Hello, and welcome to today's Journal Club Critical Care Medicine webcast. The webcast hosted and supported by the Society of Critical Care Medicine as part of the Journal Club Critical Care Medicine series. In today's webcast, we feature two articles from the June issue of Critical Care Medicine. The webcast will be available to registrants on demand within five business days. Simply just log into mysccm.org and navigate to the My Learning tab. Hello everyone, and my name is Tony Gerlach. I'm a clinical pharmacist at Ohio State University Medical Center in Columbus, Ohio, and I will be the moderator for today's webcast. Thank you for joining us. Just a few housekeeping items before we get started. First, during the presentation, you'll have the opportunity to participate in several interactive polls. When you see a poll, simply click on the bubble next to your choice. Second, there'll be a question and answers or Q&A session at the conclusion of the presentation. 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And now I'd like to introduce both of our presenters for today. First is Georgia Kara, who is a PhD student at the Laboratory of Intensive Care Medicine at KU Leuven in Belgium, Netherlands. She is a biomedical engineer by training, and in her PhD, she uses advanced analytics to unravel complexities or complex links between multiple physiological signals and neurological outcomes with the goal of improving quality of care for different types of neuromonitored patients. Her research focuses on children that undergo cardiac surgery and on patients with severe traumatic brain injury and subarachnoid hemorrhage. Dr. Lauren Ferrante is an assistant professor of medicine in the section of pulmonary critical care and sleep medicine at the Yale School of Medicine, and she's the director of operations core at the Yale Claude D. Pepper Older Americans Independent Care Center. Her research program is centered at the interface of critical care medicine and geriatrics with the overreaching goal of understanding and improving the functional outcomes of critically ill older adults. Her work is currently funded by the Paul B. Beeson Emerging Leaders in Aging Career Development Award from the National Institutes of Aging and the Yale Claude D. Pepper Older Americans Independent Center. Clinically, she is an attending physician at Yale New Haven Hospital, where she cares for patients in the medical intensive care unit in the post-COVID recovery program. Thank you both for joining us today. Now I'll turn things over to our first presenter, Georgia Kara. Thank you very much, Dr. Gedlack, for the nice introduction, and welcome everyone. Today I will present our study, recent study published in Critical Care Medicine, entitled Postoperative Cerebral Oxygen Saturation in Children After Congenital Cardiac Surgery and Long-Term Total Intelligent Quotient, a Prospective Observational Study. I have no conflict of interest, but I want to state that I am an engineer, so I was, I performed the analysis of the study, but I'm not involved in the treatment of patients, so I cannot provide any kind of clinical recommendation. Every year, seven out of 1,000 children born with congenital heart disease, or CHD. CHD are characterized by a structural deformation to the heart of great vessels, and can have enormous repercussions on the cardiac functioning and systemic blood circulation of the child, to the extent that about 25% of cases require corrective surgery in the first year of life. In the last years, advances in pediatric intensive care have reduced mortality, unveiling new challenges. In fact, these children often suffer from long-term neurodevelopmental deficits, such as neurocognitive impairment, speech and language problems, attention deficits, and learning disabilities. Common causes can be linked with the poor neurological outcomes of these children. First, children with severe cases of CHD often present lesions to the grey and white matter tissue of the brain, due to inflammation, hypoxic, or ischemic events that occur not only during the gestational period, but also in the entire perioperative period. Neurodevelopmental deficits might be the result also of genetic problems that often accompany CHD, but they can also be related to factors of the clinical practice. Different causes could be potentially linked with the poor neurological outcomes of these children, and I'm sure that this list is not really exhaustive. But in the specific case of children with CHD, white matter lesion is believed to be one of the main factors that determines the neurocognitive outcomes. As a consequence, clinicians try to improve the cerebral oxygenation of the children during their stay to improve the outcomes. In a pediatric setting, clinical perfusion can be monitored non-invasively with the near infrared spectroscopy, or NIRS, which measures the cerebral tissue oxygen saturation, or SCTO2, of the frontal lobe of the child. In fact, this technology is based on two electrodes that are placed on the forehead of the patient. Despite NIRS is a promising tool for the neuromonitoring of children with CHD, the range of physiological SCTO2 values is not well defined yet, and it remains unclear whether there is a range of SCTO2 values to target, not only to reduce mortality, but also to improve the long-term outcomes of these