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Podcast with Orestis Panagiotou, Elizabeth White, and Marlon Aliberti 2

Nursing home residents have been devastated by COVID.  Somewhere around 40% of deaths from COVID have been among nursing home residents, though they make up just a sliver of the US population.

Prognostication among nursing home residents who have COVID is important for a host of reasons – for counseling patients and families about what to expect, for making clinical decisions, and potentially for allocation of scarce resources such as treatments.

In today’s podcast, we talk with Orestis Panagiotou and Elizabeth White, the authors of a JAMA IM study that finds that physical and cognitive function are key predictors of mortality prediction for nursing home residents with COVID.  We also talk with Marlon Aliberti, who authored a commentary.  

Physical and cognitive function are easy to assess measures that should be routinely captured for older adults, in nursing homes and elsewhere.  Study after study document the importance of function to risk prediction.

We also have a brief debate about how vaccinations should be allocated – according to a “one size fits all” age criteria, or a prognostic model that individualizes risk.  Though I’m an advocate for prognostic models (see eprognosis.org) I’m actually on the age criteria alone side of the debate, with generous distribution among hardest hit minority communities. 

And sing along to This Little Light of Mine!

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TRANSCRIPT

Eric: Welcome to the GeriPal Podcast, this is Eric Widera.

Alex: This is Alex Smith.

Eric: And Alex, we have a full complement of guests today.

Alex: We have a full complement today. Today we have Orestis Panagiotou, wonderful Greek name, who’s an epidemiologist and health services researcher in faculty at the Brown School of Public Health. Welcome to the GeriPal Podcast Orestis.

Orestis: Thanks for having me, nice to meet you.

Alex: And we have Elizabeth White who is an investigator in the School of Public Health at Brown and a geriatric nurse practitioner. Welcome to the GeriPal Podcast, Elizabeth.

Elizabeth: Thank you, nice to be here.

Alex: And joining us from Brazil, we have Marlon Aliberti, who is a geriatrician and clinical researcher at the University of Sao Paulo in Brazil. Welcome to the GeriPal Podcast Marlon.

Marlon: Thank you for having me. It’s a pleasure to be here.

Eric: I am super excited about this topic. There has been a lot of discussion about COVID in nursing homes and the high mortality rates. Where I live the vast majority of deaths are taking place in nursing homes, and it’s hard to actually make sense of what does it actually look like as far as mortality rates for nursing home residents. So I’m really excited to have all of you. We’re going to be talking about a JAMA IM paper that came out called Risk Factors Associated With All-Cause 30-Day Mortality in Nursing Home Residents With COVID-19. And we’ve also invited Marlon on to join us because he wrote the editorial, Beyond Age, improvement of Prognostication Through Physical and Cognitive Functioning for Nursing Home Residents With COVID-19. So lots to unpack here, but before we do we all start off with a song request who has a song request today.

Elizabeth: I think that was mine. Since we’re talking about COVID In Nursing Homes, which isn’t the cheeriest of topics and we’re talking particularly about dying from COVID, but I thought we could do something a little uplifting and a song about resilience to begin with, so I chose This Little Light Of Mine which I think is kind of nice.

Alex: (singing)

Eric: That was fabulous Alex, maybe at the end, all of our listeners can join us singing that song. Well, we can’t sing because zoom actually destroys the syncing. Anyway, I think this is a fascinating topic. With news today out of Europe, the… I think she is the second oldest person in the world, French nun, who is a 116 years old, survived COVID-19, and is looking to celebrate her 117th birthday on the day of this podcast is going to be released. So we hear all of these issues around mortality rates and COVID, and how bad it is for older adults and how bad it is for nursing home patients, that I’d really love to unpack kind of what this all means and I loved your article. Before we go into that, maybe we can just start off with, how did you guys get interested in this as a topic?

Elizabeth: So I can probably just provide a little context of how we got involved with us early on, and the pandemic became very evident that this was just absolutely devastating nursing homes and other long-term care facilities. And since the beginning of the pandemic, I mean long-term care residents have representatives anywhere from about 78% of cases, but about 40 percent of the deaths, and that’s been a pretty consistent trend since the beginning. And it also became evident early on is that we just didn’t have good data to understand what was happening in the nursing homes.

