50,280
and Dr. Ashley Vargas for the opportunity
to speak to you today and of course, to the

1644
02:18:50,280 --> 02:18:55,899
NIH for supporting our work over the years.

1645
02:18:55,899 --> 02:19:00,639
Now the definition of malnutrition has many
definitions, but I prefer to focus on this

1646
02:19:00,639 --> 02:19:05,679
one, not eating enough of the right things.

1647
02:19:05,679 --> 02:19:11,189
One question that often comes up is between
visceral protein status, muscle grip strength

1648
02:19:11,189 --> 02:19:12,189
and sarcopenia.

1649
02:19:12,189 --> 02:19:18,620
We have to ask, is this enough information
to diagnose malnutrition?

1650
02:19:18,620 --> 02:19:19,620
I think not.

1651
02:19:19,620 --> 02:19:24,399
I think we need to go beyond this and look
at our microbiota because microbes have co-evolved

1652
02:19:24,399 --> 02:19:25,399
with us.

1653
02:19:25,399 --> 02:19:29,160
They can sense our health status before we
can.

1654
02:19:29,160 --> 02:19:35,450
Remember they were here first, and it is in
their best interest to know the health status

1655
02:19:35,450 --> 02:19:40,929
of their host upon whom their survival depends.

1656
02:19:40,929 --> 02:19:46,929
So one hypothesis is that interrogating the
gut microbiome will generate a more predictive

1657
02:19:46,929 --> 02:19:51,080
picture of host health status during critical
illness.

1658
02:19:51,080 --> 02:19:56,540
And another might be that preserving essential
functions of the gut microbiome can change

1659
02:19:56,540 --> 02:20:00,730
the occurrence course and outcome of critical
illness.

1660
02:20:00,730 --> 02:20:07,939
Now, this represents 25 years of work from
my laboratory, and I think it's important

1661
02:20:07,939 --> 02:20:15,149
to recognize that host-derived bacterial activating
cues are released into the host-pathogen interaction

1662
02:20:15,149 --> 02:20:17,540
during critical illness.

1663
02:20:17,540 --> 02:20:23,560
These host factors signal bacteria and bacteria
release products that re-signal against the

1664
02:20:23,560 --> 02:20:28,170
host in a bidirectional interkingdom signal
exchange.

1665
02:20:28,170 --> 02:20:34,540
In addition, bacteria and bacterial communities
have a similar system in which there is interspecies

1666
02:20:34,540 --> 02:20:41,180
and intraspecies signal exchange, resulting
in a matchless web of dense, dynamic interactions

1667
02:20:41,180 --> 02:20:44,970
unique to and dependent on the environmental
context.

1668
02:20:44,970 --> 02:20:50,990
So virulence or harmfulness is neither a sole
property of the pathogen nor that of the host,

1669
02:20:50,990 --> 02:20:53,730
but rather it is a property of their interaction.

1670
02:20:53,730 --> 02:20:56,729
And it's complicated.

1671
02:20:56,729 --> 02:21:01,370
Yet nearly all biologic research is centered
on host genes.

1672
02:21:01,370 --> 02:21:02,370
Why?

1673
02:21:02,370 --> 02:21:07,000
Well, because we, animals, think we are the
only life on earth that really matters.

1674
02:21:07,000 --> 02:21:12,790
However, there are now multiple gene pools
to consider when interrogating the occurrence,

1675
02:21:12,790 --> 02:21:15,210
course and outcome of human disease.

1676
02:21:15,210 --> 02:21:17,130
And guess what?

1677
02:21:17,130 --> 02:21:23,510
You are missing most of them because unless
you look at the entire environmental metagenome

1678
02:21:23,510 --> 02:21:29,920
or what's known as the hologenome, you don't
really realize that the soil bacteria give

1679
02:21:29,920 --> 02:21:33,530
us the very food that we eat, the air that
we breathe.

1680
02:21:33,530 --> 02:21:40,040
In fact, the gas that we put in our cars that
we then, you know, allow emissions to blow

1681
02:21:40,040 --> 02:21:43,550
out into the atmosphere.

1682
02:21:43,550 --> 02:21:48,271
And critical illness involves exposure to
many things hyperoxia, antibiotics, chemically

1683
02:21:48,271 --> 02:21:51,350
defined diets, ECMO, polypharmacy, etc..

1684
02:21:51,350 --> 02:21:57,720
And you could imagine that the gut microbiota
metabolites that are produced become depleted.

1685
02:21:57,720 --> 02:22:03,220
And we became interested in this particular
area when we started looking at aryl hydrocarbon

1686
02:22:03,220 --> 02:22:12,109
receptor ligands and found that they bind
to specific cell types and the immune system

1687
02:22:12,109 --> 02:22:19,600
that can regulate what I call a recovery-directed
immune response.

1688
02:22:19,600 --> 02:22:24,600
And critically ill patients harbor a depleted
gut microbiome dominated by virulent healthcare-associated

1689
02:22:24,600 --> 02:22:25,890
pathogens.

1690
02:22:25,890 --> 02:22:31,630
This paper that we wrote is now nearly 10
years old, really showed this in starking

1691
02:22:31,630 --> 02:22:34,720
detail among critically ill patients.

1692
02:22:34,720 --> 02:22:40,229
So we've been working for the last several
years on the hypothesis that metabolites from

1693
02:22:40,229 --> 02:22:46,729
the gut microbiome are systemically distributed
and regulate the interaction between infecting

1694
02:22:46,729 --> 02:22:48,569
pathogens and the immune system.

1695
02:22:48,569 --> 02:22:54,800
We focus on several pathogens and macrophages
in this interkingdom signal exchange and

1696
02:22:54,800 --> 02:23:01,700
discovered that indoles secreted by the microbiome
can drive homeostatic gene expression that

1697
02:23:01,700 --> 02:23:08,570
crescendo/decrescendo cytokines that leads
to bacterial clearance, smooth bacterial clearance

1698
02:23:08,570 --> 02:23:14,229
and recovery, versus a more patho-adaptive
position where you have impaired bacterial

1699
02:23:14,229 --> 02:23:24,680
clearance, excess cytokine release, organ
damage, sepsis and mortality. And critical illness or sepsis or severe infection
is not an immune disorder.

1700
02:23:24,680 --> 02:23:30,580
-And critical illness or sepsis or severe infection
is not an immune disorder.

1701
02:23:30,580 --> 02:23:33,140
system is that very interaction.

1702
02:23:33,140 --> 02:23:38,690
Now, a lot can be measured these days, as
we know.

1703
02:23:38,690 --> 02:23:49,930
We can measure so many things have a very
robust, dense and visually appealing image

1704
02:23:49,930 --> 02:23:53,050
display of large data sets.

1705
02:23:53,050 --> 02:23:57,210
In fact, you know, big data science is the
next big thing.

1706
02:23:57,210 --> 02:24:06,310
But we still cannot resist the most common
reasoning error in medicine and biology, which

1707
02:24:06,310 --> 02:24:11,000
is confusing association with causation.

1708
02:24:11,000 --> 02:24:14,520
For example, serum albumin is diminished in
critical illness.

1709
02:24:14,520 --> 02:24:15,520
We know this.

1710
02:24:15,520 --> 02:24:20,120
It's also a prognostic marker for poor outcome.

1711
02:24:20,120 --> 02:24:24,560
Is the solution just to provide albumin and
increase the serum albumin and it will improve

1712
02:24:24,560 --> 02:24:25,560
outcome.

1713
02:24:25,560 --> 02:24:26,710
No, we know that doesn't work.

1714
02:24:26,710 --> 02:24:31,660
Yet now we can measure multiple metabolites
in many different compartments in the gut,

1715
02:24:31,660 --> 02:24:38,090
including the gut and including areas remote
from the gut, the peritoneum, cerebrospinal

1716
02:24:38,090 --> 02:24:40,130
fluid, blood, etc..

1717
02:24:40,130 --> 02:24:45,600
And then we feel that we can design chemically
defined diets with missing metabolites.

1718
02:24:45,600 --> 02:24:48,340
This is committing the same sort of reasoning
error.

1719
02:24:48,340 --> 02:24:53,890
And now there are all sorts of agents out
on the market.

1720
02:24:53,890 --> 02:24:57,939
And in this one, I'm just poking a little
fun at.

1721
02:24:57,939 --> 02:25:03,730
It's the number one doctor-recommended brand
because it supports immunity, it boosts your

1722
02:25:03,730 --> 02:25:04,730
immune system.

1723
02:25:04,730 --> 02:25:11,050
These are very weak claims that can't be really
applied to our patients in many cases because

1724
02:25:11,050 --> 02:25:17,450
they're on antibiotics and they're in a damage
control situation.

1725
02:25:17,450 --> 02:25:24,790
So there's a big push to modulate gut microbiomes,
which you can do with a fecal microbiota transplant,

1726
02:25:24,790 --> 02:25:28,090
which in my opinion, is messy and dangerous.

1727
02:25:28,090 --> 02:25:33,370
There are now been reports of drug-resistant
E.coli bacteremia and fatalities with this

1728
02:25:33,370 --> 02:25:38,450
approach in critically ill patients because
we know they have a hyperpermeable gut.

1729
02:25:38,450 --> 02:25:43,240
This idea of a one size fits all capsule has
been proposed.

1730
02:25:43,240 --> 02:25:49,560
Again, it's not unique to the environmental
context, which is highly personalized depending

1731
02:25:49,560 --> 02:25:51,750
on the patient's life history.

1732
02:25:51,750 --> 02:25:55,390
But this is the easiest way, in my opinion,
to do this.

1733
02:25:55,390 --> 02:25:58,370
It's safe and evolutionarily stable.

1734
02:25:58,370 --> 02:26:04,470
And now we know that the gut microbiome plays
a key role in host recovery because there's

1735
02:26:04,470 --> 02:26:10,750
loss and gain of microbiota mutualism, depending
on how the patient fares over the course of

1736
02:26:10,750 --> 02:26:12,279
critical illness.

1737
02:26:12,279 --> 02:26:18,830
And these immuno-regulatory metabolites actually
drive immune cell phenotype transition.

1738
02:26:18,830 --> 02:26:26,520
What you can see is this is a moving target
and we need to promote homeostatic gene expression.

1739
02:26:26,520 --> 02:26:35,189
This crescendo/decrescendo of cytokines, inflammation
is good assuming that it gets dampened and

1740
02:26:35,189 --> 02:26:37,920
attenuated at the appropriate time.

1741
02:26:37,920 --> 02:26:45,609
And the best way to do that is a plant-based
food diet which drives the microbial consortia

1742
02:26:45,609 --> 02:26:52,660
to release these immunoregulatory metabolites
that diffuse systemically and can shift things

1743
02:26:52,660 --> 02:26:54,770
in the right direction.

1744
02:26:54,770 --> 02:27:00,380
And so our hypothesis is that proper interrogation
and modulation of the gut microbiome can drive

1745
02:27:00,380 --> 02:27:07,229
a recovery-directed immune response during
critical illness.

1746
02:27:07,229 --> 02:27:13,891
So critically ill patients need to consume
a plant-based unprocessed food type diet,

1747
02:27:13,891 --> 02:27:20,220
and they need point of care diagnostics to
define or monitor key efficacious endpoints.

1748
02:27:20,220 --> 02:27:24,160
And this is not going to be simple.

1749
02:27:24,160 --> 02:27:29,660
You need to think about the public goods that
need to be present in the microbiome on top

1750
02:27:29,660 --> 02:27:31,990
of those microbiota that need to be present.

1751
02:27:31,990 --> 02:27:36,870
And we have to promote both their stability
and diversity among the community members

1752
02:27:36,870 --> 02:27:39,320
because this is quite complicated.

1753
02:27:39,320 --> 02:27:42,620
It's a living ecosystem.

1754
02:27:42,620 --> 02:27:49,240
Then we have to keep in mind that these chemically
defined sterile liquid products are not this.

1755
02:27:49,240 --> 02:27:54,070
Earth's food evolved over millions of years.

1756
02:27:54,070 --> 02:27:56,729
Patients need to eat this.

1757
02:27:56,729 --> 02:27:58,400
Not this.

1758
02:27:58,400 --> 02:28:00,279
And/or this.

1759
02:28:00,279 --> 02:28:05,480
But in many cases, patients have no choices
because they're no choice, because their bodies

1760
02:28:05,480 --> 02:28:11,550
will not accept the foods that we think they
need to be properly nourished.

1761
02:28:11,550 --> 02:28:17,120
But if we do not properly and repeatedly assess
the microbiome over the course of illness,

1762
02:28:17,120 --> 02:28:22,840
in this case critical illness, we will not
be able to properly modulate its function.

1763
02:28:22,840 --> 02:28:34,660
Again, I want to thank the National Institutes
of Health and the program developers for the

1764
02:28:34,660 --> 02:28:40,332
opportunity to speak to you today. Thank you.

1765
02:28:45,422 --> 02:28:49,270
DR. GAIL CRESCI: Wow, thank you, everyone, for your
excellent presentations.

1766
02:28:49,270 --> 02:28:51,280
What a wealth of information.

1767
02:28:51,280 --> 02:28:57,880
Let's begin our question and answer session
now and while we're going through the questions

1768
02:28:57,880 --> 02:29:04,240
that have already been submitted.

1769
02:29:04,240 --> 02:29:13,149
(AUDIO DISTORTS) Please continue to submit
your questions as they may arise.

1770
02:29:13,149 --> 02:29:22,240
So, for our first question, I'm going to ask
actually everybody on the panel because and

1771
02:29:22,240 --> 02:29:25,330
feel free whoever wants to answer.

1772
02:29:25,330 --> 02:29:32,130
But there was many of the presentations were
about data and critical illness.

1773
02:29:32,130 --> 02:29:36,970
And critically ill patients, as we know, have
a lot of ongoing interventions such as ventilators,

1774
02:29:36,970 --> 02:29:40,479
pressure agents, sedatives, other drugs.

1775
02:29:40,479 --> 02:29:47,890
How do you control for those potential confounding
variables to make sense of the data that's

1776
02:29:47,890 --> 02:29:50,670
being generated?

1777
02:29:50,670 --> 02:30:04,260
GAIL CRESCI: Dr. Alverdi, do you want to?

1778
02:30:04,260 --> 02:30:08,650
DR. JOHN ALVERDI: Oh, sure, yeah. I'll take a
stab at it, thank you.

1779
02:30:08,650 --> 02:30:14,910
You know, as I mentioned in my last slide,
you know, repeat measurements are needed,

1780
02:30:14,910 --> 02:30:18,380
you know, it's the area under the curve, if
you will.

1781
02:30:18,380 --> 02:30:23,110
That's probably going to be important because
as you mentioned, you know, these patients

1782
02:30:23,110 --> 02:30:29,899
are on, and I mentioned, you know, have multiple
interventions, they're are a moving target,

1783
02:30:29,899 --> 02:30:38,270
and we all want this one measurement one-time point of care
measurement to be predictive of the entire

1784
02:30:38,270 --> 02:30:42,710
occurrence course, and outcome, but it can't
be, we're asking too much of it.

1785
02:30:42,710 --> 02:30:50,229
So, I think what we need to do, and I really
enjoyed everybody's presentation, is pick

1786
02:30:50,229 --> 02:30:56,200
a product that we think has a scientific premise
to it.

1787
02:30:56,200 --> 02:31:02,090
And then repeatedly measure over the course
of the patient's illness what the output is,

1788
02:31:02,090 --> 02:31:07,840
you know, we have now, as we heard, gas chromatography
of exhaled gas, we have metabolomics in the

1789
02:31:07,840 --> 02:31:13,560
blood, as Tom Ziegler told us, we have multiple
proteomics, that we can measure.

1790
02:31:13,560 --> 02:31:21,430
There's so much to measure to determine the
efficacy of what we're doing, and that might

1791
02:31:21,430 --> 02:31:26,430
change the next day, but we can repeat the
measurement.

1792
02:31:26,430 --> 02:31:33,000
DR. GAIL CRESCI: Yeah, I think that is really
key is to, you know, it's a continuum, it's

1793
02:31:33,000 --> 02:31:39,840
not just a snapshot of what might be going
on at that particular point in time.

1794
02:31:39,840 --> 02:31:47,729
Another question for everyone is regarding
these emerging tools, and we're getting so

1795
02:31:47,729 --> 02:31:55,229
much valuable data about the patient, their
metabolism, the metabolites they're producing,

1796
02:31:55,229 --> 02:32:03,000
do we envision that these tools will eventually
be able to help identify or stratify our patients,

1797
02:32:03,000 --> 02:32:07,390
that may be likely to respond to nutrition
intervention

1798
02:32:07,390 --> 02:32:14,210
and would this intervention then be able to
be personalized based on these data?

1799
02:32:14,210 --> 02:32:17,960
The metabolomics, the breath analysis, and
the microbiome.

1800
02:32:17,960 --> 02:32:21,710
DR. TOM ZIEGLER: Gail, can you hear me?

1801
02:32:21,710 --> 02:32:25,460
DR. GAIL CRESCI: Yes, I can hear you.

1802
02:32:25,460 --> 02:32:31,880
THOMAS ZIEGLER: Hi Gail, hi everybody, great
presentations everybody it was very interesting.

1803
02:32:31,880 --> 02:32:38,029
This is Tom Ziegler, let me just say, I think
we might be like Law and Order in 10 years,

1804
02:32:38,029 --> 02:32:46,920
we may have a mass spec machine in every ICU
or, you know, on every floor if I could be,

1805
02:32:46,920 --> 02:32:49,550
you know, optimistic or, you know, certainly
more expensive or...

1806
02:32:49,550 --> 02:32:54,899
Well, I think that as these machines that
can measure these fancy things become (LAUGHS)

1807
02:32:54,899 --> 02:33:02,600
less expensive, and more specific, we might
be able to take a drop of blood over time

1808
02:33:02,600 --> 02:33:09,950
from our patients, for example, in the ICU
and, you know, do amino acid grams, you know,

1809
02:33:09,950 --> 02:33:15,990
in five minutes, and be able to tell what
the amino acid situation is in that particular

1810
02:33:15,990 --> 02:33:24,350
day, or we might be able to measure thiamine
metabolites and get a sense of, is the patient

1811
02:33:24,350 --> 02:33:25,870
potentially thiamine deficient?

1812
02:33:25,870 --> 02:33:31,380
I think that this will help us to guide our
therapies in a personalized way going forward.

1813
02:33:31,380 --> 02:33:38,600
You know we're probably less than a decade
off from that, starting to happen obviously,

1814
02:33:38,600 --> 02:33:44,819
we'll need research in these areas, point
of care, if you will, mass spectrometry, is

1815
02:33:44,819 --> 02:33:46,740
one example.

1816
02:33:46,740 --> 02:33:47,740
Thank you.

1817
02:33:47,740 --> 02:33:53,180
DR. DAVID EVANS: Hey, it's Dave Evans, can you
hear me?

1818
02:33:53,180 --> 02:33:57,601
DR. GAIL CRESCI: Yeah, David, we can hear you,
Dr. Evans.

1819
02:33:57,601 --> 02:33:59,203
DAVID EVANS: Yeah, may I just comment?

1820
02:33:59,203 --> 02:34:04,479
I think the one concern is, you know, on the
other side of the spectrum is that you know,

1821
02:34:04,479 --> 02:34:07,960
U.S. healthcare costs are out of control.

1822
02:34:07,960 --> 02:34:14,570
And, you know, we know a lot of very basic,
you know, easy-to-do things right now that

1823
02:34:14,570 --> 02:34:16,319
we're not doing.

1824
02:34:16,319 --> 02:34:23,380
Well, I think that you know, the high-end
research, and I'm really excited about awesome

1825
02:34:23,380 --> 02:34:28,000
presentations, I really enjoyed seeing everything
everybody is doing.

1826
02:34:28,000 --> 02:34:33,330
I think there also needs to be a focus on,
you know, what can we implement practically,

1827
02:34:33,330 --> 02:34:40,100
and affordably, and you know, put it in the
hands of every clinician, and not just, you

1828
02:34:40,100 --> 02:34:43,380
know, the high-end kind of university research-based
ICU?

1829
02:34:43,380 --> 02:34:49,710
And so, you know, I would just, you know,
well, I'm super excited about all these possible

1830
02:34:49,710 --> 02:34:50,710
innovations.

1831
02:34:50,710 --> 02:34:55,979
I think, you know, we can need to continue
investing in you know, education and, you

1832
02:34:55,979 --> 02:35:01,750
know, rolling out the simpler tools, and the
knowledge that we already have because we

1833
02:35:01,750 --> 02:35:07,931
still fail to appropriately screen, and appropriately
optimize, you know, many patients who come

1834
02:35:07,931 --> 02:35:09,000
into our hospitals.

1835
02:35:09,000 --> 02:35:13,840
DR. GAIL CRESCI: Thank you, Dr. Evans.

1836
02:35:13,840 --> 02:35:17,939
Dr. Dweik, did you have a comment you wanted
to add?

1837
02:35:17,939 --> 02:35:22,399
DR. RAED A. DWEIK: Yeah, I can add to that I think
these are all excellent points raised by other

1838
02:35:22,399 --> 02:35:27,420
speakers, but I think, with the promise of
what we are doing, you see the holy grail

1839
02:35:27,420 --> 02:35:32,290
of all of that is the ability to do point
of care testing at the bedside, or in the

1840
02:35:32,290 --> 02:35:34,180
clinic, or in the office.

1841
02:35:34,180 --> 02:35:38,910
And I think hopefully the future developments
would be not really necessarily mass specs

1842
02:35:38,910 --> 02:35:43,730
of the bedside, but new technologies that
can do similar measurements, but they are

1843
02:35:43,730 --> 02:35:45,590
not as complicated as mass specs.

1844
02:35:45,590 --> 02:35:54,189
And I think that hopefully, will be the true
benefit of the kind of work that I heard of,

1845
02:35:54,189 --> 02:35:58,180
and the kind of work that we are doing as
well.

1846
02:35:58,180 --> 02:35:59,180
Thank you.