children. Different studies have tried to answer to this question, and in particular, reduced SCTO2 has been associated in the pre-operative period with lower psychomotor development and lower developmental quotient, while reduced SCTO2 in the post-operative period has been associated with longer length of stay, longer duration of mechanical ventilation, and major morbidities after surgery. However, it remains unclear whether reduced SCTO2 in the post-operative period is also linked with long-term neurocognitive deficits. This is exactly the goal of our study, where we investigated the association between SCTO2 in paediatric patients after surgery for CHD and long-term total IQ. To do that, we analysed the post-operative continuous SCTO2 recordings from 87 children admitted in the paediatric intensive care unit of KU Leuven between 2012 and 2015. In particular, we extracted from the first 12 and 24 hours after surgery two features, the mean SCTO2 and the dose of the saturation. The saturation was defined as SCTO2 below 65%, while the dose is a composite measure that takes into consideration not only the intensity of an ICP event, but also its duration in time. So we analysed the association between these two features and the total IQ two years after PICU admission. And we did that with the Bayesian linear regression model, which was corrected for the age of the patient, the nutritional strategy, presence of syndrome, presence of cyanosis after surgery and pimitry. I will just give a very brief introduction about Bayesian statistics, because I think it is relevant to later understand the result. In traditional statistics, the linear relationship between two variables is classified with coefficient beta. However, we know that the sample that we observe represents only in part the general population and that the real beta coefficient of the general population may differ from the one obtained in our study. Bayesian regression takes this uncertainty into consideration and expresses the regression coefficient beta in terms of probability distribution. In other words, we will have the probability of each possible value of beta. So we will have values that are more likely than others. Also in Bayesian statistics, we call 95% credible interval the range of values to which beta belongs with a 95% probability. Another advantage of Bayesian statistics is that it's possible to include prior knowledge into the model. So when we provide prior knowledge, we indicate whether the probability of an event increases or decreases given a specific condition. Let me give you an example. So in this study, we set priors for the syndrome and synoptic cardiopathy. So what we integrated into the model is the knowledge that children with syndrome and children with synoptic cardiopathy are likely to have lower total IQ than other children with CHD, but not syndrome and synoptic cardiopathy. Also it sets priors for the SETU2 predictors, but I will go real quick on it. We set the neutral prior where we assume no association between SETU2 and outcomes, optimistic prior where we assume that SETU2 desaturation is associated with worse outcomes, and skeptical prior when we assume that SETU2 desaturation is associated with better outcomes. So for the cohort, as I mentioned before, we included 87 children which were admitted in the paediatric intensive care unit of the Hospital of Leuven. The age at surgery of these children, the median age of surgery was four months, and 64% of the children were males. Also all children presented quite low PIMTRI score, which resulted in a quite low probability of death. 89% of children underwent cardiopulmonary bypass, and only 4% did hypothermic circulatory arrest. Now let's move to the result, but first let me explain to you what I will display in the table. So here there are the two features we analysed, the saturation dose and mean SETU2. And the results are presented in terms of posterior beta estimates with 80% credible interval. What does it mean? It's the most likely beta estimate of the probability distribution and the range of values to which the beta estimate of the general population belongs with the 80% probability. So if we look at the example we saw before, the most likely value in this case will be 1, and the credible interval will be something around between 0 and 2. Also the second result we provide is the probability that the posterior beta estimate is strictly negative or positive, which means the probability that we will have a positive association or a negative association. So looking at the example above, you can notice that the majority of the beta values are positive. So for example, we might have a 97.5% probability of a positive association between the two variables. Now let's move to the results. I will just present the result of the neutral prior for the first 12 hours of SETU2 monitoring, but the results are quite comparable. So there is a 90% probability that the desaturation dose is negatively associated with total IQ at two years follow-up. In other words, increased dose of SETU2 is associated with a 90% probability of lower total IQ two years after PICU admission. Similarly, there is a 90% probability that the mean SETU2 is positively associated with total IQ at two years follow-up. So there is a 90% probability that reduced in SETU2 is associated with reduced