Thank you, Pete. So my name is Sandeep, and I will be presenting our data on analgesia and sedation at terminal extubation, a secondary analysis from the DONATE database. And this work was collaborative work between nine institutions, and the collaborative co-authors are listed here. And Meredith was the PI of the parent DONATE registry. I do not have any conflict of interest. So these are the sites which contributed to the DONATE registry and this analysis. I am from the University of Illinois at Peoria. Meredith is from CHLA, which was the primary site for the DONATE registry. Then we also have a contribution from Wake Forest, Dallas, LIJ, CHOP, Lurie Children's at Chicago, and Loma Linda and University of Florida. And this map just shows the representativeness of our data. It represents most of the geographical regions of US, and we are right here. If somebody doesn't know where Peoria is, right in the middle, little red dot over there. So background. Most of us in this audience would agree that at the time of death, nobody should die in pain and suffering. So it's our duty as physicians to make sure that we control pain and suffering at the time of death. And we do do that by giving morphine or Versace at the time we withdraw life support. But there is always a moral distress, if you will, that if you give too much of these medicines, will they hasten the time of death or euthanasia? Thankfully, Supreme Court has affirmed the doctrine of double effect when, as long as the intent is to provide comfort, even if it hastens the death, time of death as a consequence of it, it's not considered euthanasia. But still we sometimes end up in some ethical situations and some of these even end up in court because of the use of pain and sedation medications at the time of death and the amount of medications that were administered. So based on that background, we decided to do some analysis of this donate registry data that was collected for a different purpose which I will get into. But the primary objective of this study, of this analysis was to describe the contemporary doses of opioids and benzodiazepines administered to a very large cohort of patients after terminal extubation in the United States. And the secondary objective was to identify the association of the doses of opioid and benzodiazepines with the time of death, with the hypothesis that sedation and pain medication used for comfort and analgesia at time of death do not hasten the time to death. So this was a secondary analysis of the donate registry. It is done at nine US hospitals and 680 patients zero to 21 years of age who died within one hour of terminal extubation between 2010 to 2021. And donate registry was itself collected retrospectively in nine hospitals in US. So what was donate registry was for, the primary objective of donate registry was to validate a machine learning tool to predict the time to death. So Meredith at UCLA had come up with a single centric model to predict the time to death because that's also important for many reasons, but including organ procurement is to be able to know the time to death. And this was an attempt to validate that externally in a much larger data set. So objective of donate registry was prediction of time to death. In this analysis, we're not doing prediction, we're doing exploratory or description of the medication used among all those sites and use a sort of a causal model to predict to find an association between the time to death and the medication given. So what's the inclusion criteria for donate registry? So donate included all patients zero to 21 years of age who died in the ICU after terminal extubation, should be ICU or OR because DCD patients were included in it and terminal extubation was defined as very specifically discontinuation of invasive mechanical ventilation with the expectation that the death will occur without intent for reintubation. So you are extubating the patient with an intent that he will die. And patients who died on the ventilator, died after withdrawal of non-invasive positive pressure were simultaneously decanulated from ECMO or were brain dead or had a terminal extubation at any other location were not included in the donate registry. And that's one of the limitation, the last point we'll talk about. Donate registry was only interested in knowing the events that were happening at the time of terminal extubation. So we only collected the data on the medication administered within one hour of terminal extubation. So in this, some patient died six hours after withdrawal of terminal extubation. So we couldn't include those patients. So that's why in this particular analysis, we only included patients who died within one hour of withdrawal after terminal extubation. So primary outcome variable is time to death after terminal extubation in minutes. The primary predictor variables is the total doses of opioids and benzodiazepines, 24 hour before and one hour after terminal extubation. And benzodiazepines included lorazepam, diazepam and midazolam. And opioids included fentanyl, morphine and hydromorphone and they were converted into equivalent lorazepam and morphine doses. So obviously, the drugs will not be the only factor that would impact the time to death. So we collected the confounding variables whom we think would fall in the causal model for time to death. And that would be age, sex, admission diagnostic categories, medical versus surgical admission, that would be trauma, surgical primarily. Hemodynamic instability, we tried to capture it with the use of vasoactive and anatropic medications. And neurological status, we tried to capture that with the Glasgow Coma Scale. Then pulmonary function, or how