1847
02:35:59,180 --> 02:36:00,200
DR. JOHN ALVERDI: Yeah, I would only add, I'm
sorry.

1848
02:36:00,200 --> 02:36:01,479
DR. GAIL CRESCI: No, go ahead Dr. Alverdi.

1849
02:36:01,479 --> 02:36:07,140
DR. JOHN ALVERDI: Yeah, I'd only add as a general
surgeon, you know, watching anesthesiology

1850
02:36:07,140 --> 02:36:13,189
evolve over the last 30 years is, you know,
we had this crummy little machine, no pulse

1851
02:36:13,189 --> 02:36:22,040
oximeter, no entitled CO2, no gas analysis,
and it was fine, most patients did fine, but

1852
02:36:22,040 --> 02:36:26,930
you know, when you say most patients, there
should be no outliers.

1853
02:36:26,930 --> 02:36:32,800
And so if you go into a modern operating room
today, you know, there's end-tidal CO2 being

1854
02:36:32,800 --> 02:36:37,820
measured, pulse oximetry being measured, there's
endoscopy to intubate the patient, there's,

1855
02:36:37,820 --> 02:36:44,880
you know, three different inhalational agents,
each of which can be measured, their blood,

1856
02:36:44,880 --> 02:36:48,240
partition coefficients can be measured in
blood, and in exhaled gas.

1857
02:36:48,240 --> 02:36:54,870
I mean, we're in a new era, we drive fancy
cars, we all have, you know, smartphones.

1858
02:36:54,870 --> 02:37:00,181
I think that Tom's point, you know, we're
in a new era where, yeah, you don't need it.

1859
02:37:00,181 --> 02:37:04,979
You could drive a Yugo with a three-speed,
but the fact of the matter is your fancy car

1860
02:37:04,979 --> 02:37:08,689
with the lane changers and your smartphone
and your Bluetooth.

1861
02:37:08,689 --> 02:37:16,100
And so I think it's very difficult to imagine,
you know, not applying these things in point

1862
02:37:16,100 --> 02:37:23,640
of care diagnostics, and being as precise,
and to your point, as personalized as we can be.

1863
02:37:23,640 --> 02:37:28,960
And, you know, it's a good point, not everybody
can afford everything, but it's also a good

1864
02:37:28,960 --> 02:37:31,420
point to say, we can do better.

1865
02:37:31,420 --> 02:37:39,620
DR. GAIL CRESCI: Yeah, I think that all the points
are really well made by all the speakers because

1866
02:37:39,620 --> 02:37:45,180
we're dealing with the current situation we
have, and what do we currently have available?

1867
02:37:45,180 --> 02:37:46,750
And then where's the future?

1868
02:37:46,750 --> 02:37:52,029
And that's really what this workshop is about,
is to help identify where the gaps are, and

1869
02:37:52,029 --> 02:37:55,700
where can future research development come
about.

1870
02:37:55,700 --> 02:38:04,490
And so, I think we have...it seems like we've identified that, and I'm
going to bring up a question that came up

1871
02:38:04,490 --> 02:38:09,050
for Dr. Steiber, related to our current tools.

1872
02:38:09,050 --> 02:38:18,439
So, you discussed with us the data surrounding
the AAIM tool, and there are six suggested

1873
02:38:18,439 --> 02:38:24,750
parameters for that, of which I think the
nutrition-focused physical exam to some extent

1874
02:38:24,750 --> 02:38:26,200
is included in that.

1875
02:38:26,200 --> 02:38:28,720
So, are there any parameters?

1876
02:38:28,720 --> 02:38:34,770
Do you need all of those six parameters to
have the validation or just some of them?

1877
02:38:34,770 --> 02:38:36,029
Can you address that topic?

1878
02:38:36,029 --> 02:38:41,600
DR. ALISON STEIBER: Sure, thanks, Gail. I mean,
I think this is a really interesting conversation

1879
02:38:41,600 --> 02:38:47,729
because we're sort of on the cusp of, yes,
we can do it technically in a lot of these

1880
02:38:47,729 --> 02:38:52,490
cases, and we're on cutting-edge research
for a variety of things.

1881
02:38:52,490 --> 02:38:57,319
But the reality is I completely agree with
the speaker that said, you know, our costs

1882
02:38:57,319 --> 02:38:59,319
are out of control.

1883
02:38:59,319 --> 02:39:05,600
And when we think about access to care, so
many people don't have access to quality care

1884
02:39:05,600 --> 02:39:08,330
in general, but certainly not nutrition care.

1885
02:39:08,330 --> 02:39:15,740
And so what can we do from a very practical
perspective, both within our country, in those

1886
02:39:15,740 --> 02:39:20,240
areas with low resources, and those areas
with high resources?

1887
02:39:20,240 --> 02:39:25,700
The current tool that we have, the AAIM tool
does have six parameters.

1888
02:39:25,700 --> 02:39:29,880
That was derived through a consensus process,
and what we are hoping to do but have not

1889
02:39:29,880 --> 02:39:36,819
yet done, is to really look individually,
and see which of those six parameters most

1890
02:39:36,819 --> 02:39:40,070
strongly contribute to the model, for its
predictive value.

1891
02:39:40,070 --> 02:39:42,101
And we're not constrained, right?

1892
02:39:42,101 --> 02:39:47,439
We have a huge amount of data from this dataset,
and so what we would like to be able to do

1893
02:39:47,439 --> 02:39:48,439
is look and see.

1894
02:39:48,439 --> 02:39:51,370
Are there biochemical parameters that we happen
to have?

1895
02:39:51,370 --> 02:39:57,590
Are there other measures that we can do, is
four parameters equally as strong for prediction

1896
02:39:57,590 --> 02:39:58,590
as six?

1897
02:39:58,590 --> 02:40:00,229
Can we make it simpler?

1898
02:40:00,229 --> 02:40:07,080
Can we make it a better way to predict with
less burden on the patient, and on the practitioner?

1899
02:40:07,080 --> 02:40:11,080
So, we haven't done those analyses yet, but
that's our plan in the future.

1900
02:40:11,080 --> 02:40:19,200
DR. GAIL CRESCI: That's great. So another question
is related to the current method, but futuristic

1901
02:40:19,200 --> 02:40:22,520
as well with the context of inflammation.

1902
02:40:22,520 --> 02:40:30,570
So, we know we're taking into account inflammation
with the current methods. And how does inflammation...has that been...

1903
02:40:30,570 --> 02:40:36,540
it's kind of related to the question I asked
earlier, how do these emerging tools take

1904
02:40:36,540 --> 02:40:37,640
into account inflammation?

1905
02:40:37,640 --> 02:40:44,819
And maybe that, you know, on the continuum
for measurement of these outputs, how do you

1906
02:40:44,819 --> 02:40:49,670
factor that into the equation?

1907
02:40:49,670 --> 02:40:51,811
DR. ALISON STEIBER: Can I just say one thing about
that?

1908
02:40:51,811 --> 02:40:55,649
So, I noticed that a couple
of the speakers did this, and we certainly

1909
02:40:55,649 --> 02:40:56,779
did it in our study as well.

1910
02:40:56,779 --> 02:41:03,700
But when you control for acuity, there is,
you know by some level of a proxy, you're

1911
02:41:03,700 --> 02:41:09,490
able to say, you know, a lot of our disease
acuity impacts inflammation on board with

1912
02:41:09,490 --> 02:41:14,100
the patient, and so by controlling for acuity,
I think we're taking that into account to

1913
02:41:14,100 --> 02:41:15,240
a large degree.

1914
02:41:15,240 --> 02:41:20,620
But I also think in, I think this was mentioned
as well and was a great point about anabolic

1915
02:41:20,620 --> 02:41:26,450
versus catabolic, and how we think about that
from a nutrition perspective, inflammation

1916
02:41:26,450 --> 02:41:28,899
obviously driving a huge amount of catabolism.

1917
02:41:28,899 --> 02:41:33,350
So, I just wanted to throw that out, about
the disease severity.

1918
02:41:33,350 --> 02:41:40,071
DR. GAIL CRESCI: Thank you, and I'm thinking,
you know, in lines with the microbiome, and

1919
02:41:40,071 --> 02:41:47,609
of course, in the context of the critically
ill patient, we know they're inflamed, they've

1920
02:41:47,609 --> 02:41:50,130
got inflammation going on.

1921
02:41:50,130 --> 02:41:55,610
Is there any data to show how that impacts
the microbiome?

1922
02:41:55,610 --> 02:42:00,439
And then as a consequence of that, their metabolism?

1923
02:42:00,439 --> 02:42:04,630
And then the metabolites that may be produced?

1924
02:42:04,630 --> 02:42:18,040
DR. JOHN ALVERDI: Yeah, you know, our group has
shown that specific pro-inflammatory cytokines

1925
02:42:18,040 --> 02:42:27,850
literally activate bacterial virulence circuits,
which then feed back onto the host.

1926
02:42:27,850 --> 02:42:34,600
And so it's a feedforward, feedback system,
it's what I call a bi-directional interchange,

1927
02:42:34,600 --> 02:42:41,120
which is why we say, you know, virulence,
harmfulness, clinical infections, sepsis,

1928
02:42:41,120 --> 02:42:47,319
is neither a property of pathogen or the microbiome
alone or the immune system alone, it's a property

1929
02:42:47,319 --> 02:42:49,240
of their interaction.

1930
02:42:49,240 --> 02:42:55,800
And so when we think about this, we need to
think about this interactome, which is what

1931
02:42:55,800 --> 02:43:00,920
I think all the speakers are trying to say
is at our fingertips.

1932
02:43:00,920 --> 02:43:06,950
When you look at some of the principal component
analyses, or the ordination plots, that Tom

1933
02:43:06,950 --> 02:43:14,779
and others are trying to put together when
you measure 1,350 different or 3,000 different

1934
02:43:14,779 --> 02:43:18,830
metabolites, you have a huge array of data.

1935
02:43:18,830 --> 02:43:25,340
But you've got to harness, and manage, those
data so that they tell you something that's

1936
02:43:25,340 --> 02:43:28,180
what we call actionable.

1937
02:43:28,180 --> 02:43:31,850
Something you can do something about, not
just say, "Well, this went up, this went down,

1938
02:43:31,850 --> 02:43:37,700
this went sideways," you know, it's like gene
arrays, you can't sequence your way to truth.

1939
02:43:37,700 --> 02:43:44,540
You've got to understand how to manage the
data in a big dataset, with bioinformaticists

1940
02:43:44,540 --> 02:43:48,830
who'll tell you, "This finding is actionable."

1941
02:43:48,830 --> 02:43:54,390
And I think therein lies the challenge, which
is why, you know, people who are doing sequencing,

1942
02:43:54,390 --> 02:44:01,540
metabolomics on CSF, blood, urine, exhaled
gas, you're getting a ridiculous amount of

1943
02:44:01,540 --> 02:44:07,010
data that you know, moment-to-moment you need
to deal with.

1944
02:44:07,010 --> 02:44:12,700
And you can understand the complexities, so
when you ask the question, is there a feedforward

1945
02:44:12,700 --> 02:44:14,399
and feedback system?

1946
02:44:14,399 --> 02:44:17,130
It's constantly ongoing.

1947
02:44:17,130 --> 02:44:21,130
And that's why when somebody says, "We have
to contain costs, let's try one-size-fits-all

1948
02:44:21,130 --> 02:44:27,561
for everybody," that's a problem, like, you
know, with antibiotics, and prophylaxis, in

1949
02:44:27,561 --> 02:44:28,561
general surgery.

1950
02:44:28,561 --> 02:44:31,121
We give everybody the same antibiotic, that
can't be right.

1951
02:44:31,121 --> 02:44:36,399
I mean, well, it's right most of the time,
except for the 3% that it's not right, who

1952
02:44:36,399 --> 02:44:37,740
don't do well.

1953
02:44:37,740 --> 02:44:45,510
DR. GAIL CRESCI: Yeah, I agree, I mean, that's
where I was trying to lead, is any of this

1954
02:44:45,510 --> 02:44:52,420
data we're generating helping us to identify
a personalized approach to nutrition to these different

1955
02:44:52,420 --> 02:44:53,420
patient populations?

1956
02:44:53,420 --> 02:44:59,029
Will it inform us on how to feed our patient,
and when to...

1957
02:44:59,029 --> 02:45:02,830
understanding who may respond to a certain
type of feeding?

1958
02:45:02,830 --> 02:45:08,930
So, Dr. Alverdi, you bring up about plant-based
diets, and that they should be provided to

1959
02:45:08,930 --> 02:45:16,510
our critically ill patient, how do we know if
they're going to tolerate these feedings or

1960
02:45:16,510 --> 02:45:17,510
not?

1961
02:45:17,510 --> 02:45:19,290
What are your thoughts on that?

1962
02:45:19,290 --> 02:45:25,670
DR. JOHN ALVERDI: Well, yeah, I mentioned that
in my talk, you know, it's a balance between

1963
02:45:25,670 --> 02:45:31,520
how sick is the patient, and what
will their gut tolerate versus what you should

1964
02:45:31,520 --> 02:45:32,850
put into their gut.

1965
02:45:32,850 --> 02:45:42,020
And you know, I trained a long time ago when
we had a product called Complete B Modify which was

1966
02:45:42,020 --> 02:45:49,840
basically, you know, ultra blenderized real
food, you know, it was meat, potatoes, and

1967
02:45:49,840 --> 02:45:50,840
peas.

1968
02:45:50,840 --> 02:45:54,920
And the nurses complained about it because
the patients had too many bowel movements,

1969
02:45:54,920 --> 02:45:56,569
and their stool smelled.

1970
02:45:56,569 --> 02:46:06,510
Now, we put in sterile, chemically
defined liquid diets, that we go, "It has

1971
02:46:06,510 --> 02:46:08,250
everything you need.

1972
02:46:08,250 --> 02:46:15,260
Trust me." And yet, you know, as I listened
to all the talks today, I'm thinking, boy,

1973
02:46:15,260 --> 02:46:18,210
there's a lot we don't know, that can't be
right.

1974
02:46:18,210 --> 02:46:24,770
Like I said in one of my slides, we evolved
to eat the food that comes out of the ground.

1975
02:46:24,770 --> 02:46:29,140
How is it that when we get sick, we think
we know what to feed patients?

1976
02:46:29,140 --> 02:46:37,010
So, there's a lot to learn yet, and this wonderful
session told us what we can measure to learn

1977
02:46:37,010 --> 02:46:40,810
it better, not just to try, hey, how about
this?

1978
02:46:40,810 --> 02:46:42,070
How about that?

1979
02:46:42,070 --> 02:46:47,771
No, how about giving this, and measuring what
is its response is?

1980
02:46:47,771 --> 02:46:53,850
That's what's so exciting about this field,
and this session, in my opinion.

1981
02:46:53,850 --> 02:47:00,640
DR. GAIL CRESCI: Yes, I think we would all agree
to that, it's really exciting, and where the

1982
02:47:00,640 --> 02:47:07,319
direction hopefully, is going to help inform
us, for our patient care.

1983
02:47:07,319 --> 02:47:17,840
So, I have a question again, this is for David
Evans, and it's regarding that, for surgical

1984
02:47:17,840 --> 02:47:22,951
patients a question came in, have you looked
at other relationships between muscle mass

1985
02:47:22,951 --> 02:47:25,479
and function, and surgical outcomes?

1986
02:47:25,479 --> 02:47:31,890
So, CT measures of muscle mass, the psoas muscle,
mass or density, have you looked at that?

1987
02:47:31,890 --> 02:47:36,740
And what about functional measures for lactate
clearance?

1988
02:47:36,740 --> 02:47:41,979
Because there was a paper that shows time
stair climb actually are the best predictors.

1989
02:47:41,979 --> 02:47:48,641
DR. DAVID EVANS: Yeah, well, thanks for that, and
you know, I really just to echo on everybody

1990
02:47:48,641 --> 02:47:55,020
else, you know, I still think there's incredible
potential for personalized medicine.

1991
02:47:55,020 --> 02:48:01,930
I certainly didn't mean my comment to not
imply that, it's just that I think that perhaps,

1992
02:48:01,930 --> 02:48:07,561
more than in some other areas in medicine
we haven't gotten the basics right yet; we

1993
02:48:07,561 --> 02:48:08,561
haven't gotten the simple stuff.

1994
02:48:08,561 --> 02:48:13,560
And I think your question is actually a really
good example of that, because, you know, in

1995
02:48:13,560 --> 02:48:20,780
my research, we've spent a lot of time, and
thought, on muscle mass measures,

1996
02:48:20,780 --> 02:48:24,069
we looked at, you know, CT scans, and first,
we were looking at mass, and then we were

1997
02:48:24,069 --> 02:48:26,270
looking at psoas density.

1998
02:48:26,270 --> 02:48:34,120
And...I mean, actually, just in the last year or
so, you know, a lot of that has kind of been

1999
02:48:34,120 --> 02:48:35,120
blown out of the water.

2000
02:48:35,120 --> 02:48:38,850
We saw a paper published in the Annals of
Surgery, I think, in the last year, that's

2001
02:48:38,850 --> 02:48:46,560
the one that they were referencing, that showed
that timed stair climb is actually a better

2002
02:48:46,560 --> 02:48:48,700
predictor of surgical outcomes.

2003
02:48:48,700 --> 02:48:54,270
Of course, this is, you know, surgical patients,
it's not ICU patients where the injuries already

2004
02:48:54,270 --> 02:48:58,080
happened, but pre-operatively, that having
a patient go down a flight of stairs, and

2005
02:48:58,080 --> 02:49:02,081
up a flight of stairs, and timing how fast
they can do that, which kind of gives you

2006
02:49:02,081 --> 02:49:06,630
this global assessment of muscle mass, muscle
function, coordination.

2007
02:49:06,630 --> 02:49:16,130
Clearly, it's not just a nutritional measure,
but that outperformed any of our kind of analytical

2008
02:49:16,130 --> 02:49:23,310
assessments of muscle and, you know, lactate
clearance, you mentioned that too, you know,

2009
02:49:23,310 --> 02:49:29,061
we have data kind of trying to get at that
question about muscle function, about how

2010
02:49:29,061 --> 02:49:30,720
fast a patient can trigger lactate.

2011
02:49:30,720 --> 02:49:36,350
And of course, we know that like a well-trained
athlete can clear lactate faster than a poorly

2012
02:49:36,350 --> 02:49:37,630
trained athlete, for example, and that often
sets athletes apart.

2013
02:49:37,630 --> 02:49:46,670
Well, the same is true in clinical medicine,
but at the end of the day, the time stair

2014
02:49:46,670 --> 02:49:49,770
climb has actually outperformed almost every
tool.

2015
02:49:49,770 --> 02:49:54,051
Now, we haven't gotten to, you know, take
it to like Dr. Ziegler or, you know, some

2016
02:49:54,051 --> 02:49:57,720
of these other labs to see if that data would
be superior.

2017
02:49:57,720 --> 02:50:04,779
But certainly, in terms of things that we
can do today in our office, we still have

2018
02:50:04,779 --> 02:50:09,350
a lot of opportunities that we're not taking
advantage of, thank you.

2019
02:50:09,350 --> 02:50:17,890
DR. GAIL CRESCI: Yeah, because that's a really
good point, you know, that's more of a practical

2020
02:50:17,890 --> 02:50:23,859
outcome too for the patient that, you know,
we talk about frailty index and you know,

2021
02:50:23,859 --> 02:50:29,520
just being able to get back to their activities
of daily living, and the impact of nutrition

2022
02:50:29,520 --> 02:50:34,730
on that, is that a better outcome to perhaps
look at?

2023
02:50:34,730 --> 02:50:40,660
But we did have a question that came in regarding,
you know because we've been talking mostly

2024
02:50:40,660 --> 02:50:45,660
about inpatients' critical illness, but there
was a question about, what are the best parameters

2025
02:50:45,660 --> 02:50:49,609
to assess nutritional status amongst outpatients
with disease?

2026
02:50:49,609 --> 02:50:57,410
And is this still left to weight loss over
the past six months, or looking at BMI?

2027
02:50:57,410 --> 02:51:04,710
That's for everyone, everyone might like want to
look at that question.

2028
02:51:04,710 --> 02:51:08,290
DR. THOMAS ZIEGLER: Can I just make a comment
about BMI?

2029
02:51:08,290 --> 02:51:10,170
Can you hear me, Gail?

2030
02:51:10,170 --> 02:51:12,800
DR. GAIL CRESCI: Yes, I can hear you.

2031
02:51:12,800 --> 02:51:19,420
DR. THOMAS ZIEGLER: You know, so the thing about
BMI, you know, the data getting, I mean, the

2032
02:51:19,420 --> 02:51:26,609
data, it's really becoming quite clear that
BMI is a very, you know, crude measurement.

2033
02:51:26,609 --> 02:51:32,109
And we need better, for example, there is
something called normal-weight obesity where

2034
02:51:32,109 --> 02:51:36,950
someone walks into the office with a normal
BMI of 23, but they have an excessive body

2035
02:51:36,950 --> 02:51:37,950
fat mass.

2036
02:51:37,950 --> 02:51:43,640
And normal-weight obesity we've defined in
cystic fibrosis, and others have defined it,

2037
02:51:43,640 --> 02:51:49,830
is really associated with coronary artery,
and other outcomes.

2038
02:51:49,830 --> 02:51:54,610
But as you know, we just definitely need better
markers of body composition.

2039
02:51:54,610 --> 02:52:02,130
We need to measure body composition in everybody
as best we can, even if it's DEXA or some

2040
02:52:02,130 --> 02:52:08,850
of the methods that Dr. Earthman talked about
earlier, and get away from BMI.

2041
02:52:08,850 --> 02:52:16,239
If we can, according to cost, I really like
what John said about, you know, (LAUGHS) I

2042
02:52:16,239 --> 02:52:21,109
mean, we could use a flip phone, although
flip phones are back, I guess, or we could

2043
02:52:21,109 --> 02:52:27,359
use an iPhone, and yeah, it's more expensive
but if you look at all the money being spent

2044
02:52:27,359 --> 02:52:32,770
in any typical ICU, or even a hospital floor,
if anybody's been in the hospital lately,

2045
02:52:32,770 --> 02:52:34,430
and you get the hospital bill, it's ridiculous.