total IQ two years after admission. To check for the robustness of these results, we also performed three sensitivity analysis by defining desaturation with different desaturation thresholds, by adding as additional correcting factor the educational status of the parent or the duration of cardiopulmonary bypass. All three of these sensitivity analysis provided consistent result, giving an idea of the robustness of the model we created. Now, I want to provide you a very practical example of what does it mean, the practical implications of our findings. So I invite you to look at the image below that represent the SETU2 recording of a child. And I refer to the orange line. The dashed gray line indicates the 65% threshold of desaturation, and the pink area represent the dose of SETU2 desaturation. Now I want to think about, and I will read the question, what is the drop in IQ points according to our study associated with the event of desaturation in the example below? A, a drop from 1 to 6 IQ points, B, a drop from 5 to 11 IQ points, or a drop from 4 to 15 IQ points? OK, so all of you answered a drop from 5 to 11 IQ points. Actually, the correct answer is a drop from 4 to 15 IQ points, which, as you can imagine, is quite a striking result. Now, let's move to a second example that might be a little bit more interesting, different type of example, same question. So I invite you all to look at the image below. Here, the patient did not really experience drastic, let's say, events of desaturation, but still the SETU2 was always constantly below the desaturation threshold of 65%. So what is the drop of IQ points associated with the event of desaturation in the example below? A drop from 0 to 4 IQ points, a drop from 2 to 7 IQ points, or a drop from 5 to 12 IQ points? Again, I invite you to check what is the answer for you. OK, all of you answered from 5 to 12 IQ points. Actually, in this case, the correct answer is from 2 to 7 IQ points. And so lower than what most of you think. But still, I remind you that this is a type of event to which probably that would not really trigger a clinical intervention because the SETU2 levels are way above what is now considered severe desaturation. Thank you for answering the poll. So the study has some limitations, and it's very important to acknowledge them. First is a single-centre design, so external validation is required. It's an observational study of prospectively collected data, so we can prove association, but not causality. There are a couple of niche-related limitations that need to be taken into account. We only focused on the first 12 and 24 hours after surgery, and we did not stratify among children with and without cyanosis, even though probably the saturation threshold may vary for this type of children, and no information on possible causes of desaturation. We did not include information about possible causes of desaturation in our study. So to conclude, in critical-yield children admitted to the paediatric intensive care unit after a CHD surgery, increased dose of desaturation and lower mean SETU2 in the first 12 and 24 hours of monitoring time, independently increased the probability of a lower total IQ at two years follow-up. Whether intervention to prevent saturation and reduce mean SETU2 in the first 12 and 24 hours of monitoring time would result in improved outcomes remains to be investigated. And with this, I want to thank you for your attention. I want to thank everyone who was involved in the study, Professor Mehua, Dr Giza, Professor Van der Berg, and all the research and clinical team of the Laboratory of Intensive Care Medicine in KU Leuven, and I turn it over to Dr Ferrante. Thank you so much, Dr. Kara, and thank you everyone for being here. Today I'll be discussing our study, Functional Effects of Intervening Illnesses and Injuries After Critical Illness in Older Persons. I have no conflicts of interest to disclose, though I do need to disclose my funding. So I'm currently funded by a Beeson Award from the National Institute on Aging, a COVID supplement also from the National Institute on Aging, and the Yale Pepper Center. So it's widely known that critical illness is a potent precipitant of functional decline in older persons, and we know that among older adults who have survived an ICU stay, that nearly half will not achieve functional recovery within six months of an ICU hospitalization. And just to be clear, in prior work, when we've looked at trajectories of function after a hospitalization, after six months, these tend to plateau. So if somebody is going to recover, they tend to do so within six months. And we expect that these numbers are only going to increase as the population ages. So in 2015, there were approximately 1.9 million ICU hospitalizations among patients age 65 and older in the United States. And that's with a population of older adults at about 50 million. That's a 2017 estimate. And by 2050, there will be about 94.7 million older adults in the U.S. And not achieving functional recovery means that an older adult is living with new or worsened disability. So disability is defined as dependence in activities essential to independent living, also known as functional activities. And these generally fall into three categories, activities of daily living, instrumental activities of daily living, and mobility activity. And