Elizabeth: So, even back in March and April, the researchers that tend to do research in nursing homes, and we were all scrambling to just get data from State Departments of Health, and it just wasn’t being systematically collected, it wasn’t even until May that CMS, the Medicare program began, requiring that nursing homes report data to them. So we work with a large nursing home FIDA, that since the beginning has shared all their electronic medical record data with us, because they really wanted to understand what was happening for their own purposes, and also just to help advance the science and understand what was happening. So this is a collaboration that started back in March, we’ve had a number of papers investigating various aspects of covid in nursing homes since then and this is a particular paper trying to get into some of the nuances of which patients in nursing homes are at greatest risk for adverse outcomes, because it’s not just a universally vulnerable population.

Orestis: And I think our group of Brown is not new to this field, is not that we just jumped into this opportunity, we have been doing work in nursing homes and long-term care for a long time. So this was just a natural extension of our previous work before COVID to tackle another important public health problem in this really vulnerable population.

Eric: I mean we go a little bit more into the why. Why is this important? We know COVID is really not good in older adults, every additional decade mortality rates look worse. We know COVID in nursing homes for older adults is even worse. What were you hoping to really drill down to accomplish?

Orestis: So I think one question that hadn’t been addressed is exactly how can we stratify these patients. CDC was putting out some estimates and risk factors, but they were really at the high level, so no one had really combined them into a single number to try to tell people that not everyone has all those factors has none of those factors. So when you start combining a really big number of individual factors, you get people who are all over the place in terms of the risks. So we’re going to see more specifically how some of these risk factors look like in the nursing home population and how can we use this information to really identify at a very granular and finer level whether individual risks are. And some potential, for example, implications of why this work might be important or what longer-term questions one might answer with this work is, you can think of risk based interventions or risk-based vaccination.

Orestis: We have a supply issue right now in terms of vaccines and people who may want to somehow prioritize who will get vaccinated. one potential way to make some decision would be to identify those who are at higher risk and prioritize those over someone who might be in the lower end of the risk distribution, and they want to get technical, but some of these is really, what are the practical implications of knowing someone’s individual risk? And how can we stratify patients and target interventions if there is, without constraints in terms of resources, for example?

Eric: Yeah. And Marlon you wrote the editorial for this, when you saw what they were trying to do, did you think this was important? Did you think what… the question they were trying to ask was the question you wanted to hear?

Marlon: Yeah. It just extremely important. It’s interesting that as geriatricians, we are trying to fight against ageism, just saying that age is a very important risk factor in COVID-19, we already know that, but we need to know better how to differentiate among those with similar age, who are those who have high risk and I think studying a prognosis in nursing room or in nursing room environment, It’s the perfect place to understand other factors, and these factors are normally age-related impairments as you notice related to cognitive environment and physical environment as important risk factors to differentiate older people, those who can go better and those can go worse after getting COVID. So I think it’s extremely important to talk.

Eric: So today’s date that we’re recording, this is Wednesday February 10th, in the US numbers are dropping pretty dramatically throughout the US, definitely here in California. Marlon can you just describe what’s happening in… you’re in Sao Paulo, right?

Marlon: Yeah.

Eric: What’s happening in Sao Paolo, right now?

Marlon: Well, we are in the second wave in Brazil as a whole. Sao Paulo is the biggest city in Brazil in South America, so we are having many cases right now, very similar to that we have in April and May is still, we are trying to improve vaccination to try to overcome this pandemics, but right now we have a lot of many cases is still.

Eric: And in nursing homes too?

Marlon: Well, Brazil is different from the US and other developed countries. Yes, we have many cases in nursing home, but we have few older adults living in nursing home. We have a culture that older people is still lives with their family, so we have 10% of people living in nursing home compared to the US for example, but even having a few people living in nursing home, our mortality rate is very similar to the US and other countries in Europe, For example.

Orestis: That sounds very similar to the Greek situation, where we keep most of our older adults with family members and try to minimize the nursing home stays as much as possible. Even after an acute hospitalization that goes to a slightly different topic, but nursing homes are not the standard post-acute care setting in Greece and glad to hear it from Marlon as well.

Eric: Yeah, and for those listeners if you want to hear what life is like in a nursing home during a surge in an outbreak, we’ve had previous podcasts back, and what was that, April, Alex?

