Hello, everyone, and welcome to today's Journal Club Critical Care Medicine webcast. This webcast, hosted and supported by the Society of Critical Care Medicine, is part of the Journal Club Critical Care Medicine series. This webcast features two articles that appear in the March 2023 issue of Critical Care Medicine. This webcast is being recorded. The recording will be available to registrants on demand within five business days. Just simply log into MySCCM.org and navigate to the My Learning tab. My name is Tony Gerlach, and I'm a clinical pharmacist at Ohio State University Medical Center here in Columbus, Ohio, and I will be serving as a moderator for today's webcast. Thank you for joining us. Just a few housekeeping items before we get started. There will be a Q&A session at the conclusion of both presentations. To submit questions throughout the presentation, simply type into the question box located on your control panel. If you have a comment to share during the presentation, you may also use the question box for that as well. And finally, everyone joining us for today's webcast will receive a follow-up email that will include an evaluation. Please take five minutes to complete the evaluation as your feedback is greatly appreciated. Please note the disclaimer stating that the content to follow is really only for educational purposes. And now I would like to introduce today's presenters. First is Ryan McHenry, who is a senior resident in emergency, pre-hospital, and retrieval medicine in Glasgow, Scotland. His ongoing postgraduate research investigates the influence of social economic status in geographic isolation on service use and outcomes in critical care, pre-hospital, and retrieval medicine. Our second presenter is Dr. Micah Helblig, who graduated from medicine in 2018. After initially working as a medicine house officer in Curacao, he started a dual position of clinical work and research in Amsterdam in 2020. His research cumulated in a PhD project on lung ultrasound in critical care. The current critical care medicine article is one of the main constituents of this PhD program and project. In 2021, he started residency training at the Amsterdam UMC to become a specialist in anesthesia and critical care. Thank you both for joining us, and now I'll turn the presentation over to Ryan. Thank you very much, Tony, and I'm very grateful to be asked to speak today about our recently published review of the association between socioeconomic status and outcomes in critical care, which was published in Critical Care Medicine just last month. Before we begin, I have no disclosures to make. And so I suppose to begin with, a bit of a plan about what I want to speak about today. So I'll speak a little bit about why we've written this paper, and why this question might have importance for us who work with the critically ill. We'll speak a bit about the paper itself, including some of the difficulties and limitations whenever we're trying to synthesize the evidence on subjects like this. And then finally, really to touch a bit on what this means for us in clinical practice, particularly for those of us who work with a critically ill environment, where often it feels that there's little that we can do to materially change the social conditions that our patients face. So first of all, why have we written this paper? And for me, it starts with this place, and for those of you who haven't been lucky enough to endure the Scottish rain, this is the Glasgow Royal Infirmary. This is the home of Leicester and the home of antisepsis, and where I started my medical career. And the striking thing about the Royal Infirmary, both in Leicester's time and now, is the communities that it serves. And if we look at the Scottish Index of Multiple Deprivation, which is an area-based index that attempts to describe deprivation across seven different domains, we can see why. So with the red as the most deprived and the blue as the least deprived communities in Scotland, we see that Glasgow has its fair share of social deprivation. But if we look at the Royal Infirmary itself, we find that in particular, this sits within some of the most concentrated areas of social deprivation in the country, and by some measures, Western Europe. And this is not just an abstract index. These figures are also borne out whenever we look at life expectancy and social conditions. And why this matters, and why it mattered to me whenever I was a young doctor, was how it colours presentations. And it was very clear that the social circumstances of our patients influenced why they presented to hospital and how they presented to hospital. But this is not just a personal story. So we've known for a long time, certainly long before Tudor Hart published his seminal paper on the inverse care law, that social circumstances influence both morbidity and mortality. And what Tudor Hart added with this 1971 paper was that services themselves may act to exacerbate these issues, finding that the provision of services is often inversely proportional to the needs of the population. And in the intervening years, we've only really developed and reinforced these findings. But it's not clear for those of us who work in clinical care to what extent that for us delivering a service that's based on clinical need, and hopefully less on accessibility, maybe this is a service that maybe has the potential to mitigate the health inequalities that we see elsewhere in healthcare. And we do have some evidence for that, not least in a 2019 systematic review by Jones et al, also published in Critical Care Medicine, that summarised 10 papers with a narrative review. And that was really a great help in terms of the building blocks for our paper, and one that I would certainly recommend. So what did we do? We took a population of adults who were admitted to critical care units worldwide, trying to, I think, recapture the broadest inclusion criteria that we can to answer this question. And we looked at any paper that might have a marker of socioeconomic status, and crucially excluding those that just used insurance status. And that's something we can potentially speak about a little bit later. And in the systematic review part of our paper, we looked at any outcome from critical care, be that physical function, or cognitive function, or social outcomes. But for our meta-analysis, we really looked at mortality at less than 30 days, with the intention that that would allow us to have a look at mortality related to the acute illness. And we also did a smaller and more limited meta-analysis of length of stay. And if we look at what we found, as usual with these systematic reviews, we screen a huge number of patients on our screen, a huge number of papers, almost 3,000 papers to begin with, narrowing that down to almost 70 for full-text