All right, and that's a good segue, because we've been talking a lot about that these children surviving septic shock have ongoing medical problems and health resource needs, that they have persistent declines in quality of life, and that their families tend to have distress and dysfunction. And what I'm going to talk about today is how does illness severity, as we conceptualize and measure it, contribute to any of those outcomes, especially as we think about what can we do about this ongoing morbidity? So I have some grant funding that supported this work, and then as well, received consultancy fees that aren't related to the content of this presentation. Multiple illness severity and organ dysfunction scales that are commonly used in the pediatric ICU are well-established to be associated with mortality after pediatric sepsis. These summary measures demonstrate in yellow the mean effect size, essentially, of the association between each of these measures and mortality. The pediatric risk of mortality and the pediatric index of mortality, as implied by their names, were developed to estimate risk of mortality in children. The pediatric logistic organ dysfunction was developed to assess the degree of organ dysfunction, but also, as you can see here, has, unsurprisingly, a strong association with mortality. And again, these are all children with sepsis, so this is the population that we're interested in. When we hone down on the LAPS cohort itself, the same thing was found, is that the association between each of these scores shown here and 28-day mortality was statistically significant. The PRISM score on the day of admission, the PILOD score on the first day of admission, the summary of the sum of the PILOD scores, which I'll get to in a moment, and the highest vasoactive infusion score were all associated with mortality. I'm going to highlight the sum of PILOD because I'm going to come back to that a couple times throughout this presentation. As Dr. Meert mentioned, the sum of PILOD is just a simple summation of each daily PILOD score while in the ICU and is intended to provide a more summary measure of the overall burden of critical illness and organ dysfunction in these children. When we think about illness severity and morbidity, there is a relatively consistent association between higher illness severity and worse functional outcomes. That's been demonstrated in multiple studies. However, it's been much more variable when we look at health-related quality of life, with some studies demonstrating that higher illness severity is associated with worse quality of life and other studies not showing that association. In lapse, there did seem to be an association between all of these or most of these illness severity and organ dysfunction measures with quality of life. The persistent serious deterioration in quality of life that Dr. Prout mentioned is that health-related quality of life scored 25% below baseline at three months as an indicator of really severe and persistent deterioration from baseline. And the day one PILOD, the sum of PILOD, and the highest vasoactive infusion score all demonstrate an association with persistent serious deterioration in quality of life at three months. The sum of PILOD remains statistically significant on the multivariable model. So then the next question that we had was, can you actually use illness severity scores and organ dysfunction scores to predict morbidity? A patient comes in, their PRISM score is whatever. Does that tell you an estimation of what their actual morbidity is going to be, not just the mortality? Because we do know that all of those scores have been shown to predict mortality, but can they predict morbidity? So as I mentioned, both the PRISM and the PILOD do predict mortality in both general PICU patients and in subpopulations of critically ill children. Various studies have demonstrated an area under the receiving operating characteristics curve ranging between 0.75 and 0.95, just on the day of admission, for prediction of mortality using either of those two scores. This is just an example of two UROC curves from another publication. So can these two scores predict functional status and health-related quality of life? So look at this. We used the 359 lab survivors and assessed discrimination of four exposures, the PRISM score. And this was collected in labs on the day of admission, minus 2 hours to capture emergency department time, and plus 4 hours after admission to allow collection of laboratory values and vital signs. Day 1 PILOD, which was a midnight to midnight calculation, but for this study, we made sure to only include it as day 1 if the child was admitted before 8 PM to allow at least 4 hours of data collection to mimic the PRISM window of opportunity for data collection. The maximum PILOD score over the course of the PICU stay, and then that cumulative or sum of the PILOD score that's maxed out at 28 days, so the sum over the first 28 days of a PICU admission. We assessed discrimination of each of those exposures with new functional morbidity, defined as an increase in FSS or functional status scale at 28 days or hospital discharge, whatever occurred first. And this persistent serious deterioration in health-related quality of life, the decline by 25% from baseline in either the PEDS QL or the FS2R at each of the four follow-up time points of month 1, 3, 6, and 12. What we found is looking at new functional morbidity, there was no significant or at least a good association or area under the receiver operating characteristics curve prediction of functional morbidity with either the PRISM or the first day PILOD. So your illness severity, your organ dysfunction on the first day of admission did not provide very good prediction of your functional morbidity 28 days later at hospital discharge. Maximum PILOD had an AUROC of 0.74, which many people