2046
02:52:34,430 --> 02:52:39,479
And so, you know, I think we need to take
advantage of higher-tech instrumentation,

2047
02:52:39,479 --> 02:52:42,630
and stuff, particularly to look at clinical
outcomes.

2048
02:52:42,630 --> 02:52:48,500
And that could include metabolomics, breath
tests, gut microbiome, all that, but I just

2049
02:52:48,500 --> 02:52:56,689
think we need to move forward past BMI, and
as was said in the first talk, prealbumin,

2050
02:52:56,689 --> 02:52:59,330
and albumin measures.

2051
02:52:59,330 --> 02:53:06,220
DR. GAIL CRESCI: Yeah, and perhaps I don't know
what you think, Dr. Dweik, regarding the volatile

2052
02:53:06,220 --> 02:53:11,271
organic compounds in the inpatient versus
outpatient setting.

2053
02:53:11,271 --> 02:53:12,770
Do you have any thoughts on that?

2054
02:53:12,770 --> 02:53:18,310
You've done a lot of work in a lot of different
disease states showing a correlation with

2055
02:53:18,310 --> 02:53:22,350
that, what are your thoughts on that as far
as assessing for nutrition, and nutrition

2056
02:53:22,350 --> 02:53:23,350
intervention?

2057
02:53:23,350 --> 02:53:28,880
DR. RAED A. DWEIK: Yeah, thank you for asking,
so definitely, you know, breath analysis allows,

2058
02:53:28,880 --> 02:53:32,370
lends itself to be done in both settings, the
inpatient and the outpatient.

2059
02:53:32,370 --> 02:53:36,591
You know, I think the future, of course, if
you have a point of care test, it'll be even

2060
02:53:36,591 --> 02:53:42,649
in other locations, like in the field, or
in low-resource areas, similar to the breathalyzer

2061
02:53:42,649 --> 02:53:43,649
for alcohol.

2062
02:53:43,649 --> 02:53:48,400
So, the complication with the inpatient is
similar to the questions that were raised

2063
02:53:48,400 --> 02:53:53,300
earlier, the clinical illness, there are so
many confounding variables, and that becomes

2064
02:53:53,300 --> 02:53:54,300
a lot more complicated.

2065
02:53:54,300 --> 02:53:58,640
And I think it's true for breath analysis
as it's true for other metabolic testing is

2066
02:53:58,640 --> 02:54:02,960
that these patients are on so many confounding
interventions that may difficult.

2067
02:54:02,960 --> 02:54:07,360
I think that outpatients are kind of simpler
in a way, they still have the confounding

2068
02:54:07,360 --> 02:54:11,500
variables, but they are easier to control
than the inpatient setting.

2069
02:54:11,500 --> 02:54:16,069
But definitely, breath testing can be done
in both settings, and beyond that as well.

2070
02:54:16,069 --> 02:54:23,200
DR. GAIL CRESCI: Thank you for that, well, we
have run out of time, we had such a robust

2071
02:54:23,200 --> 02:54:29,229
list of questions submitted to us, and I thank
everyone for their questions.

2072
02:54:29,229 --> 02:54:36,640
Unfortunately, we didn't get to all of them
and Dr. William Evans was unable to join us.

2073
02:54:36,640 --> 02:54:42,380
So, for any of the speakers, if you have any
further insight, or you want insight, you

2074
02:54:42,380 --> 02:54:52,080
can write to nutritionresearch@nih.gov with
your questions, and we will try to get those

2075
02:54:52,080 --> 02:54:53,311
addressed.

2076
02:54:53,311 --> 02:55:00,960
Again, I wanna thank our stellar speakers,
this was really an exciting event today, I

2077
02:55:00,960 --> 02:55:09,500
really enjoyed this interaction that we had,
and identification of clinical gaps, and potential

2078
02:55:09,500 --> 02:55:11,569
future research opportunities.

2079
02:55:11,569 --> 02:55:18,380
So, now we're going to take a quick break
before joining Dr. Steiber for Session 4

2080
02:55:18,380 --> 02:55:21,479
which will begin at 3:20 ET.

2081
02:55:21,479 --> 02:55:23,390
Thank you.

2082
02:55:23,390 --> 02:55:29,890
DR. ALISON STEIBER: Welcome to the session four,
which is on implementation challenges and

2083
02:55:29,890 --> 02:55:34,600
case examples, addressing malnutrition and
reducing health disparities.

2084
02:55:34,600 --> 02:55:39,130
I'm Dr. Alison Steiber and I'll be your moderator
for this session.

2085
02:55:39,130 --> 02:55:44,550
So for this session, I'd like to just walk
you through the agenda about what to expect.

2086
02:55:44,550 --> 02:55:50,399
We'll begin with a talk by Dr. Mirtallo, who
will address supply chain shortages.

2087
02:55:50,399 --> 02:55:56,689
Then we will move on to Dr. Mechanick, who
will discuss dual burden of overweight, obesity

2088
02:55:56,689 --> 02:55:57,689
and malnutrition.

2089
02:55:57,689 --> 02:56:03,439
We will then hear a talk by Dr. Newberry on
malabsorptive and small bowel disorders.

2090
02:56:03,439 --> 02:56:09,700
And on to Dr. Patel for ICU nutrition, moving
beyond support.

2091
02:56:09,700 --> 02:56:13,550
To Dr. Seres, Dementia and enteral feeding
needs.

2092
02:56:13,550 --> 02:56:18,880
And then to Dr. McMacken Nutrition and Lifestyle
Medicine Services.

2093
02:56:18,880 --> 02:56:25,510
And finally, we will end with a robust discussion
on quality question and answers.

2094
02:56:25,510 --> 02:56:32,130
And so we hope that you will take a few minutes
and put your questions in the Q&A box.

2095
02:56:32,130 --> 02:56:37,840
And that way, we can address as many of them
as possible during the Q&A session.

2096
02:56:37,840 --> 02:56:41,130
So with that, thank you very much.

2097
02:56:41,130 --> 02:56:46,580
DR. JAY MIRTALLO: Hello, my name is Jay Mirtallo.

2098
02:56:46,580 --> 02:56:51,020
I am a Clinical Practice Specialist of the
American Society for Parenteral and Enteral

2099
02:56:51,020 --> 02:56:55,200
Nutrition and Professor Emeritus at The Ohio
State University College of Pharmacy.

2100
02:56:55,200 --> 02:57:00,450
It's my pleasure to present to you the topic
of problems related to shortages.

2101
02:57:00,450 --> 02:57:08,160
To get started, I wanted to show you a picture
of the supply chain.

2102
02:57:08,160 --> 02:57:10,630
This is for drugs available from the FDA.

2103
02:57:10,630 --> 02:57:16,420
Just to show you the complexity of what it
takes to take a raw product, over on the left-hand

2104
02:57:16,420 --> 02:57:22,880
side of the slide, going to the final product
that's in a form that can be a nutrition,

2105
02:57:22,880 --> 02:57:27,109
nutritional product that can be administered
to patients to manage malnutrition.

2106
02:57:27,109 --> 02:57:31,340
You can see there's a number of different
reasons why there is problems for the supply

2107
02:57:31,340 --> 02:57:36,220
chain that I've highlighted in red here that
can happen at any one particular point in

2108
02:57:36,220 --> 02:57:37,220
time.

2109
02:57:37,220 --> 02:57:42,500
The main point to make is our supply chain
for nutrients is vulnerable and prone to shortages

2110
02:57:42,500 --> 02:57:46,029
over long periods of time.

2111
02:57:46,029 --> 02:57:52,890
Provided an example, these are the parental
nutrition shortages we were dealing with in

2112
02:57:52,890 --> 02:57:55,939
ASPEN during 2010.

2113
02:57:55,939 --> 02:58:00,250
If you look at the nutrients, it pretty much
includes all of the nutrients that we need

2114
02:58:00,250 --> 02:58:03,000
in our body at any point in time.

2115
02:58:03,000 --> 02:58:10,080
Now, I noted 2010 most because since that
time we have still continued to have shortages

2116
02:58:10,080 --> 02:58:12,590
at any one time for any one of these products.

2117
02:58:12,590 --> 02:58:18,550
They haven't really gone away and it might
be for a different products, but also we've

2118
02:58:18,550 --> 02:58:24,220
seen an extension of these shortages to include
both enteral nutrition as well, which would

2119
02:58:24,220 --> 02:58:30,080
be the specialty infant formulas that have
been struggling with regards to making them

2120
02:58:30,080 --> 02:58:32,330
available to that population.

2121
02:58:32,330 --> 02:58:38,330
We've also seen shortages of just the ability
to infuse these products since with our nutrition

2122
02:58:38,330 --> 02:58:41,430
you need some kind of device to infuse it.

2123
02:58:41,430 --> 02:58:46,750
And so we've seen shortages also occurring
with pumps, infusion pumps, we've seen them

2124
02:58:46,750 --> 02:58:51,760
with IV filters, we've seen them even with
the products that are needed to make these

2125
02:58:51,760 --> 02:58:54,170
products in the pharmacy.

2126
02:58:54,170 --> 02:59:02,080
So we've really had critical issues with regards
to making sure we have an adequate supply.

2127
02:59:02,080 --> 02:59:06,950
These are examples of problems that result
from shortages because clinicians are exposed

2128
02:59:06,950 --> 02:59:09,810
to less desirable or unfamiliar products.

2129
02:59:09,810 --> 02:59:17,939
There could be errors with regards to prescribing,
such as omission of the product or a provision

2130
02:59:17,939 --> 02:59:20,360
of an overdosage for the product.

2131
02:59:20,360 --> 02:59:26,100
With bringing new products into the organization
that people aren't familiar with, there's

2132
02:59:26,100 --> 02:59:31,601
confusion on how to prescribe due to the substitution
as other systems issues related to compounding

2133
02:59:31,601 --> 02:59:33,649
and distribution of workarounds.

2134
02:59:33,649 --> 02:59:37,870
All of these are systems issues that need
process improvement efforts, education of

2135
02:59:37,870 --> 02:59:42,610
staff, as well as clinicians that need to
purchase the products in order to avoid clinical

2136
02:59:42,610 --> 02:59:47,540
issues in the patients.

2137
02:59:47,540 --> 02:59:52,359
But the real problems with the shortages really
comes from the fact that we don't have enough

2138
02:59:52,359 --> 02:59:57,170
nutrients available to provide all the patients
that it would be prescribed for, that have

2139
02:59:57,170 --> 02:59:58,230
the need.

2140
02:59:58,230 --> 03:00:04,200
So because of a shortage, we need to develop
some sort of rules for constraining this inadequate

2141
03:00:04,200 --> 03:00:10,020
supply and those things that we need to do
in order to identify which patients that this

2142
03:00:10,020 --> 03:00:12,010
is going to apply to.

2143
03:00:12,010 --> 03:00:16,320
And so we really are looking at identifying
risk in this patient population and in this

2144
03:00:16,320 --> 03:00:18,061
case, a risk of deficiency.

2145
03:00:18,061 --> 03:00:24,930
If a patient has little or no risk, they may
just omit the product from a patient and monitor

2146
03:00:24,930 --> 03:00:27,649
closely to make sure a deficiency doesn't
occur.

2147
03:00:27,649 --> 03:00:32,399
If they have a little risk, they might just
reduce the dose again, monitor more closely

2148
03:00:32,399 --> 03:00:34,580
to see if the deficiency would occur.

2149
03:00:34,580 --> 03:00:39,710
But if those patients are at high risk or
already have a deficiency, they'll be required

2150
03:00:39,710 --> 03:00:40,710
to have a full dose.

2151
03:00:40,710 --> 03:00:44,210
And we hope we have enough of the product
to be able to do that for the patients we

2152
03:00:44,210 --> 03:00:47,229
really believe are at the highest risk.

2153
03:00:47,229 --> 03:00:51,790
Now, any other things that can happen is or
we can use diet modification or maybe oral

2154
03:00:51,790 --> 03:00:57,710
supplements if possible. The "if possible" is if
they're available or if they're tolerated

2155
03:00:57,710 --> 03:00:59,080
by the patients.

2156
03:00:59,080 --> 03:01:04,819
But the main thing is because of these issues,
we have a predisposition to nutrient deficiencies

2157
03:01:04,819 --> 03:01:11,700
and an increased need for monitoring for our
patient population.

2158
03:01:11,700 --> 03:01:12,700
On the next few slides.

2159
03:01:12,700 --> 03:01:16,660
I want to provide some examples of clinical
issues related to shortages, starting here

2160
03:01:16,660 --> 03:01:18,540
with macronutrients.

2161
03:01:18,540 --> 03:01:22,689
Looking at Amino Acids, Lipid Injectable emulsions,
and L-cysteine.

2162
03:01:22,689 --> 03:01:27,689
Looking at contaminated PN causing infection
and death, fluid overload, hyperglycemia,

2163
03:01:27,689 --> 03:01:31,489
when use of glucose as a calorie source instead
of fat.

2164
03:01:31,489 --> 03:01:36,979
And then last is an inability to provide adequate
doses of calcium and phosphorus for neonates,

2165
03:01:36,979 --> 03:01:42,770
which could be a problem that cause permanent
problems in that population.

2166
03:01:42,770 --> 03:01:43,770
We have electrolytes.

2167
03:01:43,770 --> 03:01:48,580
One of the issues here we have here with electrolytes
is diarrhea that's caused by an oral electrolyte

2168
03:01:48,580 --> 03:01:49,580
supplement.

2169
03:01:49,580 --> 03:01:55,100
So all oral doses of drugs, per se, are not
tolerated very well by patients that have

2170
03:01:55,100 --> 03:01:59,200
gastrointestinal disorders that require enteral
or parental nutrition.

2171
03:01:59,200 --> 03:02:07,080
Vitamins have always been an issue with parental
nutrition, and we have had in the past deaths

2172
03:02:07,080 --> 03:02:12,640
that have been attributed to thiamin deficiency
because of multi-vitamin shortages in our

2173
03:02:12,640 --> 03:02:17,570
patient population and not understanding how we
need to be able to constrain the supply so

2174
03:02:17,570 --> 03:02:20,109
those high-risk patients receive therapy.

2175
03:02:20,109 --> 03:02:28,880
I wanted to note this slide, just note that
the clinical issues related to nutrient deficiencies

2176
03:02:28,880 --> 03:02:30,470
are not age dependent.

2177
03:02:30,470 --> 03:02:36,750
Anybody at any age that has a gastrointestinal
disorder and has had poor nutrition up until

2178
03:02:36,750 --> 03:02:41,370
the point that they're receiving parental
nutrition or enteral nutrition are going to

2179
03:02:41,370 --> 03:02:43,170
be at risk for nutrient deficiencies.

2180
03:02:43,170 --> 03:02:51,200
And so you can see this for a copper, 62-year-old,
versus selenium, 2-year-old, and thiamine,

2181
03:02:51,200 --> 03:02:52,779
a 16-year-old.

2182
03:02:52,779 --> 03:02:59,000
So hopefully what this information provides
you is that we have a vulnerable nutrition

2183
03:02:59,000 --> 03:03:00,000
support population.

2184
03:03:00,000 --> 03:03:04,840
They have gastrointestinal dysfunction and
oral/intestinal failure.

2185
03:03:04,840 --> 03:03:09,940
That is, the inability to maintain normal
nutritional status on an oral diet or nutritional

2186
03:03:09,940 --> 03:03:13,070
needs are altered due to disease.

2187
03:03:13,070 --> 03:03:17,420
And that means that normal nutrition if you
try to provide it to them to keep their nutritional

2188
03:03:17,420 --> 03:03:23,540
status adequate, is poorly tolerated or
could exacerbate the underlying gastrointestinal

2189
03:03:23,540 --> 03:03:35,250
disorder and require hospitalization or other
acute care medical therapy as a result.

2190
03:03:35,250 --> 03:03:39,900
I'd like to tie this together by bringing
in the patient perspective.

2191
03:03:39,900 --> 03:03:44,760
This is a statement that was submitted by
a parent writing to their congressman to support

2192
03:03:44,760 --> 03:03:49,640
a bill to preserve medications at that time.

2193
03:03:49,640 --> 03:03:54,010
This was on behalf of their nine-year-old
son who could not receive intravenous calcium

2194
03:03:54,010 --> 03:03:58,540
in his approach to nutrition and subsequently
developed complications from oral calcium

2195
03:03:58,540 --> 03:03:59,540
therapy.

2196
03:03:59,540 --> 03:04:05,439
She stated, "Imagine knowing your child needs
vitamins, vitamins, and there is none available

2197
03:04:05,439 --> 03:04:09,899
to give him knowing this will cause a decline
in his health and well-being and you have

2198
03:04:09,899 --> 03:04:21,950
to, in essence, watch your child starve because
in this great country there are drug shortages."

2199
03:04:21,950 --> 03:04:25,840
So this brings me to what I consider to be
the knowledge gaps or areas that we can really

2200
03:04:25,840 --> 03:04:33,130
start asking questions to research in order
to help us do better for our patient population,

2201
03:04:33,130 --> 03:04:36,120
because shortages are always going to be there.

2202
03:04:36,120 --> 03:04:41,660
The first question I have is how is nutrition
or nutrient risk of the patient identified?

2203
03:04:41,660 --> 03:04:47,489
Or specifically, how can we more accurately
assign a patient to no, reduced, or full dose

2204
03:04:47,489 --> 03:04:52,410
of a nutrient when supply must be constrained
due to shortages?

2205
03:04:52,410 --> 03:04:57,439
And this, I think, ties into one of the issues
we have in just nutrition in general.

2206
03:04:57,439 --> 03:05:02,061
You know, what are the best and most reliable
methods for determining the presence and severity

2207
03:05:02,061 --> 03:05:08,780
of malnutrition in a timely manner available
across all healthcare settings?

2208
03:05:08,780 --> 03:05:12,690
Second is what is the best and most reliable
method for determining the micronutrient status

2209
03:05:12,690 --> 03:05:17,000
of a patient in a timely manner available
across all health care settings?

2210
03:05:17,000 --> 03:05:21,150
And the main points I want to make is when
we look at these deficiencies we have seen

2211
03:05:21,150 --> 03:05:26,460
in this population, that that's actually a
great population to study because you have

2212
03:05:26,460 --> 03:05:31,850
controlled doses of nutrients that are being
provided and it's kind of like you've got

2213
03:05:31,850 --> 03:05:37,500
a placebo effect and those individuals that
aren't receiving any kind of nutrients and

2214
03:05:37,500 --> 03:05:42,550
in addition to the patients that are receiving
full nutrition, but we've had a number of

2215
03:05:42,550 --> 03:05:48,820
years big issues with regards to being able
to get the diagnosis of our patients in a

2216
03:05:48,820 --> 03:05:56,960
reliable manner before it causes clinical
problems that cause either temporary, permanent

2217
03:05:56,960 --> 03:06:04,170
nutritional deficits, or death in a patient
population.

2218
03:06:04,170 --> 03:06:08,800
I know we're going to have more questions
related to this in the future.

2219
03:06:08,800 --> 03:06:12,189
I think this ties in probably to some of the
other discussions that have come up already

2220
03:06:12,189 --> 03:06:13,601
previously related to this.

2221
03:06:13,601 --> 03:06:18,529
But with this population, these I think are
the major focuses that we should have with

2222
03:06:18,529 --> 03:06:24,160
regards to being able to come up with information
that we can provide better decisions that

2223
03:06:24,160 --> 03:06:30,060
protect our patients and can manage them clinically
so they don't have to suffer as a result of

2224
03:06:30,060 --> 03:06:31,590
shortages.

2225
03:06:31,590 --> 03:06:38,940
These are the references that I've used, and
I really look forward to hearing the discussion

2226
03:06:38,940 --> 03:06:40,649
on this topic.

2227
03:06:40,649 --> 03:06:46,460
DR. JEFFREY MECHANICK: Hello, this is Jeff Mechanick.

2228
03:06:46,460 --> 03:06:52,939
I'm pleased to speak to you today on the dual
burden of overweight, obesity and malnutrition,

2229
03:06:52,939 --> 03:07:00,590
a transculturalized driver-based chronic disease
modeling and real-world implementation tactics

2230
03:07:00,590 --> 03:07:01,910
approach.

2231
03:07:01,910 --> 03:07:05,609
Here are my disclosures.

2232
03:07:05,609 --> 03:07:08,340
And let's go through an outline.

2233
03:07:08,340 --> 03:07:10,460
We begin with what the question is.

2234
03:07:10,460 --> 03:07:16,870
Then we're going to move into theoretical
modeling of driver-based chronic diseases,

2235
03:07:16,870 --> 03:07:19,360
particularly overweight obesity and malnutrition.

2236
03:07:19,360 --> 03:07:26,080
Well, then move into epidemiology - present
just a few studies, mechanisms, preventive

2237
03:07:26,080 --> 03:07:32,230
care strategies, implementation tactics, and
then a conclusion.

2238
03:07:32,230 --> 03:07:33,480
What's the question?

2239
03:07:33,480 --> 03:07:40,689
Well, is there a connection between obesity
and malnutrition that impacts clinical burden?

2240
03:07:40,689 --> 03:07:48,689
Now, the implication of this is to reinterpret
obesity within a novel, robust theoretical

2241
03:07:48,689 --> 03:07:55,211
model, particularly one that includes aspects
of cardiometabolic risk, malnutrition, chronic

2242
03:07:55,211 --> 03:07:57,899
disease and preventive care.

2243
03:07:57,899 --> 03:08:03,271
Let's now look at driver-based chronic disease
models.

2244
03:08:03,271 --> 03:08:10,310
Now, the purpose of devising these models
or these constructs is to expose early and

2245
03:08:10,310 --> 03:08:17,020
sustainable opportunities for preventive care
in the natural history of chronic disease

2246
03:08:17,020 --> 03:08:22,040
in order to reduce clinical and, in fact,
economic burdens as well.