Alex: April where we’ve had several. Yeah, we’ve had one with Jim Wright, I believe about a podcast in a nursing home in Virginia. And then we had another one with folks from Indiana University about how things are going there and just devastating impact on nursing homes. How are things in Providence Rhode Island and the East Coast right now, Elizabeth?

Elizabeth: Yeah. I mean, we’re fortunately starting to come down the peak a little bit. I can say, we’re looking at the nursing home data across all the states for the provider that we work with, which is about 25 states across the country and fortunately, we’re kind of on the other side of the peak. It’s interesting because that’s also coinciding with when all the vaccinations started, so in the United States most nursing homes are being vaccinated through CVS and Walgreens, which is in arrangement where they get three separate vaccine clinics and that varies in some states, but the provider that we work with, they’re just about to finish with their second clinics, and they’re seeing pretty good vaccination rates and we’re actually, as part of our work, we know that cases are coming down, but we’re looking to see, how much of that is attributed to vaccinations,] the normal being the other side of the Peaks.

Alex: What do you mean Elizabeth when you say three separate vaccination clinics in the nursing homes?

Elizabeth: So the way they’re setting it up just because of the sheer volume of nursing, I mean, there’s 15,000 nursing homes in the country and the number of nursing homes that have to be vaccinated, the residents and the staff and them, so the CVS and Walgreens Partnerships, so essentially, they come in they do one clinic and then they get as many residents and staff as they can during that first clinic, then they come back depending on whether they give the Pfizer, the Moderna in three to four weeks to give …

Elizabeth: … dose two and then also to give dose one to anyone who did not receive it during the first clinic, and then a few weeks later, they have a third Clinic, where they come back and they give the dose twos for the people who got their first dose in the middle clinic. So it’s been quite a logistical operation and an important point that’s coming up now is that, we’re doing a pretty good job of vaccinating the residents, but this is a transient population, people get admitted to nursing homes, people get this vaccines, there’s going to be a constant flow of people coming into nursing homes, also new staff that come in, so there’s going to need to be systems in place to continue these vaccinations overtime, it can’t just be the three clinics and we gone.

Alex: Do you have the sense from the huge provider that you work… Is it the largest provider of nursing homes in the country, which makes me think that anonymity is not quite as important.

Elizabeth: Yeah. And I should say… they’ve been very transparent and we’ve been using their name throughout, so actually, it’s Genesis Healthcare, we’ve been using their name throughout our work, I think in this particular paper we didn’t, but they’ve been transparent about this.

Alex: Okay. Thank you. And how about the staff, vaccination rates among staff has it seemed to be acceptable and are staff getting vaccinated, there were paper published in JAGS recently out of the group at Indiana, showing that staff were very leery of getting vaccinated.

Elizabeth: Yeah. And it’s certainly been a challenge. There was MMWR report that came out. I think that was last week using national data from CVS and Walgreens, and then also the national parallel data that only reported about 38% of staff had been vaccinated across the country not specific within Genesis, they just released their numbers I think last week around time as well, they’re seeing vaccination rates around 61% for the staff, so they’re doing a little bit better, but this is an ongoing challenge and there’re a lot of investment across, I think all nursing home providers to educate staff, support staff, help them to get to a point where they’re accepting the vaccine because, I mean, that’s the number one priority right now.

Alex: Yeah, as it should be. Well, let’s talk about that because you know part of the role of the vaccine for the staff is to decrease the… What we often think is the highest risk for dying from getting COVID, the nursing home residents. Can we talk a little bit about the JAMA study? Can you just get a nutshell, what did you guys do in this study?

Orestis: So we used as a Veterinary student or Elizabeth mentioned we use data from about 350 nursing homes in the US and we were fortunate to have access both to the electronic medical records of the provider that we collaborated with as well as MDS assessments that are routinely conducted in nursing homes. So we use information from both of those sources in order to identify risk factors that are based on what was being published at that time, we thought would be important to examine the nursing home population plus some additional ones like cognitive function and physical function that together can be an indicator of frailty, we use this they’re not routinely collected at least in such large scale, they’re maybe some small studies here and there, some clinical cohorts or case series that people go after patients and do measure those things, but in a large-scale outside MDS, it’s uncommon to find this information.