bad the lungs were, lung function, we captured this with the SF ratio. And use of any other sedative medications and the neuromuscular blockade administered one hour before and one hour after. So during this timeframe, 10 years, 905 patients' data was entered into the donate registry. And out of these patients, about 25% died more than one hour after terminal extubation. So they were excluded from this analysis. The total study cohort included 680 patients from nine institutions. Median age of the study population was 2.1 years. And median ICU length of stay was 5.6 days. And time to death after terminal extubation was 15 minutes. So this busy slide basically shows what the primary objective was to describe the prevalent usage of opioids and benzodiazepines. After terminal extubation. So this top four rows represents the proportion of patients who received these medicines. And then this is the median hourly dose in milligram per kilo per hour. So about 25% of patients in the last day of life did not receive any benzodiazepines or opioids. About 50% received both. And about 24% received opioids. And a very small minority got only benzodiazepines. And this of course varied based on what the GCS of the patient was. And the dosage was more or less standard. Intravenous morphine equivalent was 0.1 milligram per kilo per hour. And lorazepam was 0.01 milligram per kilo per hour. And this only included patients who got morphine or benzodiazepines. And this next four rows represents the proportion of patients who received these medicines after terminal extubation. So about 60% within one hour of terminal extubation received neither benzodiazepines or opioids. Only 15% received both. About a quarter of them received opioids. And 2% received only benzodiazepines. And the hourly doses however were quite high among those patients who did receive it in one hour. The intravenous morphine equivalent was 0.7 milligram per kilo per hour. So about seven doses of morphine within one hour. But lorazepam equivalents are also 0.22 milligram per kilo per hour. And this is the other sedative medications administered. Presidex was the most commonly used in about 13% and 5% afterwards. And this table just shows the straight correlation coefficient. No adjusting, it's just the time to death on the x-axis and the medication administered as a continuous variable on the y-axis. So this is just showing correlation coefficient and as you can see the correlation coefficient is very, very less and none of it is significant. So just by this table we can say that the time to death is not correlated with the amount of medications administered before or after. But in isolation it doesn't mean much because the time to death is impacted by a lot of other things than just medication. So then we did a regression analysis. Well this is just the scatter plots of the table that we showed earlier which is the time to death in minutes on the x-axis and the doses on the y-axis. And they're pretty flat. If there were an association you would wanna see these lines going like this. So this is the regression model and this basically adjust for the other factors that will fall in the causal model for time to death. At least the variables that we had data on. So these are the medications, the morphine equivalent after morphine, lorazepam equivalents after morphine equivalents before and lorazepam equivalents before terminal extubation. And the other factors that we include in the model were age, sex, GCS three or more than three, so neurological status, SF ratio, inotrop administration 24 hour before terminal extubation and neuromuscular blocker. So as you can see the p-values for all of the four categories, they were all non-significant. But appropriately age was negatively associated with time to death, so younger patients died sooner. Age, sex had no association. As intuitively also it makes sense, a patient who had GCS of three died sooner. SF ratio had positive association, so the higher your SF ratio, the healthier your lungs, the longer it took to die. Same as with hemodynamic instability, the more unstable you are, the quicker you die. And neuromuscular blocker were not associated with time to death. So conclusions, in this multicentric retrospective cohort of PICU patients receiving terminal extubation, opioid and benzodiazepines did not appear to hasten death for patients dying within one hour. And it was used in a sizable proportion of patients, but still about, it's only 60% of patients who received opioids and benzodiazepines, although we're limited to patients who died within one hour. So that might be why it's undercounting the proportion of patients. So do we have time for limit? So I'll go through the limitations real quickly. Some of the limitations are pretty standard for retrospective analysis. We are limited to the variables collected by the donate registry. So for example, we could not include patients who died after 60 minutes. A very important marker would be severity of illness, prism and pilot scores, which were not collected. So we can't control for that. We use surrogates for it. So they all add up to limitations, and they become addictive. And study did not assess, we can't say that the medication that we gave actually caused patient comfort or not, because we didn't measure that. And doses were extracted from the EMR, and especially at the time of death, the administration and charting may not be as accurate. So it's possible that we under calculated it. And it's retrospective. So all we can say is, it's an association. We can't say it caused acknowledgements, and this is the team. Thank you.

terminal extubation

opioids

benzodiazepines

analgesia

end of life