2247
03:08:22,040 --> 03:08:24,550
Let's look at the structure, there's three
dimensions.

2248
03:08:24,550 --> 03:08:33,590
The first dimension is stage progression over
time, and the map prevention type. Risk

2249
03:08:33,590 --> 03:08:40,029
would be primordial prevention, to prevent
disease primary prevention, to prevent progression

2250
03:08:40,029 --> 03:08:46,760
of disease secondary, and to prevent complications
and the impact of complications on suffering

2251
03:08:46,760 --> 03:08:49,700
and mortality, that's tertiary prevention.

2252
03:08:49,700 --> 03:08:54,470
The second dimension is to look at the key
mechanistic drivers.

2253
03:08:54,470 --> 03:09:01,270
This is networking, causation, and then from
a clinical standpoint, to prioritize these.

2254
03:09:01,270 --> 03:09:08,290
The third dimension is the social determinants
of health and also the transcultural factors.

2255
03:09:08,290 --> 03:09:16,640
Now examples of these models pertain to adiposity,
dysglycemia, hypertension, lipids, cardiometabolic

2256
03:09:16,640 --> 03:09:21,270
risk, and, of course, malnutrition.

2257
03:09:21,270 --> 03:09:22,390
How did this all start?

2258
03:09:22,390 --> 03:09:28,189
Well, we wrote a paper for the Journal of
the American College of Cardiology back in

2259
03:09:28,189 --> 03:09:35,279
2016, and we looked at the networking effects
of adipokines, cardiovascular system, and the

2260
03:09:35,279 --> 03:09:37,859
impact of lifestyle medicine.

2261
03:09:37,859 --> 03:09:43,080
And what we found is really this complexity
that really needed to be teased out.

2262
03:09:43,080 --> 03:09:49,500
You can see here in the yellow highlighted
boxes are small world phenomenon of diet and

2263
03:09:49,500 --> 03:09:52,430
obesity within this network.

2264
03:09:52,430 --> 03:09:58,390
And that inspired us to then come up with
these models, the first on the top left for

2265
03:09:58,390 --> 03:10:04,630
abnormal adiposity rather than just dwelling
on amount or BMI to also look at abnormal

2266
03:10:04,630 --> 03:10:05,630
distribution.

2267
03:10:05,630 --> 03:10:07,979
That would be a topic fat, right?

2268
03:10:07,979 --> 03:10:14,770
And also abnormal function looking at various
levels or indicators of inflammation, then

2269
03:10:14,770 --> 03:10:21,670
interpreting them through the lens of context,
physical and non-physical world culture, and

2270
03:10:21,670 --> 03:10:24,690
you come up with the burden of disease.

2271
03:10:24,690 --> 03:10:31,630
Our next paper was looking at dysglycemia
and in this paper, we actually were able to

2272
03:10:31,630 --> 03:10:36,290
configure this stage progression over time,
four stages.

2273
03:10:36,290 --> 03:10:42,180
Stage one: risk, Stage two: pre-disease, Stage three: disease, Stage four: complications.

2274
03:10:42,180 --> 03:10:48,430
And here we're actually merging together insulin
resistance, pre-diabetes, type 2 diabetes

2275
03:10:48,430 --> 03:10:51,489
and diabetes vascular complications.

2276
03:10:51,489 --> 03:10:55,450
On the right side, you can see we pulled the
drivers together, that's second dimension,

2277
03:10:55,450 --> 03:10:59,700
and we get cardiometabolic based chronic disease.

2278
03:10:59,700 --> 03:11:06,600
Essentially looking at these key drivers of
abnormal adiposity, A, B, C, D, dysglycemia

2279
03:11:06,600 --> 03:11:13,680
DBCD on various forms of cardiovascular disease
or cardiometabolic based chronic disease.

2280
03:11:13,680 --> 03:11:20,660
And these models form the context in order
to interpret this interaction between malnutrition

2281
03:11:20,660 --> 03:11:23,050
and obesity.

2282
03:11:23,050 --> 03:11:28,310
If we evolve this model even further, we start
to introduce a third dimension.

2283
03:11:28,310 --> 03:11:34,341
If you look at the two-by-two matrix of time
versus driver on that right side, you can

2284
03:11:34,341 --> 03:11:40,660
see for each cell you could transculturalize
or find social determinants that modulate

2285
03:11:40,660 --> 03:11:47,550
the phenotype, modulate the way in which you
can more precisely introduce an intervention

2286
03:11:47,550 --> 03:11:53,130
in this model for a cardiometabolic based
chronic disease.

2287
03:11:53,130 --> 03:12:00,950
Now let's look at how a chronic disease model
for adiposity, ABCD on the left, interacts with

2288
03:12:00,950 --> 03:12:02,779
the chronic disease model for malnutrition.

2289
03:12:02,779 --> 03:12:09,149
You have the same primary drivers, genetics,
environment, and behavior, all interacting

2290
03:12:09,149 --> 03:12:13,479
to create a particular lifestyle which could
be healthy or unhealthy.

2291
03:12:13,479 --> 03:12:20,279
And then if you look at the particular drivers,
there are interactions among diet, metabolism,

2292
03:12:20,279 --> 03:12:23,521
energy balance, and adiposity.

2293
03:12:23,521 --> 03:12:30,100
And then ultimately what happens is you have
different stages and you can codify where

2294
03:12:30,100 --> 03:12:33,770
you are in this particular chronic disease
by the stage.

2295
03:12:33,770 --> 03:12:39,479
So for instance, stage two ABCD is what we
commonly referred to as overweight.

2296
03:12:39,479 --> 03:12:41,830
Stage three would be obesity.

2297
03:12:41,830 --> 03:12:49,570
For the MBCD or malnutrition model, stage
three would be malnutrition-fulfilling criteria.

2298
03:12:49,570 --> 03:12:56,110
Now, stage two might still have some abnormal
descriptors of nutritional risk, nutritional

2299
03:12:56,110 --> 03:13:02,810
status, but not formally meeting the diagnostic
criteria that may find in various societies

2300
03:13:02,810 --> 03:13:04,061
like ASPEN.

2301
03:13:04,061 --> 03:13:12,840
And then together they merge and you can configure
a preventive and lifestyle medicine type of

2302
03:13:12,840 --> 03:13:15,670
management.

2303
03:13:15,670 --> 03:13:17,489
So let's look at the epidemiology.

2304
03:13:17,489 --> 03:13:20,439
Let's look at the scientific substantiation
for these models.

2305
03:13:20,439 --> 03:13:22,529
I just picked four studies here.

2306
03:13:22,529 --> 03:13:27,850
In the first, we found that one third of patients
with overweight/obesity were actually at risk

2307
03:13:27,850 --> 03:13:34,310
for malnutrition at hospital admission using
various scoring systems.

2308
03:13:34,310 --> 03:13:39,739
And you know, what this tells us is that we,
in fact, do need new models for abnormal adiposity

2309
03:13:39,739 --> 03:13:44,320
and malnutrition to better represent risk
classifiers.

2310
03:13:44,320 --> 03:13:50,060
In another study among low-income countries,
modest increases in income, reduced underweight

2311
03:13:50,060 --> 03:13:54,890
prevalence, but without affecting obesity
prevalence.

2312
03:13:54,890 --> 03:14:00,150
And here we need to better understand the
social determinants of health with high-quality,

2313
03:14:00,150 --> 03:14:02,600
population-based studies.

2314
03:14:02,600 --> 03:14:09,940
In the third study, the risk of undernutrition,
those risks where per capita GDP, levels of

2315
03:14:09,940 --> 03:14:16,930
urbanization, supply of fatty foods, various
population-based vulnerability shocks, and

2316
03:14:16,930 --> 03:14:17,930
diseases.

2317
03:14:17,930 --> 03:14:25,450
While the risks for overnutrition were cereal
import dependency again per capita GDP, domestic

2318
03:14:25,450 --> 03:14:29,350
food production, and dietary energy supply.

2319
03:14:29,350 --> 03:14:34,890
We need more policy actions, better policy
actions for sustainable and balanced food

2320
03:14:34,890 --> 03:14:36,970
and nutrition systems.

2321
03:14:36,970 --> 03:14:42,460
Transformation through trade, openness, and
reduction of adverse effects of urbanization.

2322
03:14:42,460 --> 03:14:47,729
In the last study, we look at the obesity
paradox, where obesity would be associated

2323
03:14:47,729 --> 03:14:51,720
with increased survival, with, let's just
say, for example, heart failure and actually

2324
03:14:51,720 --> 03:14:54,290
all types of heart failure.

2325
03:14:54,290 --> 03:14:59,220
Malnutrition doubled the mortality risk in
patients with obesity and heart failure, showing

2326
03:14:59,220 --> 03:15:05,420
the interaction of those two states, obesity
and malnutrition compared with patients with

2327
03:15:05,420 --> 03:15:07,510
normal nutritional status.

2328
03:15:07,510 --> 03:15:08,920
So actually, what do we need?

2329
03:15:08,920 --> 03:15:14,710
We need routine recommendations in patients
with obesity, not just talking about weight

2330
03:15:14,710 --> 03:15:18,450
loss, but actually nutritional status as well.

2331
03:15:18,450 --> 03:15:25,660
We look at mechanisms in a computer community-based
cohort, patients with obesity, a higher BMI

2332
03:15:25,660 --> 03:15:32,000
and poor nutritional status had the highest
comorbidity burden in terms of adverse cardiac

2333
03:15:32,000 --> 03:15:35,260
remodeling and composite clinical outcomes.

2334
03:15:35,260 --> 03:15:42,190
So this had to do with ectopic fat inflammation,
pro-BNP, better nutrition protects against

2335
03:15:42,190 --> 03:15:48,689
endothelial inflammation and damage, and the
net effect was maladaptive cardiac remodeling.

2336
03:15:48,689 --> 03:15:53,939
And this affirms this networking interaction
of adiposity and malnutrition.

2337
03:15:53,939 --> 03:15:58,989
In another study there were metabolic sub
phenotypes that reflected different responses

2338
03:15:58,989 --> 03:16:06,260
to macronutrients may impact microbiome and
other genetic susceptibilities, and clearly,

2339
03:16:06,260 --> 03:16:08,260
we need more translational research.

2340
03:16:08,260 --> 03:16:15,819
Here are the various preventive strategies
to reduce this dual burden of abnormal adiposity

2341
03:16:15,819 --> 03:16:22,810
and malnutrition on the left for adiposity,
the preventive strategies deal with cardiometabolic

2342
03:16:22,810 --> 03:16:29,830
risk, biomechanical complications, ectopic
fat, inflammation, stigma, social determinants,

2343
03:16:29,830 --> 03:16:36,590
transcultural factors for malnutrition on
the right, macronutrient amount and distribution,

2344
03:16:36,590 --> 03:16:41,670
micronutrient deficiencies, endocrine disruptors,
body composition, sarcopenia, and then, of

2345
03:16:41,670 --> 03:16:46,220
course, social determinants and transcultural
factors.

2346
03:16:46,220 --> 03:16:51,420
Implementation over the short term, you need
a mandate, then a champion, a person who's

2347
03:16:51,420 --> 03:16:53,479
credentialed and experience.

2348
03:16:53,479 --> 03:16:59,881
Assemble a team, get your funding, leverage
technology, which is a force multiplier, create

2349
03:16:59,881 --> 03:17:06,010
your infrastructure, your physical and non-physical
immersive infrastructure, and then you adapt

2350
03:17:06,010 --> 03:17:08,590
and optimize based on data.

2351
03:17:08,590 --> 03:17:15,660
Let's conclude. Patients with nutritionally
unhealthy obesity represent a distinct high-risk

2352
03:17:15,660 --> 03:17:23,489
population, and this is supported by theoretical,
epidemiologic, mechanistic, and social relationships

2353
03:17:23,489 --> 03:17:29,210
and can be better understood and pragmatically
managed using our driver-based chronic disease

2354
03:17:29,210 --> 03:17:30,550
models.

2355
03:17:30,550 --> 03:17:36,850
Next steps should address research gaps, knowledge
gaps, and practice gaps.

2356
03:17:36,850 --> 03:17:39,670
Thank you.

2357
03:17:39,670 --> 03:17:46,430
DR. CAROLYN NEWBERRY: So I wanted to thank the
organizers for asking me to speak today about

2358
03:17:46,430 --> 03:17:52,430
malabsorptive and small bowel disorders and
the increased burden of malnutrition in GI

2359
03:17:52,430 --> 03:17:57,359
patients and what to do about it, and what
research directions we can take to improve

2360
03:17:57,359 --> 03:18:02,020
care in this population.

2361
03:18:02,020 --> 03:18:08,359
Here are my current disclosures, none of which
are pertinent to this talk.

2362
03:18:08,359 --> 03:18:10,200
In terms of a lecture outline today.

2363
03:18:10,200 --> 03:18:15,211
We'll be reviewing small bowel anatomy
and absorptive properties, the small bowel

2364
03:18:15,211 --> 03:18:20,140
pathology as a high risk disease state using
inflammatory bowel disease as an example,

2365
03:18:20,140 --> 03:18:25,750
risk stratification and care management pathways,
and future directions for clinical care and

2366
03:18:25,750 --> 03:18:29,020
research.

2367
03:18:29,020 --> 03:18:33,620
The small bowel is one of the most important
areas of the luminal GI tract for digestion

2368
03:18:33,620 --> 03:18:39,149
and nutrient absorption, the total length is
achieved by the age of nine.

2369
03:18:39,149 --> 03:18:44,812
And it includes about 500 to 700 centimeters
or 16 to 20 feet, the height of a giraffe.

2370
03:18:44,812 --> 03:18:50,340
The colon, in comparison is only about 150
centimeters long.

2371
03:18:50,340 --> 03:18:56,680
The total absorptive capacity of the small
intestine is about 8.5 liters, which is 85%

2372
03:18:56,680 --> 03:19:01,070
of total ingested fluids and digestive secretions.

2373
03:19:01,070 --> 03:19:06,180
Surface area is enhanced by the presence of
villi.

2374
03:19:06,180 --> 03:19:11,310
Different gastric secretions, bile and pancreatic
secretions allow for further breakdown of

2375
03:19:11,310 --> 03:19:17,270
macronutrients and micronutrients into their
byproducts, which is then primarily absorbed

2376
03:19:17,270 --> 03:19:23,029
throughout the length of the small intestine,
as depicted here.

2377
03:19:23,029 --> 03:19:27,040
Considering the absorptive properties of the
small intestine, it's not hard to see why

2378
03:19:27,040 --> 03:19:33,271
patients with pathology in this area are at high
risk for malnutrition.

2379
03:19:33,271 --> 03:19:38,649
The combination of malabsorption, which leads
to reduced calorie and nutrient utilization,

2380
03:19:38,649 --> 03:19:43,670
inflammatory changes such as found in things
like inflammatory bowel disease, which increases

2381
03:19:43,670 --> 03:19:49,319
resting energy expenditure and associated
digestive symptoms and anorexia, which reduce

2382
03:19:49,319 --> 03:19:55,460
oral intake, would all lead to a high risk
of malnutrition in this population, putting

2383
03:19:55,460 --> 03:20:03,790
them at risk of chronic disease state related
malnutrition, as per ASPEN guidelines.

2384
03:20:03,790 --> 03:20:09,260
The prevalence of significance of malnutrition
in patients with small bowel diseases, including

2385
03:20:09,260 --> 03:20:13,199
things like inflammatory bowel disease, is
quite high.

2386
03:20:13,199 --> 03:20:19,270
And current studies estimate that between
20 and 85% of patients with IBD have some

2387
03:20:19,270 --> 03:20:20,870
degree of malnutrition.

2388
03:20:20,870 --> 03:20:25,859
And obviously this number varies widely based
on patient demographics, underlying disease

2389
03:20:25,859 --> 03:20:30,570
state in Crohn's versus ulcerative colitis,
with Crohn's having higher rates of malnutrition

2390
03:20:30,570 --> 03:20:36,649
due to more extensive disease processes and
surgical history.

2391
03:20:36,649 --> 03:20:40,920
In terms of clinical outcomes of these patients
when they are hospitalized, the results are

2392
03:20:40,920 --> 03:20:42,470
also quite staggering.

2393
03:20:42,470 --> 03:20:48,960
So this is some information about a large
all-payer database maintained by the AHRQ

2394
03:20:48,960 --> 03:20:55,080
that provides a nationwide inpatient sampling
of thousands of patients.

2395
03:20:55,080 --> 03:20:59,710
Patients who are admitted to the hospital
who had inflammatory bowel disease were actually

2396
03:20:59,710 --> 03:21:07,300
six times more likely to be coded as having
protein calorie malnutrition per ICD 10 coding

2397
03:21:07,300 --> 03:21:12,010
versus those without inflammatory bowel disease.

2398
03:21:12,010 --> 03:21:17,510
Mortality was actually up to five times higher
in the population of patients with inflammatory

2399
03:21:17,510 --> 03:21:24,170
bowel disease that also had concomitant malnutrition
in comparison to those who didn't.

2400
03:21:24,170 --> 03:21:34,220
Their length of stay was twice as long, and
their hospital charges were more than double.

2401
03:21:34,220 --> 03:21:39,739
In light of statistics like these, national
guidelines like those put forth by the European

2402
03:21:39,739 --> 03:21:45,130
Society for Parenteral and Enteral Nutrition,
have spelled out that these patients are at

2403
03:21:45,130 --> 03:21:51,050
high risk for malnutrition and that we need
to start both risk stratifying and intervening

2404
03:21:51,050 --> 03:21:53,340
when appropriate.

2405
03:21:53,340 --> 03:21:57,689
Here are two guidelines that are important
to highlight in this population.

2406
03:21:57,689 --> 03:22:01,859
The first is the patients with IBD are at
high risk and therefore should be screened

2407
03:22:01,859 --> 03:22:06,870
for malnutrition at the time of diagnosis
or on a regular basis thereafter.

2408
03:22:06,870 --> 03:22:10,990
And that documented malnutrition in these
patients should be treated appropriately,

2409
03:22:10,990 --> 03:22:17,960
but it can worsen prognosis, complication
rates, mortality and quality of life.

2410
03:22:17,960 --> 03:22:22,170
Extensive literature has shown that early
identification of malnourished patients in

2411
03:22:22,170 --> 03:22:27,530
this population using a two step approach
of nutritional screening followed by a subsequent

2412
03:22:27,530 --> 03:22:32,090
assessment in those that are high risk can
lead to earlier intervention and impact on

2413
03:22:32,090 --> 03:22:33,590
clinical outcomes.

2414
03:22:33,590 --> 03:22:39,689
However, the optimal approach to screening
and the optimal approach intervention are

2415
03:22:39,689 --> 03:22:44,100
still under negotiation.

2416
03:22:44,100 --> 03:22:47,620
Risk stratification tools really come in two
flavors.

2417
03:22:47,620 --> 03:22:51,660
The first is the actual screening tool, which
you've probably heard about in this conference

2418
03:22:51,660 --> 03:22:58,100
already, examples being the NRS-2002, the
MUST score, the nutritional risk index, the

2419
03:22:58,100 --> 03:23:01,210
Malnutrition Inflammation Risk Tool. 

2420
03:23:01,210 --> 03:23:05,830
These things include things like BMI, recent
weight loss trends, especially in terms of

2421
03:23:05,830 --> 03:23:12,920
percentage of total body weight loss, current
disease severity, and basic laboratory data.

2422
03:23:12,920 --> 03:23:17,040
And then the nutritional assessment tools
that are often used as a second step if the

2423
03:23:17,040 --> 03:23:20,271
nutritional screening comes back positive.

2424
03:23:20,271 --> 03:23:26,979
These include things like comprehensive dietitian
and gastroenterologist assessment, the SGA,

2425
03:23:26,979 --> 03:23:33,199
skeletal muscle assessment, and free fat mass
assessment, which includes things like taking

2426
03:23:33,199 --> 03:23:39,800
a complete inflammatory bowel disease history,
again, BMI, more comprehensive nutritional

2427
03:23:39,800 --> 03:23:45,550
labs and micronutrient screenings, and then
body impedance analysis or cross-sectional

2428
03:23:45,550 --> 03:23:52,870
imaging, like CAT scan to define body composition.

2429
03:23:52,870 --> 03:23:58,500
Determining whether screening tools are accurately
identifying patients that are malnourished

2430
03:23:58,500 --> 03:24:03,300
requires comparing them with formal assessment
tools.

2431
03:24:03,300 --> 03:24:07,330
This study did just that in IBD populations.

2432
03:24:07,330 --> 03:24:12,680
It determined that the NRS-2002, which is
usually used in the inpatient setting, had

2433
03:24:12,680 --> 03:24:18,989
reasonable correlation with assessment tools,
as did the newer malnutrition inflammatory

2434
03:24:18,989 --> 03:24:27,069
risk tool, which is developed for use in Crohn's
patients but hasn't been extensively validated.

2435
03:24:27,069 --> 03:24:33,760
The MUST score which has been validated in
a large percentage of populations had some

2436
03:24:33,760 --> 03:24:38,319
correlation in some studies and weak correlation
in others.

2437
03:24:38,319 --> 03:24:47,449
A newer tool called the SaskIBD-NR tool has
also been analyzed, which takes into account

2438
03:24:47,449 --> 03:24:52,680
more digestive complaints that may be pertinent
to the IBD patient.

2439
03:24:52,680 --> 03:24:57,359
Considering the lack of definitive evidence
for which screening tool corresponds to the

2440
03:24:57,359 --> 03:25:01,771
best outcomes, there's still more work to
be done in this field.

2441
03:25:01,771 --> 03:25:08,120
I did want to highlight another potential area
of study which looks at nutrition education

2442
03:25:08,120 --> 03:25:10,540
in gastroenterology fellowships.