Orestis: So we thought to going to see how much can we improve our prediction or stratification of mortality, if we add those factors that may be unique indicators of frailty among older adults, how much do we gain if we add them on top of existing risk factors that we knew already from clinical studies and CDC? And actually we did see that we can stratify people better at least older adults in nursing homes, we can stratify them better if we just don’t consider comorbidities and symptoms, but we also look or we incorporate into our assessment measures of frailty. And then we saw quite a big of them in increasing this stratification by adding cognitive function and physical function alone.

Marlon: We have been reading many papers making quite essence against electronic and medical records that we cannot achieve good information for them, but you choose the opposite, you had a very good experience in combining different electronic and medical records, I would like to ask you the challenges to do that, and if you thinking providers can combine those information easily to offer better care for older adults in nursing home.

Orestis: I think the answer is probably yes and no to some extent. It takes quite some time, so there was lots of work that was done behind the scenes by other members of our team trying to combine this information, because they live in separate data sets sometimes, we have to do some data cleaning to identify these measures, so we really had great support from IT colleagues of ours, who could really master these data sets and create the information that we needed. I think part of the answer to your second question is, I think it’s really up to whoever collects the data to make the extra effort. It’s definitely feasible to integrate some of these measures and electronic health records especially if there’s a single provider that has access to both assessments of physical function or other care-sub assessments and the electronic medical records.

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Orestis: So most of the time in my experience ends up being an IP issue where different systems are not really communicate the information exists, but we have to make the extra step to combine this information. And then we know whoever the user is, it might be provide physician who uses this electronic medical record, and that medical record is set up in that way that it can… So what is the physical function of that patient over time, and running some models behind the scenes is not computation problematic nowadays, the most important issue is how do we allow this systems to talk to each other.

Eric: Looking at your paper, It looks like if you just look at the results, 1 out of 5 nursing home residents will die if they get COVID. So that’s one prognostic factor, I’m just going to use one, if I add another prognostic factor in addition to nursing home patients, just age, it looks like if you’re less than 65, one out of 20 will die, and if you’re greater than 90, over one out of three will die, so age seems to be a really important factor and it sounds like you’re saying that there are other things too, some that, we may traditionally get and some like physical functioning which are a little bit harder in the EMR, when you think about what you found in this study as far as important factors for mortality, what were they?

Alex: Wait, can I guess? I want to guess.

Eric: Alex is going to guess.

Alex: I’ve been reading all these papers about prognosis for people with COVID and Eric has been writing about it, so I think I have a good guess. The first would be this disease affects the lungs and that’s why people get sick. So people with chronic conditions it affect the lungs, so I’m going to go with COPD chronic obstructive pulmonary disease, as a really important risk factor in nursing home residents. Second would be, we know people who are febrile, right, high risk for death or who have low oxygen level, hypoxia, so those are the three I’m going to go with, risk factors for nursing home residents, is how’d I do.

Elizabeth: So you will, so I think we going to lay symptoms. Interesting, we going to find that COPD was a predictor in this particular population. There are other studies out there that have certainly people that have underlying chronic lung disease, that’s certainly a risk factor. The two comorbidities that were had strong association with mortality in our sample, were diabetes and chronic kidney disease, there’s been some other work out there that has looked at CKD as being a predictor. The underlying mechanisms of that, I think are still being figured out, whether it’s related to underlying information or just these patients tend to be… Have other comorbid illnesses, if it’s… ACE receptors play an important role in how the virus gets into the cells.

Elizabeth: So, I mean, it was kind of an interesting point that diabetes and CKD were the only chronic conditions that we identified. We did identify much stronger relationship with the level of cognitive impairment and functional impairment, and kind of our hypotheses around that is, one, that these are both important indicators of frailty, and we know that frailty is a geriatric syndrome that in and of itself is an important predictor of mortality, but also it goes to the point and we were talking about staff earlier is that people that are more functionally impaired need more help and just, they need to be in… Somebody who needs help with bathing and they need help with toileting and that can’t be done in a socially distanced way, so they need more prolonged contact with staff which can potentially influence, the amount of virus that they’re infected with, the viral load at time of infection, and there’s been some evidence that may be related to severity of illness. So, there are a couple of underlying explanations there, one that it’s just an indicator of frailty but then also maybe potentially around the mechanism of how people are being infected.