I will give you an example of these in a future slide. And it's important to note that disability is associated with a number of downstream consequences, including institutionalization, which of course represents a loss of independence for the older adult, greater use of both formal and informal services, increased caregiver burden, and overall increased healthcare costs to society. So in prior work conducted by Terry Freed that was published in the Archives of Internal Medicine in 2011, with follow-up studies subsequently published in the New England Journal, Dr. Freed asked older adults to rate which health outcomes were of greatest importance to them. And when older adults were presented with a list of health outcomes, the vast majority of them rated maintaining independence as their most important health outcome priority. And you can see here that 76% of them chose maintaining independence. Staying alive was actually a distant second at 11%. And so this is our first polling question for this study. So which health outcome was rated as most important by a majority of older adults in a 2011 Archives of Internal Medicine study? Was it A, staying alive, B, pain relief, C, symptom relief, D, maintaining independence, or E, walking without an assistive device? But for those of you who chose maintaining independence, that was the correct answer. So in thinking back again to functional activities or activities essential to independent living, I had mentioned that there were three categories of activity. The first category is activities of daily living or ADLs. These include basic activities such as bathing, dressing, walking across a room, or transferring from a chair. Instrumental activities of daily living are higher order activities such as shopping, housework, meal preparation, taking medications, and managing finances. And mobility activity includes activities such as walking a quarter mile, climbing a flight of stairs, lifting or carrying 10 pounds. And for our intents and purposes, we also include driving a car here, which is an advanced activity. And you'll see here that if you add up the activities on this page that they form a total of 13 functional activities. So for the next polling question, which of the following describes disability in a functional activity? A, using a cane to ambulate, B, depending on a caregiver to transfer to a chair, C, using a shower chair to bathe, D, relying on eyeglasses to read the newspaper, or E, relying on a raised toilet seat to use the toilet. Okay, great. So whoever selected depending on a caregiver to transfer to a chair, and it looks like that was all of you, that is the correct choice. And that's because, again, disability means that the person is dependent on another person to execute the functional activity. So using a cane or using a raised toilet seat, those are actually, a cane is an assistive device, and a toilet seat is an accommodation, so that a person can still execute the functional activities themselves. So that does not make them disabled in that activity, they're still able to conduct that activity with the use of an assistive device. So in prior work, there have been many factors associated with disability and recovery among older ICU survivors. We've done a lot of this work and have identified that certain factors such as pre-ICU frailty. In a different study, we looked at cognitive impairment. We've also done some work on functional trajectories. We found all of these factors to be associated with post-ICU disability. And that body of work had largely focused on pre-ICU vulnerability factors that are more likely to be present among older adults than younger adults, and weren't traditionally thought of as being associated with long-term outcomes, but are obviously very important for older adults. But it's important to acknowledge that events may occur after the index hospitalization too. So events such as hospital readmissions, emergency department visits, and episodes of restricted activity can occur after somebody survived an ICU hospitalization and now they're in the recovery period, in the months after discharge. And so just to clarify what I mean by episodes of restricted activity, this is when somebody might not feel well or might be sick or having symptoms that require them to spend some time in bed or lying on the couch, where they're not so sick that they need to go to the emergency department or be readmitted to the hospital, but they're not up and about and conducting their daily activities in a normal way. And so our objective in this study was to evaluate the functional effects of these illnesses and injuries in the year after a critical illness hospitalization. For this work, we use data from the Precipitating Events Project, which has been based at the Yale Program on Aging since 1998. In that year, 754 community dwelling, non-disabled older adults were enrolled, and they've been followed all the way through to this day with monthly assessments of hospitalizations, emergency department visits, restricted activity assessments, and disability in the 13 functional activities that I showed you on a previous slide. And they've also undergone every 18-month comprehensive in-home assessments of a battery of different tests, basically everything that would comprise a comprehensive geriatric assessment. This is not the