would consider in the moderate prediction category. But cumulative PILOD, which again is that score that gives a much better assessment of the overall global burden of critical illness over the course of the admission, had an AUROC of 0.81, which would tend to be classified as good or better prediction. Then we move into this persistent serious deterioration in quality of life. The results are much more poor. So only the cumulative PILOD gets into that range of moderate to maybe you could call that OK prediction at 0.71. It would be hard pressed to say that that's anything more than moderate prediction of quality of life. When we stratified that result by whether these patients filled out or their families completed the PEDS QL or the FS2R to get a sense of both the impact of the survey itself as well as some element of the underlying comorbidity and neurologic status of these patients, there was no difference. They were equally poor at predicting. The illness severity was equally poor at predicting the quality of life based on either of those measures. This is another way of looking at it as we compare the different outcomes. So the four colors are the different four illness severity organ dysfunction scores. Mortality in the LAPS cohorts, the maximum PILOD had very good predictive ability for that. So the maximum organ dysfunction you experienced had an area under the receiving operating characteristics curve of almost 0.9. The day one PILOD and the cumulative PILOD were at about 0.7 or just above that. PRISM was quite poor at predicting mortality, ironically. Functional morbidity was actually pretty good with cumulative PILOD just over 0.8 and maximum PILOD in the 0.75 range. And again, that's for functional morbidity. This is your persistent serious deterioration quality of life at each of the three time points. So cumulative PILOD was the best of all of them. But even then, at 3 and 6 months, it was just about 0.7, so moderate ability to predict your persistent serious deterioration in quality of life. And overall, if you look at least from 3 months onward, that predictive ability decreased for all of those severity scores. And as a reminder, this PSD-HRQL is looking at a 25% decline from baseline. That's considered a very substantial change. When we then look at the minimum clinically important difference of just 0.45 points, the predictive ability is essentially negligible with still that cumulative PILOD being the best and just over 0.6. So in a smaller deterioration, there's almost no predictive ability by illness severity. So can illness severity scores predict morbidity? Moderate to good ability to predict discharge functional status, but limited ability to predict health-related quality of life. Very minimal discrimination for the minimum clinically important difference, and only slightly better for a more significant difference or decline. Discrimination is best for your maximum and cumulative PILOD, which give a better sense of the overall burden of critical illness. And discrimination generally worsens over time. So why is this? As alluded to, there's lots of contributions to quality of life that aren't just related to your severity of illness. Your pre-existing age, personality, values, motivation, parental stress and family dynamics, aspects of your own genetics and comorbid conditions, elements of the environment. And that's before you even get to all of these elements of the hospital environment that have been demonstrated to be associated with quality of life. And illness severity is only one small piece of these. So next, I'm going to focus in on the family component. What is the impact of how the family is recovering, as Dr. Meart has discussed, on both the child's quality of life, but also how does illness severity impact the family's recovery? So I have two questions here. One is the child's illness severity associated with parental distress and family dysfunction. And then secondly, do parental distress and family dysfunction contribute to the child's quality of life? So first, to answer that first part of the question, we looked at the LAPS cohort, again, looking at the caregiver outcomes that Dr. Meart mentioned, the brief symptom inventory and the family assessment device at baseline and 1, 3, 6, and 12 months. The first analysis was to evaluate the association between these illness severity scores with parental distress and family dysfunction. In the multivariable models for this, we adjusted for patient age, medical complexity, and immunocompromise, which are some of the potential confounding factors to that association. Then we did a second round by looking at the association between the family outcomes with the parent proxy-reported child quality of life, so how the parents reported their child's quality of life was. Those were adjusted for the same potential confounding factors as well as the maximum PILOD scores to take out that element of severity of illness as a potential confounder, or at least to reduce the impact of that. So this graph, and I'm going to have a few that are similar, so I'm going to show you an example of what this looks like, walk you through this. So on the y-axis are a variety of different measures of illness severity or organ dysfunction. The adjusted odds ratio after adjustment for those confounding factors is shown on the x-axis with a dotted line at 1, so no difference. The purple circles are non-significant results, and the teal are statistically significant associations. So when we look at the association between day one PILOD, maximum VIS, and both PICU and hospital length of stay, there's a small association with a slightly higher likelihood or higher odds of parental psychological distress at one month with higher levels of those illness severity scores. They're small, but they're there. But then they go away. So no association with parental