Marlon: I think another aspect very interesting of the paper that many prognostic paper is on COVID, and focus on lab tests on a laboratory findings and doing that in a nursing home, you could not use that. So you need to provide a prognostic information apart from a laboratory findings, and I think it was very interesting to show how those information that we can get that on the bad side, we can have good perspective of how older adults can perform after getting COVID, so it’s very interesting as well.

Orestis: I was just going to say that was a great point and I think what you’re alluding to perhaps is what is the use of having a prognostic tools, you can do perhaps a perfect job if we start measuring all those markers, but now if we need three or four days for the labs to come back while the time that the patient or the stuff goes into the patient’s room, we can measure these things and we can build an electronic tool that tells us what is ones probability, even having a lower or less precise calculator can still be very valuable compared to all those fancy perhaps labs that take time to come back, and you need to put an extra burden on patients by having to draw blood and especially during the pandemic have an extra contact might not be the ideal situation. So one can balance this.

Eric: So I work in a nursing home, and I know if my patient, what their age is what their functional and cognitive status is, let’s say I can put all this in and I can get in it, what do I do? What should I do with this information? And I even just looking at like, okay I know with… If you look at age cognition and function, that looks really bad individually, a little bit and just from your perspective, should I treat the patient differently? Should I focus on something differently? What should I do with this information?

Elizabeth: Yes, I think from the clinical perspective, I think knowing these types of factors are really important in terms of prognostication and in terms of having a conversation with the resident, with the family about, both, where’s the best place to treat the person and what are the best kinds of treatment to provide to that individual? So, a lot of nursing home residents during COVID, had been maintained in the nursing home, because it’s primarily supportive care, much of which can be provided in house and plus then you’re saving the person a trip to the hospital and all the everything that comes along with that. And also just knowing that this is in a population that does well in ICU is on ventilators. So I think having these data and having the nuance of this, helps to inform the discussion with the family, with the resident about where’s the best place to treat the person? Is it supportive management in the nursing home? Maybe it would be appropriate just to put the person in the hospital and provide some more advanced treatment. Also, we’re seeing in the last month or two, an increase in the use of monoclonal antibodies with the nursing homes.

Elizabeth: Here in Rhode Island, they actually administer them through the field hospital, that we have set up and they developed a pretty efficient relationship with some of the nursing home. So I think just making those decisions of who may benefit best for different treatments can also just having a very realistic goals of care discussion about how to maximize the quality of life for a person who is sick with COVID.

Eric: Mm-hmm (affirmative).

Marlon: In my opinion, although this paper is about prognostication, it can also support how personal protective equipment is important for nursing home. We have very difficult situations as the pandemic start, 12 months or 30 months ago. And we see how those with cognitive impairment and physical environment are the most vulnerable to the pandemic, and they need a close care, so we should provide a real equipment for the providers and we need to protect our older adults in nursing home, so I think this is an important message of the paper that we can get as well.

Elizabeth: And Marlon, it’s such an important point. I mean, unfortunately back in March and April, nursing homes and other long-term care settings, assisted living facilities, were simply just not given the same priority as hospitals were for PPE. And there were real supply chain issues that were particularly affecting the long-term care sector in those early months, and those have largely improved. I mean, there are still a number of facilities that are reporting shortages, but we actually have some related work that we’re doing, we’re looking longitudinally at mortality rates and we’ve seen since the early months of the pandemic that mortality rates within nursing homes have declined, and we have a paper that’s in press right now, that should be coming out soon by that, that’s led by one of our doctoral students Cyrus Kosar.

Elizabeth: But there has been an improvement over time, improvement in PPE supplies certainly part of that, also just learning how to manage these population, potentially changes in the virus itself, there are a number of kind of different explanations that we’re exploring but it’s very important point.

Eric: And I loved your title Marlon, in your editorial, it was Beyond Age. There’s something more than age, and I think this is tough, and there’s a lot of messaging right now, like why are we in the US focused on those greater than 75, because they have 300 times higher chance of dying from COVID than those younger than 65, so there’s a lot of focus on. This is why we’re doing this, we’re kind of being hammered with this idea, age. We ought to focus on age, get the vaccine out as much as possible for those are 75. Does this study argue that maybe we shouldn’t just be looking at age? Maybe we got to look a little bit more cognitive function, physical function, the environment they’re in, like in a nursing facility, and I’m looking at your graphs, Age Cognition and Function, and man, they kind of look similar in some ways, they seem equally important. Should we be thinking about it more than just age?