complete list that I've listed here. I was just trying to give some examples of what is assessed at this 18-month visit. And we link the Precipitating Events Project to Medicare claims data to facilitate the identification of ICU admissions. So for our outcomes, again, I just want to remind you that we use the disability count, which ranges from zero to 13, where disability is defined as dependence in the functional activities that I listed on that prior slide. And we consider the pre-ICU functional baseline as being measured in the month before the ICU admission. And I want to remind everyone that all of these participants have prospective monthly functional assessments. So the baseline that we have was prospectively measured before the person was admitted to the ICU in the subsequent month. And then we have post-ICU disability counts for every month in the year after discharge from the ICU hospitalization. So our primary outcome was functional recovery, which is defined as when the post-ICU disability count returns to the pre-ICU baseline. And our secondary outcome was functional decline. And so for this outcome, we looked in each month after discharge from the ICU hospitalization to see if there was any increase in the disability count from month to month. And we defined functional decline as being an increase in the disability count of at least one activity of daily living, or at least two instrumental or mobility activities from one month to the next. So this is our flow diagram for the study. We started out with 754 participants. And to allow for proximity of covariates, we selected the first ICU admission in each 18-month interval, which left us with 420 ICU admissions. We then excluded the 68 admitted from a nursing home and 13 who were maximally disabled, just because there's no room to get any worse if you already have maximum disability. And because this is a study of ICU survivors, we also excluded in-hospital deaths. And we also excluded hospice patients because their functional goals are not necessary recovery. 21 additional people died before the first follow-up interview. And we eliminated eight that had occurred within 12 months of a prior ICU admission. So this left us with 250 ICU admissions from 209 community living participants who survived to the first post-ICU interview. And I actually should have had this slide before the last one, but just to go over the statistical analysis. So for the primary outcome, we used a Cox model to evaluate bivariate and multivariable associations between each of the intervening events and time to functional recovery. So participants who had not recovered were censored at time of death, withdrawal from the study, or the end of the 12-month follow-up period. And in our multivariable model, we had eight factors from a prior functional recovery model that we had published. We also included the number of months from the start of that interval to the ICU admission and an indicator for calendar time. And then we have looked at another comprehensive set of variables, which are presented in table one, just to ensure that nothing else should be included in the multivariable model and use backward selection here to reveal that ICU length of stay should also be added to the model. So the multivariable model included all of these factors. And I should mention that for the secondary analysis of functional decline, that was a logistic regression model. So this is our table one, where we describe the characteristics of the overall cohort of ICU survivors, again, with our sample size being 250. The mean age in years was 82.3. And a little more than half of our sample was of female sex, which is pretty normal for a study of older adults. And then in looking at geriatric factors, the mean number of chronic conditions was about two and a half out of nine. About 18% had cognitive impairment. And the mean pre-ICU disability count, again, measured in that month before the ICU admission was about 4.1. And it's also worth noting that sensory impairment, hearing and vision impairment are pretty prevalent among older adults, and that about 43% of them were frail, as classified by the Freed Frailty Index. The low percentage in mechanical ventilation is due to the fact that this is a cohort of ICU survivors. Whenever we go back one of these studies and just take a step back to look at our overall number of ICU admissions, of course, the percent that are mechanically ventilated are much higher, but many of those people died during the hospitalization. So for our results, the mean time to functional recovery was 3.2 months, which is consistent with what we found in our prior work. And for the secondary outcome, the mean number of months with functional decline was about 2.2 out of the 12. There were 541 months with functional decline, where about a third were due to ADL decline only, 42% due to IADL or mobility decline only, and about 26% due to decline in both, in all categories, so ADLs plus IADLs or mobility. I found this very interesting because usually when somebody is becoming disabled, mobility and IADLs tend to go first, although I suppose this ADL decline, we didn't describe here whether somebody already had disability and IADLs or mobility, I would expect that to be the case because IADLs usually tend to go after, I'm sorry, ADLs tend to go after IADLs and