distress at three months, none at six months, and none at 12 months. Moving over to family dysfunction. Yes, you are reading this right. So day one PILOD, maximum PILOD and ventilator days, the higher those measures, the less likely families were to report dysfunction, new dysfunction compared to baseline with pretty substantially reduced odds ratios, 0.8, 0.84, 0.94. This is at one month. Three months, same thing. Six months, even more. So over and over again we're seeing that the groups with higher illness severity have lower odds of new family dysfunction. Disappears at 12 months, but certainly not moving the opposite direction. So is illness severity associated with caregiver outcomes? Minimal association with caregiver distress, a slight increase in distress with greater illness severity at the one month post-admission only. And higher illness severity is associated with lower odds of family dysfunction. We did the math on this a number of times to make sure nothing was reversed. Some of the reasons we speculated it could be contributing to this were relationships in the family strengthened by the experience of going through a very sick child and coping with that experience together. Dr. Pratt mentioned this idea of this post-traumatic growth and really the family coming together and developing positive impacts from this experience. And maybe these families were targeted to have more post-discharge support. Someone said, you had a child who is very, very critically ill. Let's make sure we focus on you as a family and make sure you're getting through this, whether it's professionally or just socially of their social and community connections. I'm not sure, but these are some of the reasons that we're thinking about this. So the final part of this is caregiver distress and child health-related equality of life decline to start out with. So in teal are the prevalence of family or the families that have psychological distress versus no psychological distress in blue at each time point. And the y-axis is the percentage of those families who reported that their child had decline from baseline. And so what we see is that at each time point, the group who did report psychological distress, they also reported that their child had worse quality of life. And that holds after adjustment for multiple confounding factors at one month, three months, and 12 months. So there does seem to be an association between the caregiver's psychological distress and their child's quality of life. When we divide that out into whether the distress was new, so again, we collected baseline information. So did they have no distress at baseline and then developed distress later? That actually had the highest prevalence of now reporting that their child had quality of life decline. Persistent distress, so they were distressed before the admission and they're still distressed after, was still pretty high, less in general than the group with new distress. But then those with resolution of distress, they were distressed before and no longer were. And those who were never distressed had lower prevalence of children with quality of life decline. So there does seem to be an association here. When we look at family dysfunction, though, there's not any significant association at all. No real trend with the raw percentages. And then when we do the adjusted odds, there's no significant associations between family dysfunction and their child's quality of life. So are caregiver outcomes associated with child quality of life? It does seem that parental distress is associated with child health-related quality of life decline. What we can't answer with this data, though, is what direction is this going? Are parents who are distressed reporting that their child's quality of life is worse because their quality of life is worse, potentially? Or is the child's quality of life poor and that is causing their parents to be distressed? We don't know. It's cross-sectional data. But I think it's an interesting thing that we need to think about when we're using proxy reporting of the relationship between the proxy reporter's mental state and what they're saying on their surveys of their child. And so in conclusion, there's definitely a complex relationship between measures of illness severity and morbidity among both substance survivors and their families. Illness severity contributes more to risk of mortality and functional morbidity than to health-related quality of life decline, as far as we can tell from this cohort. And that quality of life is influenced by many aspects of both the pre- and post-hospital environment that are not just related to the severity of illness and organ dysfunction. There's poor predictive ability of those illness severity measures with longer duration from hospital discharge, meaning that more elements of the post-discharge environment are starting to impact that quality of life. And then we also really need to think about the influence of the caregiver's psychological state and whether that is influencing the report or, again, whether the child's status is influencing the parent's status. But I do think that the poor predictive ability of illness severity to affect or predict the quality of life actually may suggest that there are more modifiable factors out there. There's often not much we can do about the severity of illness, especially on that first day of admission. That's how they're getting there. The fact that the PRISM score actually has no association, really, with the ongoing quality of life in a way can tell us there's other things than just how the kid's presenting. And maybe those are things that we can find and intervene on to help with limitation of the morbidity trajectory. And that is all I have. Thank you very much. Thank you.

septic shock

quality of life

PRISM and PILOD scores

morbidity prediction

family dynamics