2443
03:25:10,540 --> 03:25:18,240
I pulled some studies that actually analyzed
this question and found that GI fellows actually

2444
03:25:18,240 --> 03:25:24,780
get very little nutrition education, like
other physician specialties, and perform poorly

2445
03:25:24,780 --> 03:25:30,479
in knowledge-based assessment as well as in
terms of how comfortable they are providing

2446
03:25:30,479 --> 03:25:38,600
nutritional assessment support tools and understanding
how to utilize nutrition in disease states.

2447
03:25:38,600 --> 03:25:43,340
I do ask if gastroenterologist are not trained
in proper nutrition principles in the first

2448
03:25:43,340 --> 03:25:46,161
place, will they even know to use these malnutrition
screening tools in practice?

2449
03:25:46,161 --> 03:25:52,729
And I think this is a further area that we
need to analyze.

2450
03:25:52,729 --> 03:25:54,600
In terms of intervention tactics.

2451
03:25:54,600 --> 03:25:59,050
We also don't really know the best way to
intervene on these patients.

2452
03:25:59,050 --> 03:26:04,120
There's been an increase in addressing multidisciplinary
care modeling, in particular for complex disease

2453
03:26:04,120 --> 03:26:05,890
states like IBD.

2454
03:26:05,890 --> 03:26:10,640
And a number of papers have been published
in the gastroenterology literature highlighting

2455
03:26:10,640 --> 03:26:16,899
the need for incorporating people like dietitians
into clinical care teams.

2456
03:26:16,899 --> 03:26:22,620
With this, a number of large academic centers
have done just that, including teams that

2457
03:26:22,620 --> 03:26:26,899
have been developed at Cedars-Sinai as well
as my home institution.

2458
03:26:26,899 --> 03:26:33,760
National societies have also developed more
guidance for providers, both with traditional

2459
03:26:33,760 --> 03:26:36,750
tool assessments as well as interventional
tactics.

2460
03:26:36,750 --> 03:26:42,490
However, literature is lacking to determine
how these perform in clinical practice and

2461
03:26:42,490 --> 03:26:46,600
how they affect patient outcomes.

2462
03:26:46,600 --> 03:26:51,670
And so in closing, we know that patients with
small bowel pathology like found in the IBD

2463
03:26:51,670 --> 03:26:55,790
population are at high risk for malnutrition
due the small bowel's important role in digestion

2464
03:26:55,790 --> 03:26:57,620
and absorption.

2465
03:26:57,620 --> 03:27:01,699
We also know that studies have confirmed high
rates of malnutrition in this population,

2466
03:27:01,699 --> 03:27:03,449
which correlates with poorer clinical outcomes.

2467
03:27:03,449 --> 03:27:07,080
There are a number of things we don't know
however.

2468
03:27:07,080 --> 03:27:10,810
The optimal means for risk stratify patients
to provide targeted intervention, especially

2469
03:27:10,810 --> 03:27:18,460
in the outpatient setting in this subset population
of small bowel diseases like IBD is still

2470
03:27:18,460 --> 03:27:19,460
unclear.

2471
03:27:19,460 --> 03:27:24,390
National physician nutritional educational
efforts need to be augmented across the board,

2472
03:27:24,390 --> 03:27:26,939
especially in specialties who care for higher
risk patients.

2473
03:27:26,939 --> 03:27:31,330
We don't actually know if these efforts will
improve clinical outcomes.

2474
03:27:31,330 --> 03:27:36,470
Additionally, multidisciplinary teams and
patient-centered medical homes may play a

2475
03:27:36,470 --> 03:27:42,010
role in populations like IBD as well as other
complex disease states, but we need to study this.

2476
03:27:42,010 --> 03:27:47,290
DR. JAY PATEL: Hello, my name is Jay Patel, and
I am joining you from the Medical College

2477
03:27:47,290 --> 03:27:48,570
of Wisconsin.

2478
03:27:48,570 --> 03:27:52,960
Thank you to the NIH, the Office of Nutrition
and the Organizing Committee for the opportunity

2479
03:27:52,960 --> 03:27:54,430
to speak with you today.

2480
03:27:54,430 --> 03:27:59,590
I will be discussing intensive care unit nutrition
and how we can move beyond just support.

2481
03:27:59,590 --> 03:28:04,729
I have no disclosures related to the contents
of this talk.

2482
03:28:04,729 --> 03:28:07,460
Let's start by examining common critical care
trajectories.

2483
03:28:07,460 --> 03:28:11,620
Our ICU patients typically follow one of three
patterns.

2484
03:28:11,620 --> 03:28:16,260
First, there are some patients that no matter
what we do, they succumb to fulminant death

2485
03:28:16,260 --> 03:28:18,271
within 24 to 48 hours.

2486
03:28:18,271 --> 03:28:20,680
Fortunately, these patients represent the
minority.

2487
03:28:20,680 --> 03:28:25,220
The second patient in green is probably the
most common phenotype, where they spend a

2488
03:28:25,220 --> 03:28:29,390
few days to a week on various forms of life
support but recover and leave our ICU and

2489
03:28:29,390 --> 03:28:30,550
even go home.

2490
03:28:30,550 --> 03:28:36,960
The third patients in blue is the individual
who has an undulating course marred by repeated

2491
03:28:36,960 --> 03:28:42,100
ICU admissions, nosocomial infections, severe
malnourishment, and often culminating in

2492
03:28:42,100 --> 03:28:45,061
an indolent death.

2493
03:28:45,061 --> 03:28:50,310
In their most recent guideline, the European
Society of Parenteral and Enteral Nutrition

2494
03:28:50,310 --> 03:28:53,600
outlined the phases of critical illness during
that first week.

2495
03:28:53,600 --> 03:28:57,240
You'll notice that there are two phases: an
acute phase and a late phase.

2496
03:28:57,240 --> 03:29:02,840
And the acute phase is partitioned into an
early acute phase and a late acute phase.

2497
03:29:02,840 --> 03:29:07,420
Now notice that there's days, one to two,
and days three to seven listed here, but in

2498
03:29:07,420 --> 03:29:12,380
reality, we just don't know when patients
transition from one phase to another.

2499
03:29:12,380 --> 03:29:18,510
And some research gaps in this context include,
can biomarkers distinguish between the phases

2500
03:29:18,510 --> 03:29:19,510
of critical illness?

2501
03:29:19,510 --> 03:29:22,163
And we'll see why that might be important
a little bit later.

2502
03:29:22,163 --> 03:29:24,360
And can biomarkers inform anabolism?

2503
03:29:24,360 --> 03:29:28,450
Again, we'll see why that might be important a
little bit later as well.

2504
03:29:28,450 --> 03:29:32,630
Now, if we isolate the early acute phase,
that is when there's dysregulated inflammatory

2505
03:29:32,630 --> 03:29:33,920
and immune responses.

2506
03:29:33,920 --> 03:29:38,900
And the clinical phenotype is one where the
patient is newly intubated, febrile, undergoing

2507
03:29:38,900 --> 03:29:43,101
circulatory resuscitation, started on vasopressors.

2508
03:29:43,101 --> 03:29:46,620
What is the role of nutrition during this
early acute phase?

2509
03:29:46,620 --> 03:29:51,710
Well, if we shift our focus to micronutrients
for just a moment, the concept of metabolic

2510
03:29:51,710 --> 03:29:57,210
resuscitation seems to suggest that supraphysiologic
doses of micronutrients, examples include

2511
03:29:57,210 --> 03:30:03,859
vitamin C, vitamin D, selenium, could serve
to extinguish that rapidly burning inflammatory

2512
03:30:03,859 --> 03:30:04,859
fire.

2513
03:30:04,859 --> 03:30:08,840
Now, even though there are numerous negative
trials in this space, the paradigm may be

2514
03:30:08,840 --> 03:30:14,220
weakened by the fact that we don't have proper
dosing studies and additional needs work may

2515
03:30:14,220 --> 03:30:20,470
need to be done, particularly test the various
types, combinations, and doses of micronutrients.

2516
03:30:20,470 --> 03:30:25,620
So in that context, research gaps here could
include, which critically ill patients would

2517
03:30:25,620 --> 03:30:27,960
benefit most from supraphysiologic doses of
micronutrients?

2518
03:30:27,960 --> 03:30:33,830
And in critically ill patients, what are the
optimal and safe doses and delivery methods

2519
03:30:33,830 --> 03:30:35,710
for various micronutrients?

2520
03:30:35,710 --> 03:30:43,439
And what is the efficacy of combination micronutrients
with perhaps pleiotropic effects?

2521
03:30:43,439 --> 03:30:47,590
Let's go back to our trajectories and let's
home in on the second and third, which represent

2522
03:30:47,590 --> 03:30:52,770
patients that spend more than a few days in
the ICU.

2523
03:30:52,770 --> 03:30:56,310
And because of dysregulated inflammatory immune
responses.

2524
03:30:56,310 --> 03:31:01,390
The question is what happens during this early
acute phase that nutrition has the capacity

2525
03:31:01,390 --> 03:31:02,390
to modify?

2526
03:31:02,390 --> 03:31:07,279
First, let's point out that hyper-catabolism
and ensuing caloric debt are common during

2527
03:31:07,279 --> 03:31:11,970
this phase and persist throughout the intensive
care unit stay and beyond.

2528
03:31:11,970 --> 03:31:17,520
So when we think of the provision of micronutrients,
what is often asked is when, how much, and

2529
03:31:17,520 --> 03:31:19,979
through which route should I deliver nutrition?

2530
03:31:19,979 --> 03:31:24,359
I think many of us would agree that earlier
nutrition is favored over delayed.

2531
03:31:24,359 --> 03:31:29,810
But in answering the dose question, numerous
trials that have compared the dose of nutrition

2532
03:31:29,810 --> 03:31:34,600
during the first week of critical illness
have been negative, and there were negative

2533
03:31:34,600 --> 03:31:38,640
for outcomes, including mortality.

2534
03:31:38,640 --> 03:31:42,640
So if not mortality, what could dose impact?

2535
03:31:42,640 --> 03:31:45,090
Well, here's the third thing that happens.

2536
03:31:45,090 --> 03:31:48,500
And there may be varying degrees of gut dysfunction.

2537
03:31:48,500 --> 03:31:54,560
And the role of nutrition, especially macronutrients,
may be to mitigate the silently brewing threats

2538
03:31:54,560 --> 03:31:58,950
of gut dysfunction, again, during that early
acute phase of critical illness.

2539
03:31:58,950 --> 03:32:05,189
Now, this is an oversimplification, but it
turns out that these mechanisms listed here,

2540
03:32:05,189 --> 03:32:11,170
along with the emergence of a pathobiome can
generate gut-derived inflammation.

2541
03:32:11,170 --> 03:32:16,600
And it's that gut-derived inflammation, as
you all know, that serves as the motor that

2542
03:32:16,600 --> 03:32:19,521
drives multiple organ failure.

2543
03:32:19,521 --> 03:32:24,609
And research gaps related to nutrition and
therefore gut dysfunction include, what is

2544
03:32:24,609 --> 03:32:29,199
the variance in gut dysfunction based on the
type and severity of critical illness?

2545
03:32:29,199 --> 03:32:32,989
Can bedside biomarkers identify gut epithelial
functions?

2546
03:32:32,989 --> 03:32:38,770
What is the impact of various doses of enteral
nutrition on gut dysfunction?

2547
03:32:38,770 --> 03:32:43,560
And what is the efficacy of various doses
of enteral nutrition in subsets of critically

2548
03:32:43,560 --> 03:32:46,340
ill patients with varying amounts of gut dysfunction?

2549
03:32:46,340 --> 03:32:53,090
Because again, if we can identify when patients
are going to tolerate nutrition based on a favorable

2550
03:32:53,090 --> 03:32:57,380
gut function, then perhaps it's time to push
more nutrition.

2551
03:32:57,380 --> 03:32:59,800
But we just don't know right now.

2552
03:32:59,800 --> 03:33:03,729
And then there are a subgroup of critically
ill patients who are more unstable, and that

2553
03:33:03,729 --> 03:33:09,020
includes individuals who are in circulatory
shock, on ECMO, and even those who are prone.

2554
03:33:09,020 --> 03:33:14,890
And they may be more unstable because they
might have a more heightened inflammatory

2555
03:33:14,890 --> 03:33:19,520
state and more susceptible therefore to gut
dysfunction and acquired malnutrition.

2556
03:33:19,520 --> 03:33:21,770
And so in these patients, we have a conundrum.

2557
03:33:21,770 --> 03:33:27,771
On one hand, if we do not introduce luminal
nutrients, we risk gut dysfunction, which

2558
03:33:27,771 --> 03:33:31,820
can then serve to perpetuate the multiple
organ dysfunction syndrome.

2559
03:33:31,820 --> 03:33:36,100
And, of course, some of the downstream effects
include escalating energy debt and acquired

2560
03:33:36,100 --> 03:33:37,100
malnutrition.

2561
03:33:37,100 --> 03:33:44,540
But on the other hand, if we feed these so-called
unstable patients, we risk GI intolerance,

2562
03:33:44,540 --> 03:33:47,899
which as you can see, it can manifest in many
ways, including vomiting.

2563
03:33:47,899 --> 03:33:53,390
And the gravest consequence includes bowel
necrosis, often reported in patients who are

2564
03:33:53,390 --> 03:33:57,160
on ECMO and in circulatory shock.

2565
03:33:57,160 --> 03:34:02,630
And so for the unstable patients, those perhaps
prone to greater gut dysfunctions and acquired

2566
03:34:02,630 --> 03:34:05,790
malnutrition, here are some research related
gaps.

2567
03:34:05,790 --> 03:34:08,780
What's the efficacy of EN in those circulatory
shock?

2568
03:34:08,780 --> 03:34:13,830
What's the efficacy of various doses of EN
in patients undergoing various forms of ECMO?

2569
03:34:13,830 --> 03:34:18,740
And then what is the efficacy of various doses
of EN in patients undergoing prone positioning?

2570
03:34:18,740 --> 03:34:24,630
Finally, here's a fourth consequence, and
that is proteolysis, which often begins in

2571
03:34:24,630 --> 03:34:29,750
the early acute phase of critical illness
and leads to loss of muscle mass.

2572
03:34:29,750 --> 03:34:34,380
So here's a study of 60-some ICU patients
that underwent ultrasound of the rectus femoris

2573
03:34:34,380 --> 03:34:39,710
muscle for cross-sectional area assessment
and biopsies on ICUs days, one, three, seven

2574
03:34:39,710 --> 03:34:40,710
and ten.

2575
03:34:40,710 --> 03:34:44,640
And what you can see here from this graph
is that the rectus femoris cross-sectional

2576
03:34:44,640 --> 03:34:51,080
area decreased by 17% an ICU day.

2577
03:34:51,080 --> 03:34:53,380
And so why is focusing on muscle importance?

2578
03:34:53,380 --> 03:34:58,220
Well, for starters, this figure shows that
short-term mortality from critical illness

2579
03:34:58,220 --> 03:35:04,840
has decreased from greater than 40% in the
1980s and 90s to under 30% by 2011.

2580
03:35:04,840 --> 03:35:11,689
And so if our patients are dying, what happens
to them when they leave our ICU?

2581
03:35:11,689 --> 03:35:17,859
It turns out that survivorship post ICU is
plagued by physical complications that impacts

2582
03:35:17,859 --> 03:35:19,069
quality of life.

2583
03:35:19,069 --> 03:35:25,421
And that quality of life impairments can persist
for up to five years, which really has a significant

2584
03:35:25,421 --> 03:35:30,960
disability on things such as active activities
of daily living.

2585
03:35:30,960 --> 03:35:35,970
So to preserve muscle or stimulate synthesis,
it makes intuitive sense to deliver protein.

2586
03:35:35,970 --> 03:35:40,750
So here's a recent meta analysis of 15 randomized
controlled trials comparing high versus low

2587
03:35:40,750 --> 03:35:42,540
protein in critically ill patients.

2588
03:35:42,540 --> 03:35:46,970
And it found no benefit of high or low dose
protein on mortality.

2589
03:35:46,970 --> 03:35:51,449
But one important finding highlighted here
in green is a higher protein was associated

2590
03:35:51,449 --> 03:35:53,970
with an improvement in the loss of muscle
mass.

2591
03:35:53,970 --> 03:35:59,109
And future protein trials should assess outcomes
that are going to be important to survivors.

2592
03:35:59,109 --> 03:36:03,941
Parenthetically, this meta-analysis did not
include the recent effort trial, which, as

2593
03:36:03,941 --> 03:36:07,319
you know, was a negative trial, and we hope
to have it published soon.

2594
03:36:07,319 --> 03:36:12,090
But the story with protein is more complicated,
that high versus low dose.

2595
03:36:12,090 --> 03:36:16,780
So for starters, here's what happens to muscle
protein synthesis with a protein load.

2596
03:36:16,780 --> 03:36:21,029
The arrows show protein intake, and the green
areas under the curve represent periods of

2597
03:36:21,029 --> 03:36:23,480
increased muscle protein synthesis.

2598
03:36:23,480 --> 03:36:26,230
The red represents muscle protein breakdown.

2599
03:36:26,230 --> 03:36:33,050
As you can see, there's a net even nitrogen
valance.

2600
03:36:33,050 --> 03:36:37,470
But here's what happens with aging and muscle
disuse.

2601
03:36:37,470 --> 03:36:41,779
Muscle protein synthesis is attenuated, and
you can extrapolate that this could even happen

2602
03:36:41,779 --> 03:36:45,610
in our critically ill patients who have impaired
anabolic responses.

2603
03:36:45,610 --> 03:36:50,050
And as you can glean from the white areas
under the curve, there's more protein breakdown,

2604
03:36:50,050 --> 03:36:53,310
culminating in a negative nitrogen valance.

2605
03:36:53,310 --> 03:36:59,939
But when protein loading is coupled with resistance
exercise, there's a much greater increase

2606
03:36:59,939 --> 03:37:01,819
in muscle protein synthesis.

2607
03:37:01,819 --> 03:37:03,770
And the story certainly doesn't end there.

2608
03:37:03,770 --> 03:37:08,520
We still don't know the optimal type of amino
acid, method of infusion, or its effect in

2609
03:37:08,520 --> 03:37:11,020
subgroups of critically ill patients.

2610
03:37:11,020 --> 03:37:16,939
And so questions related to protein provision
and critical illness include, can admission

2611
03:37:16,939 --> 03:37:22,210
bedside ultrasound measurements of muscle
groups risk stratify our critically ill patients?

2612
03:37:22,210 --> 03:37:27,210
Can serum biomarkers inform
muscle protein synthesis?

2613
03:37:27,210 --> 03:37:32,189
And then what is the feasibility, acceptability,
and efficacy of protein loading and resistance

2614
03:37:32,189 --> 03:37:36,810
exercise on parameters of physical functioning
in survivors of critical illness?

2615
03:37:36,810 --> 03:37:41,310
And then what is the optimal safe dose of
protein in subgroups of critically ill patients,

2616
03:37:41,310 --> 03:37:45,330
including those with cirrhosis, kidney injury,
and obesity?

2617
03:37:45,330 --> 03:37:47,000
Thank you for your attention.

2618
03:37:47,000 --> 03:37:51,250
DR. DAVID SERES: Thank you for attending.

2619
03:37:51,250 --> 03:37:54,050
I'm Dr. David Seres at Columbia.

2620
03:37:54,050 --> 03:37:57,750
And we'll be talking about dementia and artificial
feeding.

2621
03:37:57,750 --> 03:38:06,649
This is a rather controversial subject, and
the data on it is really rather poor.

2622
03:38:06,649 --> 03:38:11,210
Just to reiterate what I've said in the past,
I don't have any commercial conflicts but

2623
03:38:11,210 --> 03:38:16,850
I am opinionated, and hopefully, I'll be able
to stick to the evidence.

2624
03:38:16,850 --> 03:38:22,010
Also to reiterate my concerns about basic
practice on observational research I remind

2625
03:38:22,010 --> 03:38:27,430
you that I go to the pilot every time I get
on a plane to ask that the seatbelt not be

2626
03:38:27,430 --> 03:38:32,680
turned on because there's a 100% concordance
between them turning on the seatbelt sign

2627
03:38:32,680 --> 03:38:34,430
and the plane ride getting rough.

2628
03:38:34,430 --> 03:38:41,250
Obviously, this is not causal, but it is an
example of how this kind of thinking could

2629
03:38:41,250 --> 03:38:45,090
lead us astray.

2630
03:38:45,090 --> 03:38:50,979
Speaking of observational research, this is
one of the better studies in which patients

2631
03:38:50,979 --> 03:38:57,370
were all offered gastrostomy, this is from
the VA, approximately 45 patients.

2632
03:38:57,370 --> 03:39:03,600
And there was a cohort of patients who did
not get a gastrostomy based on surrogate refusal

2633
03:39:03,600 --> 03:39:04,970
or an advance directive.

2634
03:39:04,970 --> 03:39:11,800
And their longevity was tracked, and there
was no difference in the life expectancy between

2635
03:39:11,800 --> 03:39:17,600
the two cohorts whether they received the
gastrostomy or not.

2636
03:39:17,600 --> 03:39:22,700
There have been some studies that have shown
some improvements in some characteristics

2637
03:39:22,700 --> 03:39:28,140
in these patients, but only in patients with
mild dementia.

2638
03:39:28,140 --> 03:39:35,810
This is also retrospective, and the patients
that benefited had mild dementia.

2639
03:39:35,810 --> 03:39:39,870
The ones with severe dementia did not.

2640
03:39:39,870 --> 03:39:45,479
The benefits were improvement in independent
living, in oral intake.

2641
03:39:45,479 --> 03:39:50,960
Both of these were improved in this study.

2642
03:39:50,960 --> 03:39:53,359
Pneumonia was not.

2643
03:39:53,359 --> 03:40:00,580
In fact, the most common cause of death for
patients who have gastrostomies is pneumonia.

2644
03:40:00,580 --> 03:40:06,300
So the idea that putting a gastrostomy on
a patient and not letting them eat because

2645
03:40:06,300 --> 03:40:09,359
of swallowing dysfunction is probably erroneous.