mobility. So this is one of the figures from our paper that basically looks at the primary analysis. And these are the three intervening events in the year after critical illness by functional outcome. And I'd like to draw your attention to this first row here, the dark gray, which is our primary outcome of functional recovery. Again, whether or not the person returned to their pre-ICU functional baseline. And you can see here that the rates of all three intervening events are higher among older adults who did not achieve functional recovery in the year after a critical illness. However, the only one that was statistically significant was exposure to a hospitalization. So here, if you did not achieve functional recovery, you had about a three-fold increase in exposure to a hospitalization during the year after critical illness, as opposed to people who did achieve functional recovery were less likely to be hospitalized. And again, you can see that these trends are consistent here but not statistically significant. And here, this is just showing our multivariable model results. By having this forest plot here, it's just much easier to visualize that the effects that are seen with hospitalization are much larger and statistically significant as opposed to the other two intervening events. Although here, you can see that ED visits are significant for the outcome of functional decline as well. So in summary, intervening illnesses or injuries leading to hospitalization, ED visit, or restricted activity were common in the year after critical illness. And importantly, exposure to intervening hospitalizations was nearly three-fold higher in the absence versus presence of functional recovery. Intervening hospitalizations were significantly associated with a lower likelihood of functional recovery. And intervening hospitalizations and emergency department visits were each significantly associated with a higher likelihood of subsequent functional decline. So that was the month-to-month look at functional decline over the year after a critical illness. And so when thinking about the implications of this study and also just some additional food for thought, this sort of raises the idea that strategies for improving functional outcomes after a critical illness might focus most intently on intervening hospitalizations. And in taking this to the next step, I tried to think about whether any of these might have been preventable. And I know everyone on this webinar, you're all SCCM members, so you would have access to the supplement that's published along with this article. And in the supplement, there are detailed tables that include the reasons for the different intervening events. And so when you look at hospitalization, the most common categories were infection and cardiac. For ED visits, cardiac, musculoskeletal and infection, and fatigue and dizziness or unsteadiness for restricted activity. And I was particularly struck by infection being the largest category, which is what we've seen epidemiologically evolve over the last couple of decades. When you look back two decades, cardiac hospitalizations were the most common reason. But more recently, as you are all probably aware, infection and sepsis have moved up to be the most common reasons. And that seems to be what's driving the hospitalizations in this study as well. And also I found the timing very interesting. So when you dive into the data here, it turns out that about 25% of the hospitalizations in this study occurred within the first month after discharge for critical illness in the functional recovery cohort. So among all the hospitalizations that occurred in the 12 months after discharge, about a quarter were in the first month. And so I think when we are thinking about programs and follow-up, really focusing on making sure that older adults have close follow-up and really good plans in place for treating infection and ensuring that infections are identified early might be a starting point in thinking about next steps and how we can act to improve functional outcomes. So with that, I will just say thank you. I'd like to thank all of my colleagues at the Yale Pepper Center and Program on Aging. Without them, this work would not be possible. And for some of the field core members that you see listed here, they have been following these older adults who are part of the Precipitating Events Project for decades and without their hard work, we really would not be so fortunate to have the great data that we have in this study. So I'd like to say a special thank you to them. And I'd like to thank all of you for your attention and I'm happy to take any questions. Thank you. Thank you to both of our presenters. And I think this really highlights both of these presentations, the fact that what we do in the critical care unit actually has effects well beyond the patient's time in critical care. And we really need to more think about critical illness not as a unit or a specific location, but really a continuum. And Lauren, I was going over the results of your study and I was kind of surprised about the reports on the restricted activity. And did any of those surprise you from what patients helped reported? What I thought interesting was fatigue was a top reason and it was almost double the next most frequent, which was dizziness. Do you have any thoughts on