Marlon: I think this is a very important aspect. As I said before, we have a lot of ageism during the pandemic, saying that just older people should stay home or should do physical distancing, and just saying that age is important, we forgot to go deeper and analyzing older adults as and it resents group of people that we can have older people that have a very low risk of mortality, despite having being 85 years old, so I think this message is very important, just simple but is very important.

Eric: I guess another question is, should we be rethinking how we’re doing lets say even vaccinations? Should it just be focused on age or should we be thinking about not just comorbidities but function cognition, prioritizing other groups first?

Orestis: So yeah. I think the more information that we can consider to predict once the risk of outcome, the better it is. It’s just that we know that most of these… We can achieve probably some decent risk certification based on age and comorbidities or maybe this might not be the same in younger patients, because the majority of younger patients may not have physical disabilities or may not have cognitive impairment issues. So you do not gain much by adding physical function or cognitive function in these individuals while you can do gain more in older adults. So at the end of the day, I think it becomes a resource allocation problem and some of the work that we did definitely can inform this decisions, hopeful even when the CDC came up with their chart with a different boxes to try to create some ranking, essentially this chart implies that there are some factors that make the different groups have different risks.

Orestis: Now to what extent the same information can be measured and applied to all? I think that’s an issue that has to do with how do we measure some things that we think are valuable. That’s why I said earlier, we’re lucky that we have this information for our nursing home population, but this might not be easily measurable in the outpatient clinic, where someone goes for their diabetes medication, right. So how do we have this information? Probably things might be different, and it’s difficult to say that young should consider this if we don’t really have the data tool to test some of these hypotheses.

Alex: I want to push back on this idea a little bit. The San Francisco Chronicle called me a couple weeks ago and asked me, they said, “People with disabilities who are younger are riled up, because they are no longer prioritized in California under the new distribution policy, its people over 65 are next, whereas they would have been further up in the queue had they stuck to the original in a multi-tiered complex plan.” And I said, “Look, I’m a researcher, I study prognosis, Eric and I have this website that we prognosis.” You all have studied prognosis, obviously. Marlon had a paper about frailty as a prognostic marker, I think that was an aging recently, and yet at this time, we need to invoke a public health ethic, and the ethics and public health as we’ve talked about in this podcast previously with Doug white are different from the ethics of clinical encounter with a patient in the exam room or at the bedside.

Alex: And in this case we need to do the most good for the most people, and I think we can all agree that when it comes to outcomes that are important from COVID, that death is the most important outcome and it’s quite clear that older age is a tremendous marker of mortality, and the most important and easily measured marker getting back to your pointer Orestis, but what-

Eric: And maybe not the most important from this study Alex, but the most easily measured, because it’s functioning cognition and I’m looking at their paper-

Alex: That’s in nursing homes.

Eric: In nursing.

Alex: Because your statement before about 300 times the risk was not compared to eight people younger than 65, it was actually compared to people in their 20s on the CDC website. So when you’re looking across the spectrum of people who are going to get vaccinated overall, I think, absolutely right to start with nursing homes one, and then two absolutely right to continue by vaccinating older adults, and that’s different I should know from what we have talked about in this podcast before which is, Rationing Scarce Treatments for COVID, where we’ve argued that age… Some have argued that age should be included, and some have argued that it shouldn’t, and I’ve come to the side that it shouldn’t be included and that we should rely on other risk factors for mortality from COVID alone.

Alex: But I don’t think we can practically have a risk calculator to determine everybody’s individual risk, and then allocate scarce vaccine resources according to the algorithm, we just can’t do that. This is public health, We got to do the most good for the most people and build public trust in that system, so that’s my push back against that idea. I’ll get off myself.

Orestis: Yeah. I think it’s a fair point. speaking of the public health perspective, there are still many fears, for example, nursing home by itself, is there are various factors that we haven’t really studied as far as I know, for example, just being in the nursing home regardless of age because it’s a congregate setting definitely increases your risk compared to being at home, right, So then you have the comparison between community-dwelling, people of any age versus older people who are at the nursing home, which is an extra risk factor by itself.