2646
03:40:09,359 --> 03:40:14,470
Through the past 30 years or so, there has
been a growing trend for nursing homes to

2647
03:40:14,470 --> 03:40:19,130
refuse to take nasal feeding tubes and require
gastrostomies.

2648
03:40:19,130 --> 03:40:26,609
Back in 2015, we surveyed every nursing home
in New York City, and then an adequately powered

2649
03:40:26,609 --> 03:40:28,850
sample of the rest of the United States.

2650
03:40:28,850 --> 03:40:33,430
We had a tenacious young student who called
every nursing home five and six times, so

2651
03:40:33,430 --> 03:40:36,010
we had an 85% response rate.

2652
03:40:36,010 --> 03:40:40,540
Eighty percent of the nursing homes in New York City
refused to take nasal feeding tubes.

2653
03:40:40,540 --> 03:40:43,810
Nationally, the refusal rate was only 35%.

2654
03:40:43,810 --> 03:40:47,750
I would wager that this has gotten far worse.

2655
03:40:47,750 --> 03:40:52,029
It's all based on anecdote when I was working
in.

2656
03:40:52,029 --> 03:40:56,760
SPEAKER: Early in my career, I was working
in three different hospitals.

2657
03:40:56,760 --> 03:41:02,189
And on the same day, two of the same patients
in each of those hospitals, a feeding tube

2658
03:41:02,189 --> 03:41:03,189
was placed.

2659
03:41:03,189 --> 03:41:08,239
It went down to the trachea through the lung
parenchyma into the pleural.

2660
03:41:08,239 --> 03:41:11,770
A patient was fed into the pleural and died.

2661
03:41:11,770 --> 03:41:16,239
And I say again, it happened to the same patient
in each of the three hospitals on the same

2662
03:41:16,239 --> 03:41:17,239
day.

2663
03:41:17,239 --> 03:41:18,239
So it must not have happened at all.

2664
03:41:18,239 --> 03:41:22,260
I've never been able to find the index patient.

2665
03:41:22,260 --> 03:41:25,399
That said, I'm sure that this has happened,
but this spread like wildfire.

2666
03:41:25,399 --> 03:41:31,271
And within about a year we started hearing
about nursing homes starting to refuse nasal

2667
03:41:31,271 --> 03:41:33,569
tubes because of this story.

2668
03:41:33,569 --> 03:41:38,590
Currently, if you were to ask the nursing
homes why they were refusing them, the answers

2669
03:41:38,590 --> 03:41:40,439
are really quite interesting.

2670
03:41:40,439 --> 03:41:44,430
The tubes will fall out, the patient will
aspirate and die, we'll lose our license.

2671
03:41:44,430 --> 03:41:50,480
This was actually a quote of somebody in tears
telling me, 'Please, don't do this.'

2672
03:41:50,480 --> 03:41:56,750
In my efforts to try and get nursing homes
to take them once again, there are complete

2673
03:41:56,750 --> 03:42:04,621
misquotes of both state and CMS policy, and
having been to the state and CMS,

2674
03:42:04,621 --> 03:42:12,080
I can tell you, that they absolutely
do not have a preference for nasal tubes or

2675
03:42:12,080 --> 03:42:17,990
gastrostomies nor do they pay differently.

2676
03:42:17,990 --> 03:42:20,640
Long-term comparative effectiveness studies
are small.

2677
03:42:20,640 --> 03:42:29,819
And in the aggregate and the Cochrane Review, there
are about 750 patients really showing no substantive

2678
03:42:29,819 --> 03:42:30,819
differences.

2679
03:42:30,819 --> 03:42:35,670
There are similar complication rates, but
the complication severity strongly favors

2680
03:42:35,670 --> 03:42:37,450
the nasal tubes.

2681
03:42:37,450 --> 03:42:45,590
And the conclusions of the paper say that
there might be a benefit to using gastrostomies

2682
03:42:45,590 --> 03:42:49,979
because of a decrease in what they call the
treatment failure, which was mostly clogging,

2683
03:42:49,979 --> 03:42:52,800
which is really quite preventable.

2684
03:42:52,800 --> 03:42:54,270
There was no difference in survival.

2685
03:42:54,270 --> 03:42:57,850
There were no difference in readmission.

2686
03:42:57,850 --> 03:43:02,600
But the thing that worries me the most is
the severity of the complications.

2687
03:43:02,600 --> 03:43:09,739
In a cohort of patients that we followed in
the hospital over a period of three months.

2688
03:43:09,739 --> 03:43:13,840
Every patient was...who had been receiving
tube feeding.

2689
03:43:13,840 --> 03:43:17,890
And on average, that's about 60 patients in
our hospital.

2690
03:43:17,890 --> 03:43:25,421
Every one of them was visited twice a week
where adverse event...adverse events were

2691
03:43:25,421 --> 03:43:30,500
sampled, collected, and recorded.

2692
03:43:30,500 --> 03:43:39,500
And we did this at the bedside because we
have also shown that the incidence of complications

2693
03:43:39,500 --> 03:43:44,610
in the chart is far, far less than what actually
happens.

2694
03:43:44,610 --> 03:43:50,460
So this was based on patient, family, and
nurse interviews, and examinations.

2695
03:43:50,460 --> 03:43:56,480
And you can see here that the complication
rates were far higher with the gastrostomies

2696
03:43:56,480 --> 03:44:02,149
than they were with the nasal tubes.

2697
03:44:02,149 --> 03:44:08,350
Our final conclusion was that the adverse
event rate was something on the order of at

2698
03:44:08,350 --> 03:44:19,600
least twice of...in the patients who had gastrostomies
that the nursing homes are forcing us to put

2699
03:44:19,600 --> 03:44:21,290
in these.

2700
03:44:21,290 --> 03:44:27,319
We think that it's really quite unethical
and have been trying over the years to change

2701
03:44:27,319 --> 03:44:28,319
this behavior.

2702
03:44:28,319 --> 03:44:34,739
We have certainly had success in presenting
the data to nursing homes and training them

2703
03:44:34,739 --> 03:44:38,239
once again to use these nursing homes...using
these nasal tubes.

2704
03:44:38,239 --> 03:44:47,500
The 
practice of placing a gastrostomy at the same

2705
03:44:47,500 --> 03:44:52,569
time as a tracheostomy has become standard
practice in a lot of places.

2706
03:44:52,569 --> 03:44:57,330
In anticipation of the fact that if you're
sick enough to need a tracheostomy, of course,

2707
03:44:57,330 --> 03:45:02,430
you're going to need to be discharged to a
nursing home with a gastrostomy.

2708
03:45:02,430 --> 03:45:12,220
To test this, we put in a policy of delaying
gastrostomy until discharge planning was underway.

2709
03:45:12,220 --> 03:45:19,739
Usually, that gives us three or four days
and our endoscopists were willing to make

2710
03:45:19,739 --> 03:45:26,850
sure that these patients were prioritized
so that length of stay was not delayed...increased.

2711
03:45:26,850 --> 03:45:35,939
As a result of this delay process, we decreased
the frequency of gastrostomy from 60% of tracheostomy

2712
03:45:35,939 --> 03:45:43,790
patients down to 26%, meaning that more than
half of the gastrostomies we were replacing

2713
03:45:43,790 --> 03:45:48,930
were unnecessary or futile, meaning that the
patient was either discharged eating or had

2714
03:45:48,930 --> 03:45:54,409
expired during their hospitalization.

2715
03:45:54,409 --> 03:45:59,690
So the research questions boil down to needing
randomized controlled trials.

2716
03:45:59,690 --> 03:46:01,859
Does artificial feeding prolong life?

2717
03:46:01,859 --> 03:46:09,630
And what is the differential effect with different
levels of dementia?

2718
03:46:09,630 --> 03:46:12,790
What kind of nourishment is required to have
an impact?

2719
03:46:12,790 --> 03:46:14,590
Other alternatives to tube feeding?

2720
03:46:14,590 --> 03:46:20,210
Certainly, there's a large literature on hand
feeding of patients with dementia and swallowing

2721
03:46:20,210 --> 03:46:21,210
problems.

2722
03:46:21,210 --> 03:46:24,229
What are the predictors of response?

2723
03:46:24,229 --> 03:46:27,660
As with all this kind of research, there are
confounders we have to look at.

2724
03:46:27,660 --> 03:46:30,550
As I've mentioned, the severity of types of
malnutrition.

2725
03:46:30,550 --> 03:46:34,770
The causes for feeding difficulty, whether
it's dysphagia or anorexia.

2726
03:46:34,770 --> 03:46:39,370
The cause for the malnutrition, whether it's
starvation or catabolism.

2727
03:46:39,370 --> 03:46:45,330
I would wager that patients with catabolism
will not respond to nutrition intervention,

2728
03:46:45,330 --> 03:46:48,440
whereas those who are purely starved might.

2729
03:46:48,440 --> 03:46:53,489
We have to look at the route, whether it's
nasal versus a gastrostomy or even parenteral

2730
03:46:53,489 --> 03:46:54,489
nutrition.

2731
03:46:54,489 --> 03:46:56,229
And there are a lot of ick factors here.

2732
03:46:56,229 --> 03:47:03,239
We feel very strongly about whether or not
it's moral to prolong the life of somebody

2733
03:47:03,239 --> 03:47:08,960
in a state of severe dementia and so forth.

2734
03:47:08,960 --> 03:47:12,970
And so there's a lot of emotion around these
issues.

2735
03:47:12,970 --> 03:47:17,819
The Moonshot study that I'd love to see would
be with the patients with advanced dementia

2736
03:47:17,819 --> 03:47:25,720
and feeding problems randomized to tube feeding
or hand feeding and looking at these outcomes.

2737
03:47:25,720 --> 03:47:31,430
Thank you for your attention and I look forward
to discussing this with you in the discussion

2738
03:47:31,430 --> 03:47:32,430
section coming up.

2739
03:47:32,430 --> 03:47:38,960
DR. MICHELLE MCMACKEN: Hi, I'm Dr. Michelle
McMacken and I'll be speaking today on nutrition

2740
03:47:38,960 --> 03:47:46,910
and lifestyle medicine efforts at New York
City Health and Hospitals, the nation's largest

2741
03:47:46,910 --> 03:47:49,180
public health care system.

2742
03:47:49,180 --> 03:47:54,390
So we serve all New Yorkers regardless of
their ability to pay or their immigration

2743
03:47:54,390 --> 03:47:55,390
status.

2744
03:47:55,390 --> 03:47:59,129
The majority of our patients have Medicaid
or are uninsured.

2745
03:47:59,129 --> 03:48:04,390
We have very high racial and ethnic diversity,
and a significant proportion of our visits

2746
03:48:04,390 --> 03:48:07,629
are conducted in languages other than English.

2747
03:48:07,629 --> 03:48:12,800
So it's not uncommon in a typical week of
clinical practice to conduct visits in all

2748
03:48:12,800 --> 03:48:15,989
of these languages and sometimes more.

2749
03:48:15,989 --> 03:48:25,170
So I've been a primary care internal medicine
physician for 18 years, and my practice over

2750
03:48:25,170 --> 03:48:32,989
this time has really revolved around all of
these conditions, which, as we know, are related

2751
03:48:32,989 --> 03:48:37,359
to lifestyle behaviors, particularly nutrition.

2752
03:48:37,359 --> 03:48:44,880
In fact, we know that a suboptimal diet is
actually the number one risk factor for dying

2753
03:48:44,880 --> 03:48:47,409
of a chronic disease in the United States.

2754
03:48:47,409 --> 03:48:53,770
And yet, nutrition is vastly under-emphasized
in primary care and general clinical practice.

2755
03:48:53,770 --> 03:48:55,960
So enter lifestyle medicine.

2756
03:48:55,960 --> 03:49:03,290
This is an evidence-based approach for preventing
and treating lifestyle-related conditions

2757
03:49:03,290 --> 03:49:06,300
through the adoption of healthy behaviors.

2758
03:49:06,300 --> 03:49:10,220
So those behaviors, you can think of them
across six different pillars.

2759
03:49:10,220 --> 03:49:12,521
There's healthful eating or the nutrition
pillar.

2760
03:49:12,521 --> 03:49:18,810
There's physical activity, stress management,
forming positive relationships or connections,

2761
03:49:18,810 --> 03:49:22,550
improving sleep and avoiding risky substances
such as tobacco.

2762
03:49:22,550 --> 03:49:29,180
And I want to draw a distinction between lifestyle
medicine and other fields, such as functional,

2763
03:49:29,180 --> 03:49:32,780
integrative, or alternative medicine.

2764
03:49:32,780 --> 03:49:39,270
Lifestyle medicine is an approach that uses
well-established behavior changes to improve

2765
03:49:39,270 --> 03:49:40,270
health.

2766
03:49:40,270 --> 03:49:47,449
In fact, major guidelines emphasize the critical
role of lifestyle modification in preventing

2767
03:49:47,449 --> 03:49:48,790
and treating chronic disease.

2768
03:49:48,790 --> 03:49:53,729
So this is really quite mainstream.

2769
03:49:53,729 --> 03:50:00,500
So after many years of promoting lifestyle
change as a primary care physician in practice,

2770
03:50:00,500 --> 03:50:07,460
in 2019, I had the opportunity to launch the
plant-based lifestyle medicine program at

2771
03:50:07,460 --> 03:50:09,069
New York City Health and Hospitals/Bellevue.

2772
03:50:09,069 --> 03:50:17,040
And our mission with this program is to provide
intensive support using an interdisciplinary

2773
03:50:17,040 --> 03:50:26,390
team for evidence-based lifestyle modification,
including a more plant-based diet.

2774
03:50:26,390 --> 03:50:32,880
We really aim to reach communities that are
facing inequities, including a disproportionate

2775
03:50:32,880 --> 03:50:39,810
burden of cardiometabolic disease in the community,
as well as structural barriers to even adopting

2776
03:50:39,810 --> 03:50:44,159
a healthy lifestyle in the first place, such
as food insecurity or housing issues.

2777
03:50:44,159 --> 03:50:50,300
And I'm very proud that we are the first program
of its kind in a public health care system

2778
03:50:50,300 --> 03:50:52,620
in the United States.

2779
03:50:52,620 --> 03:50:57,810
Now, I mentioned earlier helping our patients
move towards a more plant-based diet.

2780
03:50:57,810 --> 03:51:02,979
So I want to explain why we chose a plant-based
diet and what that means.

2781
03:51:02,979 --> 03:51:09,460
So a plant-based diet, as we define it, is
really a diet that's rich in fruits and vegetables,

2782
03:51:09,460 --> 03:51:15,621
proteins that come from plants such as legumes,
plant fats like nuts, seeds, avocados, and

2783
03:51:15,621 --> 03:51:19,750
an emphasis on whole grains instead of their
refined counterparts.

2784
03:51:19,750 --> 03:51:24,979
It does not need to be an exclusive...exclusively
plant-based diet.

2785
03:51:24,979 --> 03:51:30,180
Just simply that we're increasing the focus
on these very helpful foods on the plate to

2786
03:51:30,180 --> 03:51:32,760
the extent possible.

2787
03:51:32,760 --> 03:51:38,500
And these plant predominant eating patterns,
really, there's a very compelling wealth of

2788
03:51:38,500 --> 03:51:44,810
evidence around chronic disease prevention
and treatment from coronary heart disease

2789
03:51:44,810 --> 03:51:49,939
to blood pressure, cholesterol, or LDL reduction.

2790
03:51:49,939 --> 03:51:55,870
Prevention of diabetes, improving blood sugar
control in type 2 diabetes, reducing the

2791
03:51:55,870 --> 03:52:02,180
incidence and progression of chronic kidney
disease, promoting healthy weight management,

2792
03:52:02,180 --> 03:52:05,560
and reducing overall cancer risk.

2793
03:52:05,560 --> 03:52:11,020
And again, as I mentioned, for lifestyle medicine,
plant-predominant diets are aligned with numerous

2794
03:52:11,020 --> 03:52:17,310
nutrition guidelines, whether it's for general
health, cardiovascular health, cancer prevention,

2795
03:52:17,310 --> 03:52:20,930
or diabetes prevention and treatment.

2796
03:52:20,930 --> 03:52:27,920
So our program at Bellevue takes adults living
with one or more of these cardiometabolic

2797
03:52:27,920 --> 03:52:28,920
conditions.

2798
03:52:28,920 --> 03:52:35,880
Our referrals are based on referrals internally
from providers through our e-consult system,

2799
03:52:35,880 --> 03:52:39,819
or we can get referrals from our telephone
contact center.

2800
03:52:39,819 --> 03:52:44,569
So we encourage any individual in New York
City who's interested in working on their

2801
03:52:44,569 --> 03:52:48,270
lifestyle and meets our criteria to call our
number and refer themselves.

2802
03:52:48,270 --> 03:52:51,600
And we get many, many referrals that way.

2803
03:52:51,600 --> 03:52:59,439
Our interdisciplinary team uses physicians,
a dietitian, a health coach, an exercise trainer,

2804
03:52:59,439 --> 03:53:02,960
and a program coordinator.

2805
03:53:02,960 --> 03:53:05,409
We have two phases to our program.

2806
03:53:05,409 --> 03:53:12,079
The active phase is six months long and the
support phase is really indefinite after that.

2807
03:53:12,079 --> 03:53:18,189
So in the active phase, each patient will
have 2 to 3 individual visits with every clinical

2808
03:53:18,189 --> 03:53:19,189
team member.

2809
03:53:19,189 --> 03:53:26,411
And the backbone of this phase is our weekly
video group sessions, which involve lifestyle

2810
03:53:26,411 --> 03:53:29,270
education and guided exercise.

2811
03:53:29,270 --> 03:53:34,920
We also offer resources to our patients, such
as cookbooks, resistance bands, and our own

2812
03:53:34,920 --> 03:53:37,390
starter guide to a plant-based diet.

2813
03:53:37,390 --> 03:53:43,409
And in support phase, we continue to have
monthly video support groups to help patients

2814
03:53:43,409 --> 03:53:48,170
continue to have that peer support that's
so beneficial for lifestyle change.

2815
03:53:48,170 --> 03:53:55,319
This is just a list of the different topics
that we cover in our Lifestyle Starter series

2816
03:53:55,319 --> 03:53:56,550
group classes.

2817
03:53:56,550 --> 03:54:00,040
You can see that there's numerous topics related
to nutrition.

2818
03:54:00,040 --> 03:54:03,689
It's very practical, helps meet patients where
they're at.

2819
03:54:03,689 --> 03:54:09,800
Focuses also on fitness, mindful eating, stress
management, and sleep health.

2820
03:54:09,800 --> 03:54:17,040
Our approach from all of our providers is
really to focus on a very patient-centered

2821
03:54:17,040 --> 03:54:19,750
goal setting and action planning approach.

2822
03:54:19,750 --> 03:54:28,140
So we tailor this very carefully to our patients'
cultural background, their family situation,

2823
03:54:28,140 --> 03:54:30,060
their socioeconomic situation.

2824
03:54:30,060 --> 03:54:36,069
We work very hard to help address our patients'
social needs, and we really help to welcome

2825
03:54:36,069 --> 03:54:38,000
any movement towards healthier habits.

2826
03:54:38,000 --> 03:54:43,460
So we tell our patients that they can move
at the pace that they're ready for.

2827
03:54:43,460 --> 03:54:48,710
And we will really celebrate them as they
move along the spectrum towards change.

2828
03:54:48,710 --> 03:54:57,680
In terms of our outcomes, we've had a very,
very robust interest in our program with more

2829
03:54:57,680 --> 03:54:58,939
than 1500 referrals.

2830
03:54:58,939 --> 03:55:03,290
We've taken care of more than 500 patients
since we started.

2831
03:55:03,290 --> 03:55:08,860
We've seen clinically significant and statistically
significant improvements in diet quality,

2832
03:55:08,860 --> 03:55:14,609
physical activity, sleep health, glycemic
control, and body weight.

2833
03:55:14,609 --> 03:55:20,529
And we've had very high patient satisfaction,
which has been so rewarding to see.

2834
03:55:20,529 --> 03:55:25,790
Just sharing a testimonial from one of our
patients who said, "Since starting the program

2835
03:55:25,790 --> 03:55:32,430
four months ago, I've lost 18 pounds, lowered
my blood pressure, lowered my triglycerides,

2836
03:55:32,430 --> 03:55:34,330
and reduced my blood sugar.

2837
03:55:34,330 --> 03:55:36,630
The program is nothing short of life-saving.

2838
03:55:36,630 --> 03:55:42,710
I hope it can continue to be offered to more
New Yorkers."

2839
03:55:42,710 --> 03:55:44,529
And that's exactly what we're going to do.

2840
03:55:44,529 --> 03:55:49,199
So earlier this year, we announced together
with the mayor's office and City Hall, that

2841
03:55:49,199 --> 03:55:55,250
we are going to be expanding our Bellevue
program to six new sites covering all five

2842
03:55:55,250 --> 03:55:59,040
boroughs of New York City.

2843
03:55:59,040 --> 03:56:04,319
With the expansion to our new sites, they'll
be based on the Bellevue program model, but

2844
03:56:04,319 --> 03:56:05,609
with some key upgrades.

2845
03:56:05,609 --> 03:56:12,510
First, we are going to collaborate with behavioral
health by hiring psychologists to work with

2846
03:56:12,510 --> 03:56:17,960
patients in our program, particularly those
who are experiencing disordered eating, emotional

2847
03:56:17,960 --> 03:56:21,870
eating, a history of trauma, anxiety, or depression.

2848
03:56:21,870 --> 03:56:27,899
We'll have community health workers that are
dedicated to our program to help meet our

2849
03:56:27,899 --> 03:56:29,430
patients' social needs.

2850
03:56:29,430 --> 03:56:37,069
We'll have nurse practitioners to co-lead
our shared medical appointments to turn them

2851
03:56:37,069 --> 03:56:38,750
into billable group visits.

2852
03:56:38,750 --> 03:56:45,569
And finally, we're very excited that we have
the ability to offer produce prescriptions

2853
03:56:45,569 --> 03:56:50,720
to all of our patients during the active phase
of the program.