that? Yeah, no, I thought, sorry. I thought that was really interesting too. And it's hard to know if the, so a couple of things, I guess. The fatigue, so it's hard to know how much that was tied to something like a brewing infection, especially with infection being found to be the reason most commonly, the most common reason behind hospitalizations. And so, looking at that, I kind of wondered if fatigue was a marker of downstream infection, but our three events were mutually exclusive and hierarchical. So, someone who was reporting fatigue for restricted activity would not have been hospitalized, but I did wonder if they would be later on. So that was one thought, but I actually think it has less to do with that and more to do with the fact that in the ICU, despite our best efforts and amazing protocols, such as the ABCDEF bundle, that we still probably could be doing a lot better in terms of getting people up and moving and starting early rehabilitation and also more aggressive rehabilitation, especially after discharge. We published a study last year that showed that even among older adults who were discharged home after a critical illness and deemed homebound, so only eligible for home health, that a third of them never received physical therapy, even though they were referred for it. And among those who did receive it, they were receiving an average of like one session a week. And so, if we're under-rehabilitating our older ICU survivors, many of whom are frail and vulnerable to begin with, it's not surprising that a lot of them are experiencing symptoms such as fatigue. I see patients in the post-COVID clinic and a lot of my patients are younger and fatigue has been such a predominant symptom for so many this year. And so many of my patients are in their 30s and 40s that when I think about an older adult surviving a critical illness and then not getting enough rehabilitation, I guess it's maybe less surprising. Now, I think that that's quite interesting. And as you've related to COVID with people who were quote, healthy versus your patient population, and it really kind of brings to the point that what we do in the ICU really makes a difference. And following that A to F bundle, one, I know COVID was hard to have families in there, but two, to do early mobility, especially in the ICU actually might make a difference. And it sounds like you actually might have a couple more studies coming looking specifically at that issue and does that make a difference? Yeah, that's great. So, we actually do have a cohort study of older adults who were hospitalized with COVID called the Valiant Study that's funded by NIA. And actually enrollment is closing next week and then we'll have six months of follow-up through December. But we are, you're absolutely right. This is a cohort study that's evaluating function, cognition, burdensome symptoms and a number of other outcomes. And we will have those data including what we just discussed in hospital rehabilitation. And we do have a robust early mobilization program at Yale, it's called the Steps ICU Program. But like everywhere else early in the pandemic, that program was, I don't wanna say suspended, but it wasn't being applied to COVID patients. And after a few weeks of this, we realized that that could not continue. So we modified our protocols to ensure that COVID patients were also receiving early mobilization. Because with the isolation in the hospital, we actually felt the situation was even worse for them than it is for normal or non-COVID critically ill patients. So we addressed that pretty quickly. But yeah, so we'll see what comes, what we see when we analyze those data. Well, thank you for that, I can't wait to read that. Now for the audience, please feel free to use the question box. And if you have any questions for either of our presenters, type it in there and I'll get to them. And I do have one for Georgia. And realizing that she is an engineer by training, I was just curious, were there any concerns with the accuracy of the oximetry in the patients, especially with those with either darker skin tones or darker hair color? And was there a protocol in place to account for differences in skin or hair color and tone? Yeah, thank you for the question. It's indeed a very relevant question because yeah, higher concentration of melanin can produce a high reflection of this near infrared light leading to different readings for the same actually amount of cerebral oxygenation. In our study specifically, we did not, we had one patient with the dark skin tone. So we did not, yeah, we did not have enough power to really stratify for that. But it's definitely a very important point that needs to be taken into consideration whenever we will externally validate this result on bigger external cohort before maybe moving to a randomized clinical trial to really see if targeting the saturation can actually improve the outcomes of these children. Well, thank you. And I wasn't 100% surprised that you probably didn't have too many people at your institution, but it'll be quite interesting to see as we think more about diversity and inclusion, we need to think about some of our machines and are they actually doing the same thing across all of our patient types? Now, Lauren, I do have a question back for you. And it's really on the trend with functional recovery