Orestis: So I think it’s a complicated decision based on what we can measure among which individuals and how do we make these allocations, because some of these issues for example do exist in renal transplant, right, there is a registry and these are allocations, again, it’s problems that are solved by resource allocation methods which go beyond the simple prognostic tool, like if you have to think of the supply, you have to think of the consequences, if you don’t give it to one what happens to the next person, and some of those issues are not always of the same way that across interventions, like a vaccine which has no side effects versus a drug that is metabolized differently in younger and older people, we still have to factor these decisions, risk and benefits into our decision-making.

Eric: Yeah. And I will just, I mean, I really love this paper. We’ve been talking about mortality. I think this paper is equally important and you flip it around is that, four out of five people in nursing home survive COVID, at least at 30 days. Less than two out of three people with cognitive impairment or functional… People survive and I think that’s a really important part of having these discussions and that there is risk factors that increase mortality rates and that just highlights the importance of how to actually have these discussions with patients and family members about risk, and both being honest and hopeful but also realistic not fatalistic, not that nobody survives, but finding that right balance and I thought this paper gave me balance.

Marlon: I think another aspect it’s very interesting in this paper. Although we have selective population comprising only those with symptomatic COVID-19, we have very low prevalence of the typical symptoms, for example, one in five had shortness of breath, one in two had fever, but you have a right selected those with asymptomatic disease. So, how do you say something about the asymptomatic or nonspecific symptoms in the nursing home…

Elizabeth: Yeah. I think it’s the old saying that older adults don’t read the textbook, I mean and we certainly have seen that you also see it’s not just, not manifesting a fever at all, but if they do manifest a fever, the definition of fever in a frail older adult is different than it is for someone like me. So we do see that when they do have a fever it tends to be… You have to use a lower threshold to classify that. So when we’ve have investigated asymptomatic infection in this population as well interestingly, we find that about the same proportion of cases in the nursing home population is in the general population about 40% or asymptomatic and that kind of opens the whole another, carrying worms around, transmission and really drives home why frequent surveillance and diagnostic based on low thresholds of suspicion for infection or exposure are so important in this setting, because there is so much asymptomatic infection.

Alex: Were you able to look at delirium, which I know has come up, confusion, Louise Aronson talked about it on this podcast, why aren’t we modifying our criteria for older adults who have different presentations often with things like confusion?

Elizabeth: Yeah. It’s another great point and this kind of goes to Orestis, pointing about being able to measure it. So the tool that we use, Well, we don’t really have a tool to measure, we don’t have the CAM or another delirium tool built specifically into the EMR, we do see, the fairly high proportion of people with COVID that do have other symptoms documented, agitation or other things that may be symptomatic of delirium, but we don’t have a good measure of it.

Eric: Well, I want to be mindful of time. I want to thank all of you for joining us today. This is outstanding editorial Marlon, and I really appreciate the work that you guys are doing.

Marlon: Thank you.

Eric: And I also think you know one day even after COVID, there will be an article of it. This is a really important paper to think about and I think Marlon’s editorial highlights, this is when we think about prognostication not just relying on age, but thinking about other factors that may be harder for us to capture an EMR but are equally important, so thank you for that knowledge. But before we leave… go ahead, Orestis.

Orestis: I want to say that probably this is one of the things that can stay because COVID most likely is going to stay around even after vaccination, so there will still be people who might be infected. So continue to know one’s risk of dying, once they get infected and have symptoms I think is going to be important even if we don’t face a pandemic anymore.

Alex: Right and there will be other pandemics, then general points sticks that in older adults functions so critically important, physical function, cognitive function to prognosis for every condition.

Eric: Yeah. Well, that’s the little light that we need to shine in geriatrics over and over again. Functioning cognition, Let It Shine, Alex you want to give us a little bit more of that.

Alex: (singing)

Eric: Awesome. Thank you all for joining us on this podcast and the amazing work that you do.

Orestis: Thank you so much for having us.

Eric: And I want to thank all of our listeners for joining us for this podcast and supporting the GeriPal Podcast. Please, rate us on your favorite podcasting app, it certainly helps us, and a big thank you to Archstone Foundation for your continued support. Good night everybody.

Alex: Good night.

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