2854
03:56:50,720 --> 03:56:54,620
So where do we go from here?

2855
03:56:54,620 --> 03:57:00,410
I think there's a couple of big research questions
that I would love to see answered.

2856
03:57:00,410 --> 03:57:05,970
The first is how do we implement effective
nutrition-focused programs in traditional

2857
03:57:05,970 --> 03:57:09,540
health care settings like my own?

2858
03:57:09,540 --> 03:57:12,021
How do you design programs?

2859
03:57:12,021 --> 03:57:13,450
Do you focus just on nutrition?

2860
03:57:13,450 --> 03:57:16,470
Do you also broaden to looking at lifestyle?

2861
03:57:16,470 --> 03:57:20,290
Which are the appropriate health professionals
to join the team?

2862
03:57:20,290 --> 03:57:23,710
How do you leverage telehealth in these programs?

2863
03:57:23,710 --> 03:57:25,939
How do you scale these programs?

2864
03:57:25,939 --> 03:57:31,949
Especially when we suspect that our individualized
approach is actually very, very useful for

2865
03:57:31,949 --> 03:57:33,319
patients.

2866
03:57:33,319 --> 03:57:40,120
How do you convince healthcare systems to
invest upfront in a program like this?

2867
03:57:40,120 --> 03:57:44,960
How do you navigate very challenging situations
regarding payor coverage?

2868
03:57:44,960 --> 03:57:51,449
There's so much variability in coverage of
some of these services, for example, dietician

2869
03:57:51,449 --> 03:57:54,600
visits or shared medical appointments.

2870
03:57:54,600 --> 03:57:58,760
How do you address the needs of diverse patient
populations?

2871
03:57:58,760 --> 03:58:05,399
And finally, of course, how do you develop
programs that can address patients' social

2872
03:58:05,399 --> 03:58:07,909
needs while you're also counseling on lifestyle?

2873
03:58:07,909 --> 03:58:13,310
Because we know that goes hand in hand.

2874
03:58:13,310 --> 03:58:17,949
Another question that I have is how do we
define "effective" when it comes to these

2875
03:58:17,949 --> 03:58:20,100
nutrition-focused programs?

2876
03:58:20,100 --> 03:58:22,010
Are we looking just at dietary behavior changes?

2877
03:58:22,010 --> 03:58:29,359
And if so, how do we measure that effectively
in clinical practice, or are we looking also

2878
03:58:29,359 --> 03:58:30,970
at clinical outcomes?

2879
03:58:30,970 --> 03:58:36,890
And obviously some clinical outcomes you see
quickly and others take a long time to see.

2880
03:58:36,890 --> 03:58:39,169
So how do you account for that?

2881
03:58:39,169 --> 03:58:45,430
And of course, how do you really think about
the cost-benefit or the return on investment,

2882
03:58:45,430 --> 03:58:50,489
if you will, for programs like this, especially
when we're really talking about is long-term

2883
03:58:50,489 --> 03:58:55,060
prevention in addition to treating established
chronic disease?

2884
03:58:55,060 --> 03:59:03,690
So I'll stop there and I hope to hear your
thoughts during the Q&A section.

2885
03:59:03,690 --> 03:59:06,350
Thank you.

2886
03:59:06,350 --> 03:59:09,000
DR. ALISON STEIBER: Presentations.

2887
03:59:09,000 --> 03:59:17,850
I think that what you saw today was a breadth
of everything from thinking about very basic

2888
03:59:17,850 --> 03:59:25,590
lifestyle medicine, as we just heard at the
end to very clinical shortages of TPN and

2889
03:59:25,590 --> 03:59:27,380
parenteral nutrition.

2890
03:59:27,380 --> 03:59:34,399
And so what I'd like to do today is start
a little bit with some question and answer.

2891
03:59:34,399 --> 03:59:40,850
And I have a number of great questions in
our Q&A box, but I really encourage the audience

2892
03:59:40,850 --> 03:59:45,300
to submit burning questions that you all may
have for this great panel.

2893
03:59:45,300 --> 03:59:53,739
So I think if we just kind of start out sort
of basically, I think we heard some very interesting

2894
03:59:53,739 --> 04:00:00,729
presentations that talked about dual burden,
that talked about both macronutrient and micronutrient

2895
04:00:00,729 --> 04:00:08,750
deficiencies that related to individuals in
a variety of settings and with a variety of

2896
04:00:08,750 --> 04:00:09,750
disease states.

2897
04:00:09,750 --> 04:00:13,229
But perhaps we start out with obesity.

2898
04:00:13,229 --> 04:00:17,149
So I would love to think a little bit more.

2899
04:00:17,149 --> 04:00:20,229
And I...I think that Dr. Mechanick, this
is probably for you.

2900
04:00:20,229 --> 04:00:24,680
What are just some key practical or clinical
recommendations for patients with obesity

2901
04:00:24,680 --> 04:00:26,890
from a malnutrition standpoint?

2902
04:00:26,890 --> 04:00:31,700
And maybe you can talk a little bit about,
you know, practitioners.

2903
04:00:31,700 --> 04:00:39,330
And I will say as a dietician, we would often
assess the wasting of lean body mass muscle,

2904
04:00:39,330 --> 04:00:41,470
muscle loss, and micronutrients.

2905
04:00:41,470 --> 04:00:45,780
And perhaps our other clinical colleagues
would say, well, that person is overweight,

2906
04:00:45,780 --> 04:00:46,979
they have to be well-nourished.

2907
04:00:46,979 --> 04:00:53,620
And so if you could talk to us a little bit
about why that may or may not be true.

2908
04:00:53,620 --> 04:00:54,630
DR. JEFFREY MECHANICK: Great.

2909
04:00:54,630 --> 04:00:55,630
Thanks.

2910
04:00:55,630 --> 04:00:56,630
Thanks, Alison.

2911
04:00:56,630 --> 04:01:03,699
So, unfortunately, there are still silos even
within the nutrition subspecialty.

2912
04:01:03,699 --> 04:01:08,000
And we have training programs in obesity and
training programs in nutrition.

2913
04:01:08,000 --> 04:01:13,569
And I think the purpose of the talk was that
this dual burden means that when you routinely

2914
04:01:13,569 --> 04:01:20,371
encounter anybody, any patient with obesity
or any place on that adiposity-based chronic

2915
04:01:20,371 --> 04:01:26,930
disease spectrum, that a formal nutritional
assessment ought to be done.

2916
04:01:26,930 --> 04:01:33,260
So I presented some of the data showing statistical
associations, but also mechanisms of poor

2917
04:01:33,260 --> 04:01:38,900
nutrition, malnutrition, undernutrition with
the obese state.

2918
04:01:38,900 --> 04:01:42,020
Even in the ICU, there's always been that
dilemma, right?

2919
04:01:42,020 --> 04:01:46,189
How do you properly feed somebody with obesity?

2920
04:01:46,189 --> 04:01:48,010
So the first thing is a formal assessment.

2921
04:01:48,010 --> 04:01:54,220
The second prong would be your endpoints that
when you're managing a patient with obesity

2922
04:01:54,220 --> 04:02:01,239
or abnormal adiposity, even if it's just ectopic
fat, you need to pay attention to body composition

2923
04:02:01,239 --> 04:02:04,470
and also some of the nutritional markers.

2924
04:02:04,470 --> 04:02:07,899
And David, bringing up the point about inflammation.

2925
04:02:07,899 --> 04:02:12,000
Now we know that obesity is, in fact, an inflammatory
condition.

2926
04:02:12,000 --> 04:02:16,010
So those nutritional markers play more of
a role, right?

2927
04:02:16,010 --> 04:02:23,120
Reflecting some of the adipokines and the
detrimental effects of obesity on an organ

2928
04:02:23,120 --> 04:02:24,120
function.

2929
04:02:24,120 --> 04:02:30,101
And then the third prong would be when you
put together a comprehensive preventive care

2930
04:02:30,101 --> 04:02:31,729
approach.

2931
04:02:31,729 --> 04:02:36,870
And now we start getting into the whole lifestyle
medicine narrative.

2932
04:02:36,870 --> 04:02:43,540
You're talking about nonpharmacologic therapies
for obesity, which include healthy eating

2933
04:02:43,540 --> 04:02:50,850
and nutrition and averting malnutrition, but
also pharmacotherapies and the detriment that

2934
04:02:50,850 --> 04:02:52,739
pharmacotherapies can have.

2935
04:02:52,739 --> 04:02:58,010
And lastly, the lessons we've learned in bariatric
surgery, in our bariatric surgery guidelines

2936
04:02:58,010 --> 04:03:04,409
that a lot of these patients who are rolling
into bariatric procedures already have micronutrient

2937
04:03:04,409 --> 04:03:05,760
deficiencies, right?

2938
04:03:05,760 --> 04:03:13,170
68% to 85% for vitamin D and B12 and even
protein because it dysgeusia.

2939
04:03:13,170 --> 04:03:21,680
So there are a lot of commonalities among
the threats of malnutrition and abnormal adiposity.

2940
04:03:21,680 --> 04:03:23,260
DR. ALISON STEIBER: Excellent.

2941
04:03:23,260 --> 04:03:24,830
Thank you.

2942
04:03:24,830 --> 04:03:26,030
That is exactly right.

2943
04:03:26,030 --> 04:03:31,689
And you really gave us a great entry into
thinking about if I'm a practitioner or a

2944
04:03:31,689 --> 04:03:38,010
researcher and I want to systematically understand
micronutrient deficiencies, perhaps caused

2945
04:03:38,010 --> 04:03:44,700
by something like a shortage within our country
nutrition or just as you just pointed out,

2946
04:03:44,700 --> 04:03:53,350
because we have individuals who may have consumed
too much energy but are deficient in micronutrients.

2947
04:03:53,350 --> 04:03:55,520
How do we assess that?

2948
04:03:55,520 --> 04:04:01,210
You know, if you do it in the hospital, it's
going to be 'A' very expensive biomarker perspective.

2949
04:04:01,210 --> 04:04:07,280
It may or may not represent the actual body
stores, and it takes a very long time to get

2950
04:04:07,280 --> 04:04:08,290
those values back.

2951
04:04:08,290 --> 04:04:13,800
And so I'd like to start out with Dr. Martel,
if you want to address this a bit from your

2952
04:04:13,800 --> 04:04:18,300
perspective, and then others maybe could give
their perspective as well.

2953
04:04:18,300 --> 04:04:23,620
I think a number of the speakers addressed
this question.

2954
04:04:23,620 --> 04:04:30,720
DR. JAY MIRTALLO: Well, if you're talking about biomarkers and
getting these tests available.

2955
04:04:30,720 --> 04:04:35,739
You know, one of the biggest issues we have
is just like what you said, if we want to

2956
04:04:35,739 --> 04:04:40,380
assess micronutrient status, if we don't have
a dietitian that can do the physical diagnosis

2957
04:04:40,380 --> 04:04:44,659
around any of the clinical tests, take a long
time.

2958
04:04:44,659 --> 04:04:50,100
And usually in the hospital, the patient's
gone by the time you get the values back and

2959
04:04:50,100 --> 04:04:56,659
the challenge is then to get the follow-up
for the patients when they're not your patients,

2960
04:04:56,659 --> 04:04:59,350
they were somebody else's that you consulted
on.

2961
04:04:59,350 --> 04:05:04,939
And so, the information comes back at a time
where you don't have access to the patient

2962
04:05:04,939 --> 04:05:08,580
any longer and is kind of a moot point.

2963
04:05:08,580 --> 04:05:13,189
And that's why I made the emphasis in regards
to, you know, we have these diagnostic tools,

2964
04:05:13,189 --> 04:05:19,590
but one is we need to have the experts that
are available to be able to assess those data

2965
04:05:19,590 --> 04:05:20,590
points.

2966
04:05:20,590 --> 04:05:25,170
But we also have to make sure that they're
accessible in all healthcare environments.

2967
04:05:25,170 --> 04:05:31,320
And one of the things we found in Ohio when
we advised the governor with regards to nutrition

2968
04:05:31,320 --> 04:05:35,699
care for elderly patients is one of the biggest
issues we had was the fact that all the hard

2969
04:05:35,699 --> 04:05:41,609
work in nutrition that's done in the hospital
doesn't get transferred to any of the care

2970
04:05:41,609 --> 04:05:47,060
providers that's providing care for the patients
on the outside because the nutrition assessment

2971
04:05:47,060 --> 04:05:52,032
isn't included as a part of the discharge
summary, because the person doing a discharge

2972
04:05:52,032 --> 04:05:56,050
summary doesn't think that that's important
and it doesn't make it on that tool.

2973
04:05:56,050 --> 04:06:01,439
And so, we developed a nutrition screening
tool to be used in any healthcare environment

2974
04:06:01,439 --> 04:06:04,489
for people to identify nutrition risk in the
patient population.

2975
04:06:04,489 --> 04:06:09,820
That's one of the primary focuses of what
we did with that process.

2976
04:06:09,820 --> 04:06:16,279
So, having that information available in regards
to being in any environment, being cheap as

2977
04:06:16,279 --> 04:06:21,380
well as accessible and reliable, never ever
to replace a dietician, I think that's one

2978
04:06:21,380 --> 04:06:24,989
of the other bigger issues with regards to
what I was talking about

2979
04:06:24,989 --> 04:06:30,240
with shortages. It's an access issue and there's
access issues to other things in health care

2980
04:06:30,240 --> 04:06:34,020
that are really needed for us to have a good
system of nutrition support.

2981
04:06:34,020 --> 04:06:35,840
And that is access to people.

2982
04:06:35,840 --> 04:06:40,199
That's a dietician in environments to make
sure that any patient that gets screened positive

2983
04:06:40,199 --> 04:06:44,420
gets a nutrition assessment done by a qualified
individual.

2984
04:06:44,420 --> 04:06:48,479
And it's also the products available as well,
mostly oral nutrition supplements as well

2985
04:06:48,479 --> 04:06:52,069
as medical foods.

2986
04:06:52,069 --> 04:06:56,750
We have a real hard time with policymakers
convincing them that those products aren't

2987
04:06:56,750 --> 04:07:00,780
just meal replacements, but they're medical
nutrition therapy that's needed.

2988
04:07:00,780 --> 04:07:03,820
DR. DAVD SERES: Can I just...

2989
04:07:03,820 --> 04:07:11,311
you know, the flip side of it is that we don't
know what to make of nutrient levels, micro

2990
04:07:11,311 --> 04:07:15,780
or otherwise, in people who are ill because
so many of them are protein bound.

2991
04:07:15,780 --> 04:07:21,680
And, you know, there's this entire literature
on, I've mentioned this before, on vitamin

2992
04:07:21,680 --> 04:07:27,939
D and critical illness as if the low vitamin
D levels were causing the critical illness.

2993
04:07:27,939 --> 04:07:31,240
And it's actually the other way around.

2994
04:07:31,240 --> 04:07:37,810
So, you know, we need to learn how to, and
this was discussed in a prior session, how

2995
04:07:37,810 --> 04:07:46,100
to better assess these nutrients and understand
the meaning of the assessment, and we're far

2996
04:07:46,100 --> 04:07:47,100
away from that.

2997
04:07:47,100 --> 04:07:50,449
And it's part of what I would hope would be
our Moonshot.

2998
04:07:50,449 --> 04:07:57,080
DR. ALISON STEIBER: Right, and so Dr. Seres, you bring
up some great points there.

2999
04:07:57,080 --> 04:08:01,560
When we think about transitions of care, we
think about going out into the outpatient

3000
04:08:01,560 --> 04:08:07,619
clinic or a long-term care facility like you
mentioned in your presentation, and often,

3001
04:08:07,619 --> 04:08:14,109
nutrition care does not travel with the patient,
particularly from an electronic data perspective.

3002
04:08:14,109 --> 04:08:18,979
And so, Dr. Newberry, you mentioned one of the
biggest challenges was identifying patients

3003
04:08:18,979 --> 04:08:21,630
at risk for malnutrition in this outpatient
setting.

3004
04:08:21,630 --> 04:08:27,020
And I would wonder if you could talk about
that a little bit, particularly maybe talk

3005
04:08:27,020 --> 04:08:31,380
about the new screener that was validated
that you put out, and how we can connect those

3006
04:08:31,380 --> 04:08:33,279
dots between inpatient and outpatient.

3007
04:08:33,279 --> 04:08:35,279
DR. CAROLYN NEWBERRY: Right.

3008
04:08:35,279 --> 04:08:38,899
I mean, I think this is a huge challenge and
I think it's one of the reasons why conferences

3009
04:08:38,899 --> 04:08:41,300
like this are so important.

3010
04:08:41,300 --> 04:08:43,859
You know, we don't do a great job of stratifying
patients in the hospital.

3011
04:08:43,859 --> 04:08:46,560
And I think we do an even worse job in the
outpatient setting.

3012
04:08:46,560 --> 04:08:48,189
I think there's a couple of reasons for this.

3013
04:08:48,189 --> 04:08:52,890
I mean, the first is that I think a lot of
providers, we as physicians just aren't trained

3014
04:08:52,890 --> 04:08:55,260
to ask the questions that we need to ask.

3015
04:08:55,260 --> 04:09:00,279
And so, you know, we're not even talking to
patients about oral intake and doing sort

3016
04:09:00,279 --> 04:09:04,510
of like malnutrition, like screening tools
in the first place.

3017
04:09:04,510 --> 04:09:08,989
Even for the small percentage of people that
maybe think about these things, there's not

3018
04:09:08,989 --> 04:09:13,239
a lot of validated tools that can be used
in an outpatient setting, and you don't have

3019
04:09:13,239 --> 04:09:16,630
the data right there for you like you do in
an inpatient.

3020
04:09:16,630 --> 04:09:21,500
And so, I mean, I think until we start addressing
'A', sort of the educational efforts that

3021
04:09:21,500 --> 04:09:25,640
need to be increased for the providers for
taking care of patients that are high risk

3022
04:09:25,640 --> 04:09:31,279
for malnutrition and 'B', coming up with better
screening tools and also intervention tools

3023
04:09:31,279 --> 04:09:33,210
for patients in an outpatient setting.

3024
04:09:33,210 --> 04:09:40,000
It is a hard population to take care of and
it's a lot of research that we need to do

3025
04:09:40,000 --> 04:09:42,479
to better care for these patients.

3026
04:09:42,479 --> 04:09:43,479
DR. ALISON STEIBER: Yes.

3027
04:09:43,479 --> 04:09:44,479
Thank you.

3028
04:09:44,479 --> 04:09:45,479
That's perfect.

3029
04:09:45,479 --> 04:09:48,520
And so, you know, kind of switching now over
to Dr. Sears.

3030
04:09:48,520 --> 04:09:52,630
When you were talking about the long-term
care facility, it feels like not only are

3031
04:09:52,630 --> 04:09:59,050
there challenges maybe from a workforce capacity
angle, but also with policies and thinking

3032
04:09:59,050 --> 04:10:06,439
about how we have structural policies in place
and staffing in place to care nutritionally

3033
04:10:06,439 --> 04:10:10,510
for very high-risk patients in the long term
care facilities anymore.

3034
04:10:10,510 --> 04:10:13,939
DR. DAVID SERES: Yeah, there are.

3035
04:10:13,939 --> 04:10:19,140
It's almost more like a cultural problem than
a policy problem.

3036
04:10:19,140 --> 04:10:24,569
It's the policies of the nursing homes themselves,
not of the state or the Federal Government

3037
04:10:24,569 --> 04:10:26,050
that's driving this.

3038
04:10:26,050 --> 04:10:34,109
And it's based, basically, on urban legend
and complete misunderstanding not only of

3039
04:10:34,109 --> 04:10:43,890
the data that's available, which basically
says there's no difference and the complications.

3040
04:10:43,890 --> 04:10:49,530
People just have these complete biases about,
you know, nasal tubes.

3041
04:10:49,530 --> 04:10:52,380
They're going to cause all these problems.

3042
04:10:52,380 --> 04:10:53,810
And what about gastrostomies?

3043
04:10:53,810 --> 04:10:55,909
I mean, you know, how many?

3044
04:10:55,909 --> 04:11:00,330
We have, you know, to talk to our gastroenterologists.

3045
04:11:00,330 --> 04:11:04,220
We have a hospital that's sort of a catchment
for a lot of the nursing homes in the area,

3046
04:11:04,220 --> 04:11:08,660
and they just spend all day putting in tubes
that have fallen out or become embedded.

3047
04:11:08,660 --> 04:11:10,229
And, you know...

3048
04:11:10,229 --> 04:11:14,080
So I think there's been a lack of attention
on this.

3049
04:11:14,080 --> 04:11:21,700
I think that, actually, we tried to get policymakers
to drive it in the other way, but they wouldn't

3050
04:11:21,700 --> 04:11:22,760
touch it.

3051
04:11:22,760 --> 04:11:30,140
So I think that we need to go out and do some
education and training in these places to

3052
04:11:30,140 --> 04:11:35,330
try to get them to understand that they're
stripping patients of autonomy, basically.

3053
04:11:35,330 --> 04:11:43,900
I mean, they're forcing patients to have gastrostomy
and withholding necessary medical care, meaning

3054
04:11:43,900 --> 04:11:51,340
subacute rehab often enough, and coercing
the patients into having these surgical tubes

3055
04:11:51,340 --> 04:11:52,340
placed.

3056
04:11:52,340 --> 04:11:54,439
And this needs to be changed.

3057
04:11:54,439 --> 04:11:56,090
DR. ALISON STEIBER: Alright.

3058
04:11:56,090 --> 04:11:57,740
Very good.

3059
04:11:57,740 --> 04:12:03,640
I think that as long as we're sort of in this
space of outpatient and that's a great time

3060
04:12:03,640 --> 04:12:05,550
to bring up Dr. Machen.

3061
04:12:05,550 --> 04:12:12,680
You talked a lot about the lifestyle, medicine,
and how you do it, both kind of inpatient

3062
04:12:12,680 --> 04:12:13,680
and outpatient.

3063
04:12:13,680 --> 04:12:18,540
And similar to the last speaker in the previous
session where you really brought up the need

3064
04:12:18,540 --> 04:12:20,960
for plant-based interventions.