seems to be related more to chronic conditions, but function decline did not. Did you find any signals that might have been related to functional decline or was that a surprising result to you? No, we didn't in this particular study, but I think it's important to note that, so multimorbidity is one of many geriatric factors along with frailty, cognitive impairment, and a number of the other things that we highlighted in this study. And so I don't think that chronic conditions aren't important, it just may be that one of the other geriatric vulnerability factors, they were stronger in terms of their effect and then maybe kind of washed out the effect of chronic conditions. I think it's important, I just wanna highlight that chronic conditions are incredibly important. And although I think we know that they're important and I certainly don't wanna minimize that, this is just one particular outcome and it's also looking month to month as opposed to functional recovery, which is kind of looking across the spectrum of the admission and recovery period. So I guess I would say I'm not very surprised, I think it's still, but I think it's still very important and I would still definitely recommend including it in future work in this area looking at studies of disability and recovery. Like this is just one study, so I think it's still important to include. Now, definitely I think it's there, it was just interesting thought out there. This goes back to Georgia and specifically since you had a lot of babies in your study really how does the crying or the baby potentially being upset affect cerebral desaturation? So in our particular study, this was not a concern because the babies, all the children were sedated during the monitoring, but, and I don't think that's also for an awake baby, it would be a problem, the desaturation readings in case of upsetting, but it will certainly create artifacts in the signal, would add noise to the recordings, making it more inaccurate per se. For example, what we see is that when the baby is moved, then we have artifacts in our signal. So, but it's just the mechanical problem in moving the sensor. Yeah, and that totally makes sense and just as long as thinking, I was just thinking about some of those stuff is definitely those artifacts out there and if there's a good way to record it, it's probably made your life easier too, to look at that. And finally, I do have one last question unless anyone else wants to use the chat box and it kind of goes to Lauren and really what factors do you think we should look at to reduce some of these functional recovery and declines in older adults? Is there any sort of like pulmonary specific rehab or balance training or anything like that that you think we should be starting to introduce in these patients? Yeah, thank you for that question. So, I think it's important to realize that older adults often do have unique needs compared to some of our younger patients and a lot of that comes back to what other factors they may already have. So, a really good example of this is cognitive impairment. I'm not talking about severe dementia but even something like mild cognitive impairment which is highly prevalent among older adults and also as a reminder, older just means 65 and older and that's really not very old, right? There's a huge proportion of people age 65 and older many of whom have mild cognitive impairment but that could lead to more difficulty understanding medications or perhaps coordinating follow-up and even just functioning in the home or perhaps getting the rehabilitation that they need. So, I mentioned earlier that study that we did showing that older ICU survivors discharged home are receiving rehabilitation in very low levels if they're receiving it at all. And so, I think not thinking about our ICU survivor population as one homogenous population with even needs but thinking about this older adult group as perhaps having some unique needs may help us target better follow-up and programs that are more likely to improve their functional outcomes. And I think this study is really helpful because it shows us that perhaps if we can develop some targeted programs to reduce these intervening hospitalizations with a specific focus on the, even just focusing on the first month, that was a quarter of the hospitalizations, that's likely to exert a big effect. So, I think this study is a first step but can perhaps guide next steps about what we can do better. Well, thank you very much. And I think, you know, we look forward to, for both of you, the first of many studies out there to really shed a light on this underreported phenomenon. And I would like to thank not only Lauren and Georgia, our presenters, but the audience for attending. Again, to everyone who joined us today, you will receive a follow-up email that will include an evaluation. Please take the time, about five minutes, to complete the evaluation. Your feedback is greatly appreciated. And on our final note, please join us for our next Journal Club on July 22nd. And that concludes our presentation today. Thank you, everyone, and have a great day. Thank you. Thank you for having me.

webcast

Critical Care Medicine

postoperative cerebral oxygen saturation

SCTO2 levels

long-term IQ

congenital cardiac surgery

functional effects

intervening illnesses

older adults