3065
04:12:20,960 --> 04:12:22,989
You also have brought that forward.

3066
04:12:22,989 --> 04:12:28,979
And I think as we're thinking about malnutrition
and nutrition support, the idea of bringing

3067
04:12:28,979 --> 04:12:32,109
in plant-based options seems a little out
of sync.

3068
04:12:32,109 --> 04:12:35,320
Do you want to talk a little bit more about
that?

3069
04:12:35,320 --> 04:12:37,400
DR. MICHELLE MCMACKEN: Sure.

3070
04:12:37,400 --> 04:12:43,420
So, I mean, I think that what we're talking
about with our programs is really the reduction

3071
04:12:43,420 --> 04:12:45,310
in cardiometabolic risk.

3072
04:12:45,310 --> 04:12:51,220
And when we look at our patient population
and we think about how we can sort of make

3073
04:12:51,220 --> 04:12:57,479
dietary shifts towards evidence-based eating
patterns that promote reduction in cardiometabolic

3074
04:12:57,479 --> 04:13:03,130
risk, we're really talking about, you know,
as I mentioned, increasing whole fruits and

3075
04:13:03,130 --> 04:13:10,840
vegetables, shifting towards more plant sources
of protein and plant sources of fat and increasing

3076
04:13:10,840 --> 04:13:13,580
whole grains instead of refined grains in
the diet.

3077
04:13:13,580 --> 04:13:19,640
And so there's really wide consensus around
those nutritional principles.

3078
04:13:19,640 --> 04:13:23,439
To your point, I think it is really important
and something that we do in our program for

3079
04:13:23,439 --> 04:13:29,710
any individual who is working on intensive
dietary shifts, we also want to be very cautious

3080
04:13:29,710 --> 04:13:33,310
that they are meeting their macro and micronutrient
needs.

3081
04:13:33,310 --> 04:13:37,229
So one of the wonderful things about our program
is we do have...

3082
04:13:37,229 --> 04:13:43,029
This is a very dietician-centered program
and we currently have a wonderful dietician,

3083
04:13:43,029 --> 04:13:48,020
and we're going to be hiring more, who will
actually be doing medical nutrition therapy

3084
04:13:48,020 --> 04:13:53,210
with our patients and ensuring that, for example,
how do you meet your calcium needs on a plant-based

3085
04:13:53,210 --> 04:13:54,210
diet?

3086
04:13:54,210 --> 04:13:58,569
Are you meeting your protein targets if you're
losing weight and you're increasing your resistance

3087
04:13:58,569 --> 04:14:02,060
training and your physical activity?

3088
04:14:02,060 --> 04:14:03,060
What about other Omega-3s?

3089
04:14:03,060 --> 04:14:07,180
And what about other nutrients that we want
to make sure that we're being cautious about?

3090
04:14:07,180 --> 04:14:08,279
So, and of course, B12.

3091
04:14:08,279 --> 04:14:09,279
Right?

3092
04:14:09,279 --> 04:14:11,260
The ultimate, with a fully plant-based diet.

3093
04:14:11,260 --> 04:14:13,189
So we're very aggressive about that.

3094
04:14:13,189 --> 04:14:19,770
But I think that, not to sort of lose the
forest for the trees.

3095
04:14:19,770 --> 04:14:24,470
I mean, our patients do very, very well when
they eat more whole foods and they're making

3096
04:14:24,470 --> 04:14:25,470
these shifts.

3097
04:14:25,470 --> 04:14:30,000
And as I said, we sort of welcome them to
move as far along the spectrum as they're

3098
04:14:30,000 --> 04:14:31,000
willing to go.

3099
04:14:31,000 --> 04:14:33,989
This is not about telling everyone they have
to be 100% plant based.

3100
04:14:33,989 --> 04:14:39,590
This is about making healthy choices that
are sustainable, that are culturally relevant,

3101
04:14:39,590 --> 04:14:41,989
and that are, most importantly, probably delicious,
right?

3102
04:14:41,989 --> 04:14:45,590
Tastes good and they are something that patients
are going to be willing to keep doing.

3103
04:14:45,590 --> 04:14:46,710
DR. ALISON STEIBER: Absolutely.

3104
04:14:46,710 --> 04:14:47,710
OK.

3105
04:14:47,710 --> 04:14:52,819
Well, I'm going to shift just a little bit
back into the hospital setting and go right

3106
04:14:52,819 --> 04:14:53,819
into the ICU.

3107
04:14:53,819 --> 04:15:00,029
And Dr. Patel, you talked about a variety
of things relating to the ICU, but I think

3108
04:15:00,029 --> 04:15:05,159
it's something that is challenging for a lot
of research, and thinking about our Moonshot

3109
04:15:05,159 --> 04:15:08,350
study is thinking about the right outcomes.

3110
04:15:08,350 --> 04:15:11,619
And so, how do we think about outcomes?

3111
04:15:11,619 --> 04:15:15,170
How do we think about those people who respond
to nutrition information?

3112
04:15:15,170 --> 04:15:17,319
How do we figure out who does not respond?

3113
04:15:17,319 --> 04:15:21,340
Is that part of our malnutrition diagnosis
process?

3114
04:15:21,340 --> 04:15:26,670
And then maybe think a little bit about short
versus long-term outcomes.

3115
04:15:26,670 --> 04:15:30,670
I wonder if you could just touch on those
things for us.

3116
04:15:30,670 --> 04:15:38,250
DR. JAY PATEL: Thank you, Alison, for that question.

3117
04:15:38,250 --> 04:15:40,790
There is certainly a lot to unpack there.

3118
04:15:40,790 --> 04:15:47,430
But what I will say is that I think there
has been a tremendous paradigm shift in the

3119
04:15:47,430 --> 04:15:51,199
way we think about nutrition in the ICU.

3120
04:15:51,199 --> 04:15:56,680
And so over the past decade, for example,
there have been a lot of trials that have

3121
04:15:56,680 --> 04:16:02,819
been conducted with the use of supraphysiologic
doses of micronutrients to mitigate some of

3122
04:16:02,819 --> 04:16:06,300
the acute effects of critical illness.

3123
04:16:06,300 --> 04:16:10,939
And so the paradigm has shifted such that
nutrition is beyond just sort of a passive

3124
04:16:10,939 --> 04:16:18,330
form of support, but now it's used as a form
of therapy or particularly related to micronutrients.

3125
04:16:18,330 --> 04:16:23,160
When we relate to macronutrients, we can almost
think the same way as well where we can suggest

3126
04:16:23,160 --> 04:16:29,630
that, you know, giving small amounts of macronutrients,
at least in animal models, seems to suggest

3127
04:16:29,630 --> 04:16:33,900
that there's preservation of things like the
epithelial barrier function.

3128
04:16:33,900 --> 04:16:39,180
So if I go in reverse order, what I'm really
getting at here is that I think future trials

3129
04:16:39,180 --> 04:16:45,729
and studies really have to start to form,
you know, a biologically plausible threat.

3130
04:16:45,729 --> 04:16:49,660
And that biologically plausible threat has
to start with, you know, asking questions

3131
04:16:49,660 --> 04:16:53,530
like what is it that we want this nutrition
to actually accomplish?

3132
04:16:53,530 --> 04:16:58,250
And if it's that we're trying to preserve
the epithelial barrier function and prevent

3133
04:16:58,250 --> 04:17:02,790
all the detrimental effects of an impaired
barrier function, then we have to demonstrate

3134
04:17:02,790 --> 04:17:04,319
that that's actually what's going to happen.

3135
04:17:04,319 --> 04:17:08,859
It's also going to be really important that
we sort of partner with our basic scientists

3136
04:17:08,859 --> 04:17:10,399
in trying to figure that out.

3137
04:17:10,399 --> 04:17:17,380
Once we establish sort of the biological link
that macronutrients provide in certain subsets

3138
04:17:17,380 --> 04:17:22,420
of critically ill patients, for example in
patients with sepsis, then the goal is to

3139
04:17:22,420 --> 04:17:26,751
say, you know what, by preserving the epithelial
barrier function, we're going to have less

3140
04:17:26,751 --> 04:17:29,520
complications such as, you know, infectious
risks.

3141
04:17:29,520 --> 04:17:32,050
Patients might be able to get off the ventilator
faster.

3142
04:17:32,050 --> 04:17:38,699
And in looking at more patient-centered outcomes,
since patients are surviving critical illness

3143
04:17:38,699 --> 04:17:44,040
more they are today compared to, say, you
know, even a few years ago, the patient-centered

3144
04:17:44,040 --> 04:17:48,090
outcomes are going to be important, then ultimately
are going to be looking at things like, you

3145
04:17:48,090 --> 04:17:53,950
know, is the nutrition that I receive in the
ICU truly helping me, 'A', get off the ventilator

3146
04:17:53,950 --> 04:17:58,390
faster, 'B', helping me ambulate a little
bit better, 'C', that improve my quality of

3147
04:17:58,390 --> 04:18:04,460
life, 'D', along those same lines, help me
with my muscle function and what that's sort

3148
04:18:04,460 --> 04:18:05,720
of need it for.

3149
04:18:05,720 --> 04:18:07,370
Now, what do we have so far?

3150
04:18:07,370 --> 04:18:11,830
In terms of all the data that's been produced
from contemporary randomized controlled trials,

3151
04:18:11,830 --> 04:18:20,020
we have trials that have looked at the effect
of nutrition in just the first 4 to 7 days

3152
04:18:20,020 --> 04:18:21,480
of ICU stay.

3153
04:18:21,480 --> 04:18:26,819
And then we want the nutrition that's provided
in that first week of ICU to have an impact

3154
04:18:26,819 --> 04:18:31,640
on mortality 30, 60, 90 days, six months out.

3155
04:18:31,640 --> 04:18:35,010
And you know, if you were a layperson, you
might look at and say, "Well, how is that

3156
04:18:35,010 --> 04:18:36,010
supposed to happen?

3157
04:18:36,010 --> 04:18:38,120
How can you give me a little bit of nutrition
and have an impact?"

3158
04:18:38,120 --> 04:18:42,290
Because the nutrition journey for patients
doesn't end at ICU discharge.

3159
04:18:42,290 --> 04:18:46,409
It continues well beyond survivorship.

3160
04:18:46,409 --> 04:18:51,710
And so, I think that we need to study so we
can, again, demonstrate that biological link.

3161
04:18:51,710 --> 04:18:57,550
I think we need to focus on subsets of critically
ill patients that may derive the most benefit

3162
04:18:57,550 --> 04:18:59,989
from our micro and macronutrients.

3163
04:18:59,989 --> 04:19:05,180
And then I think that for some macronutrients
we have to perhaps stop thinking of nutrition

3164
04:19:05,180 --> 04:19:12,180
as, you know, a drug where the effect is immediate
and maybe we should reserve that for some

3165
04:19:12,180 --> 04:19:18,460
of the micronutrient studies where we might
see an immediate effect as well.

3166
04:19:18,460 --> 04:19:23,310
DR. ALISON STEIBER: So, so many interesting points, as
you say, lots to unpack.

3167
04:19:23,310 --> 04:19:29,390
But when we think about, for example, the
WHO's definition on malnutrition, it is both

3168
04:19:29,390 --> 04:19:31,949
a macro and micronutrient issue.

3169
04:19:31,949 --> 04:19:39,140
Clearly, we don't have tools that are validated
or biomarkers that encompass all there is

3170
04:19:39,140 --> 04:19:42,400
to look at when we think about assessing for
nutrition.

3171
04:19:42,400 --> 04:19:45,609
So I think that's a really important piece.

3172
04:19:45,609 --> 04:19:49,840
And because of that, I'm going to David, Dr.
Sears here.

3173
04:19:49,840 --> 04:19:57,130
We don't really know in the best way possible
how to comprehensively say someone has malnutrition

3174
04:19:57,130 --> 04:19:58,130
or not.

3175
04:19:58,130 --> 04:20:00,430
We're sort of the individuals with the elephant.

3176
04:20:00,430 --> 04:20:05,369
We're blind trying to figure it out, and thus
we have a difficult time, I think.

3177
04:20:05,369 --> 04:20:10,159
And David, you would say how do we know who's
going to respond to our intervention and

3178
04:20:10,159 --> 04:20:14,710
not only just purely who's going to respond
to this intervention, but which interventions

3179
04:20:14,710 --> 04:20:17,070
are going to be best for which types of patients?

3180
04:20:17,070 --> 04:20:19,910
And so I don't know if you want to touch a
bit on that.

3181
04:20:19,910 --> 04:20:23,000
DR. DAVID SERES: Yeah, no, this is the message

3182
04:20:23,000 --> 04:20:30,270
throughout is that, and I've said this before,
I'd really rather we not use the term malnutrition.

3183
04:20:30,270 --> 04:20:37,260
And how different is the term malnutrition
from cachexia and the other terms that we

3184
04:20:37,260 --> 04:20:44,900
use when we're describing this combination
of inflammation and its consequences and starvation

3185
04:20:44,900 --> 04:20:45,989
and its consequences?

3186
04:20:45,989 --> 04:20:50,250
And what are the consequences of starvation
in the context of inflammation?

3187
04:20:50,250 --> 04:20:51,640
And all of these are...

3188
04:20:51,640 --> 04:20:56,330
This is what's being built up in this whole
conference is this question of, you know,

3189
04:20:56,330 --> 04:20:59,670
how do we know who is going to respond?

3190
04:20:59,670 --> 04:21:04,780
And fortunately, there is at least some data
on who is not.

3191
04:21:04,780 --> 04:21:07,130
So anyway, thank you for asking the question.

3192
04:21:07,130 --> 04:21:10,859
It really is, I think, the most important
one of the entire conference.

3193
04:21:10,859 --> 04:21:18,140
DR. ALISON STEIBER: I guess finally, in our last couple
of minutes here, I want to throw that question

3194
04:21:18,140 --> 04:21:19,140
to the group.

3195
04:21:19,140 --> 04:21:24,920
You know, in our previous session, we talked
a lot about cutting-edge ways of identifying

3196
04:21:24,920 --> 04:21:33,100
potential malnutrition or micronutrient deficiencies
through the microbiome and through different

3197
04:21:33,100 --> 04:21:34,560
tracers and isotope mechanisms.

3198
04:21:34,560 --> 04:21:39,310
But really for this session, we've actually
talked about very practical issues.

3199
04:21:39,310 --> 04:21:41,869
And Dr. McMacken, I think you said it best.

3200
04:21:41,869 --> 04:21:47,050
How are we going to implement these in an
equitable way, which we don't create more

3201
04:21:47,050 --> 04:21:55,021
disparity by having such expensive, difficult-to-use
methods of diagnosis that we miss the population

3202
04:21:55,021 --> 04:21:56,550
that needs it the most?

3203
04:21:56,550 --> 04:22:01,510
And so I would just throw out to you all as
a group, how do we implement malnutrition?

3204
04:22:01,510 --> 04:22:08,520
How do we build awareness and implement our
ability to screen and diagnose, and intervene

3205
04:22:08,520 --> 04:22:09,520
for malnutrition?

3206
04:22:09,520 --> 04:22:16,920
I won't do that, "I'll call you" thing unless
everybody is very silent and then I will.

3207
04:22:16,920 --> 04:22:18,500
DR. JAY MIRTALLO: Well, I have a thought on this.

3208
04:22:18,500 --> 04:22:19,500
This is Jay.

3209
04:22:19,500 --> 04:22:25,140
And I think one of the basic things that's
been threaded through the whole discussion

3210
04:22:25,140 --> 04:22:30,560
is that we're talking to each other at a very
high level with regards to nutrition care,

3211
04:22:30,560 --> 04:22:33,700
nutrition practices, and nutrition skill.

3212
04:22:33,700 --> 04:22:39,409
And what we see in the healthcare environment
is a big disparity in what we know

3213
04:22:39,409 --> 04:22:44,890
and what we can do versus what the other clinicians
and what our compatriots can do.

3214
04:22:44,890 --> 04:22:46,090
I'm a pharmacist.

3215
04:22:46,090 --> 04:22:51,250
I'm not sure very many other pharmacists other
than the 600 board-certified pharmacists in

3216
04:22:51,250 --> 04:22:54,350
nutrition can do what I do in relationship
to that.

3217
04:22:54,350 --> 04:23:00,260
I think a large portion of what we see is
a lot of nutritional cripples coming to us

3218
04:23:00,260 --> 04:23:06,350
as experts because the main core of health
care practitioners don't have a good understanding

3219
04:23:06,350 --> 04:23:12,609
of where nutrition fits in the overall care
and health of a patient population.

3220
04:23:12,609 --> 04:23:14,830
And so they don't know what to do with it.

3221
04:23:14,830 --> 04:23:16,080
They're not educated well in it.

3222
04:23:16,080 --> 04:23:19,760
There's not a consistent thread with regards
to all their training.

3223
04:23:19,760 --> 04:23:23,850
And so I think one of the basic core components
is that we need to educate our healthcare

3224
04:23:23,850 --> 04:23:30,320
practitioners on just being able to recognize
that nutrition is important to outcomes, it's

3225
04:23:30,320 --> 04:23:34,409
important to the quality and health of a healthy
living person.

3226
04:23:34,409 --> 04:23:39,649
And it's very important to the health and
recovery of a patient that survived an ICU

3227
04:23:39,649 --> 04:23:40,649
stay.

3228
04:23:40,649 --> 04:23:46,250
And unless we can get those groups on board,
a lot of what we talk about, is really

3229
04:23:46,250 --> 04:23:48,941
not going to impact what we really want to
impact.

3230
04:23:48,941 --> 04:23:54,859
And that's good nutrition across all healthcare
environments and all healthcare settings.

3231
04:23:54,859 --> 04:24:00,810
And so everyone from, we just did the nutrition
screening in a pharmacy and identified nutrition

3232
04:24:00,810 --> 04:24:01,810
risk.

3233
04:24:01,810 --> 04:24:05,409
And our main problem is we didn't have access
to a dietician to do a nutrition consultation,

3234
04:24:05,409 --> 04:24:10,659
but we do see the patients every 30 to 60
days so we can establish goals for them and

3235
04:24:10,659 --> 04:24:16,830
follow up with them in regards to what they're
doing, with regards to our objectives for maintaining their hypertension.

3236
04:24:16,830 --> 04:24:23,930
Similar to your, Dr. Mechanick, your "Food is Medicine"
kind of principle, but we're just starting

3237
04:24:23,930 --> 04:24:28,060
in that. We're just pharmacists and so we
need to have an interdisciplinary group that

3238
04:24:28,060 --> 04:24:30,170
can work with us to do that.

3239
04:24:30,170 --> 04:24:34,699
And so we see these pockets of excellence
in nutrition, but there's not enough of them

3240
04:24:34,699 --> 04:24:37,000
to handle the nutrition problems that are
out there.

3241
04:24:37,000 --> 04:24:42,449
I often wondered when I was practicing in
the hospital, you know, we see these patients

3242
04:24:42,449 --> 04:24:47,729
come into our cancer hospital and they say,
well, we want to do another course of chemotherapy.

3243
04:24:47,729 --> 04:24:51,100
But they had ignored that person's nutrition
for the past three months.

3244
04:24:51,100 --> 04:24:56,310
So, they've handed to me a nutritional cripple
and expect us to create a miracle so that

3245
04:24:56,310 --> 04:24:58,479
they could do another course of treatmentw

3246
04:24:58,479 --> 04:24:59,659
And it's like, Why?

3247
04:24:59,659 --> 04:25:06,359
When we've got such great products and things
available, does this happen when we've got

3248
04:25:06,359 --> 04:25:10,409
bright people that we're working with that
have just missed the boat with regards to

3249
04:25:10,409 --> 04:25:13,260
nutrition and thought about it too late.

3250
04:25:13,260 --> 04:25:15,090
So...and I’ll get off my soapbox and [inaudible] let anybody else talk about it, 

3251
04:25:15,090 --> 04:25:20,110
but I think that's one of the core problems
we have, is making sure that our everyone

3252
04:25:20,110 --> 04:25:25,032
in healthcare can identify and assess for
nutrition risk and be able to know what to

3253
04:25:25,032 --> 04:25:27,130
do with it once they find it.

3254
04:25:27,130 --> 04:25:31,430
DR. DAVID SERES: Just do a little self-promoting here.

3255
04:25:31,430 --> 04:25:38,520
The organizers of this meeting also agree
with you, Jay, that educating practitioners

3256
04:25:38,520 --> 04:25:39,729
is critical.

3257
04:25:39,729 --> 04:25:42,870
And there are some sessions coming up on this.

3258
04:25:42,870 --> 04:25:52,500
And ACGME is actually calling a summit that
it'll be next spring to try and discuss this

3259
04:25:52,500 --> 04:25:53,500
issue.

3260
04:25:53,500 --> 04:25:55,350
So it's fortunately making...

3261
04:25:55,350 --> 04:25:58,760
It's percolating up at least.

3262
04:25:58,760 --> 04:26:00,240
DR. ALISON STEIBER: Right.

3263
04:26:00,240 --> 04:26:02,890
Well, I think we are at time.

3264
04:26:02,890 --> 04:26:06,290
This has been a terrific discussion.

3265
04:26:06,290 --> 04:26:11,939
And you all were magnificent in your presentations
and we really appreciate your time for this

3266
04:26:11,939 --> 04:26:13,029
workshop.

3267
04:26:13,029 --> 04:26:16,690
So, I think that concludes this session.

3268
04:26:16,690 --> 04:26:22,760
And I want to thank everyone and thank all
the audience for participating and for sticking

3269
04:26:22,760 --> 04:26:25,449
with us on a long afternoon.

3270
04:26:25,449 --> 04:26:30,979
And we hope that you will come back tomorrow
because, as David just said, we have a great session

3271
04:26:30,979 --> 04:26:36,311
on thinking about training a workforce in
diversity and enhancing diversity in the nutrition

3272
04:26:36,311 --> 04:26:39,311
space. So, thanks to everyone. Have a great evening.