review, and incorporating 38 papers ultimately in the qualitative review, and then 23 in that meta-analysis of mortality outcomes. And the vast majority of these papers were retrospective cohort studies, and the very vast majority were rated as good quality on the Newcastle Ottawa scale. And what did we find? So we found something that possibly won't surprise many of us that work in critical care, but we find that a pill-to-dodge ratio of 1.13 for early mortality for the most deprived compared to the least deprived. So it does look like socioeconomic status is associated with mortality in critical care. And these are results that were robust on sensitivity analysis, and robust whether we assessed area or individual level markers of socioeconomic status. On our meta-analysis of length of stay, we find no significant difference in length of stay depending on socioeconomic status, and that was a more limited meta-analysis of eight studies. Though it has to be said that there are significant challenges whenever we're trying to synthesize the literature, and I thought it would be very useful to have a look at some of those limitations and challenges to try to put our findings in context. So the first part, and I think this is something that can be said not just for my study material, but for any attempt to synthesize the critical care literature worldwide, is that there's huge heterogeneity of healthcare systems. And this is not just necessarily in how they respond to patients of varying socioeconomic status, but it can also be about the thresholds for entry to the intensive care unit, or for the availability of different mechanics of care. One of the particular challenges in my research interest is the huge diversity of markers of socioeconomic status. These can be individual, for example, an individual patient's employment status, perhaps their education status, or even things like the education status of their parents. More often, particularly now, we're looking at area level indices, which are in some ways they're easier to gain because they don't necessarily involve speaking to individual patients. So these are things where we can assess these retrospectively. And then there are single and multiple measures of these, so indexes that try to combine various markers of socioeconomic status, like income and employment and education, into a single index. And these indexes vary worldwide in terms of the domains that they use to try to define socioeconomic status and the particular components that are included. So it's important, I think, to recognize that we're not measuring the same thing whenever we look at each of these studies, but we're hoping to try to capture a marker and an index that might be similar enough to be able to combine these markers of socioeconomic status. There's also huge heterogeneity in terms of looking at the outcomes that are assessed in these papers. We've included studies in our meta-analysis that look at in-ICU mortality, that look at in-hospital mortality, and then look at mortality at various time points up to 30 days. And actually, there's many papers out there that report timeframes that are even longer than that. And certainly, in our systematic review, we comment on the fact that some of these papers are reporting mortality up to one year after ICU admission. And I think one of the particular challenges that we've had is trying to synthesize multiple statistical methodology into a single figure to try to give an indication of the association between socioeconomic status and mortality in critical care. And that is certainly a challenge, and perhaps one for more for the statisticians than for me. And I wanted to highlight this final challenge just in a little bit more detail, and that's the head and letters here. So this is something that we find where quite often, papers that we included mainly by citation tracking included reports of an association between socioeconomic status and mortality buried deep in supplementary appendices that simply wouldn't be able to be found via conventional methods of being able to search the literature. And certainly, it's reasonable to think that there may be evidence out there that we've missed because this simply isn't searchable in the way that we currently do systematic reviews. There are some strengths to the paper as well, as I've indicated. We've tried to use a broad inclusion criteria to assess centers worldwide. We've tried to be very clear about how we've reported our methodology and our results, particularly in terms of limitations. And as I've highlighted previously, it's been useful to see that our results are robust on sensitivity analysis, which hopefully lends a little bit of weight whenever we consider some of the outliers that have been included in this study. So what does that mean for us? We've hopefully added some knowledge of the effect of socioeconomic status in critical care, or certainly the association of socioeconomic status and outcomes in critical care. And we've seen that unfortunately, health inequalities persist even in an environment where we would hope to be able to deliver care more on the basis of need rather than necessarily accessibility. And for us as clinicians, I think that we can identify socioeconomic deprivation as an important part of our practice. We can incorporate knowledge of that social deprivation of our patient group into an appraisal of risk, just as we would do for age, smoking or comorbidities, now that we've got an understanding of the impact that it has on mortality. And finally, I think that we can advocate for access to a group that we know are at increased risk of morbidity and mortality, both outside the ICU and inside the ICU. And I think one of the things that I would say for that in particular is that our systems need to be able to respond to this. So we know that the inverse care law extends to critical care. We have a sense from some of the papers that are included in our systematic review that there are potentially fewer ICU beds available to the socially deprived and that those ICU beds that do exist in socially deprived areas may be more often over capacity, for example, in the first wave of the COVID-19 pandemic. And I think that perhaps one of the more interesting parts of where the ICU literature is going really is in the work that's going in place into ICU rehab programs, assessing not only the physical and mental recovery from intensive care, but also trying to aid the social recovery for patients that we know are potentially vulnerable as well. So with that, I'm going to hand across to Micah for his presentation, and we'll have some time for questions at the end. Thank you very much, Ryan, for your interesting presentation. Thanks, Tony, and SCCM for giving me the opportunity to talk about this study, the impact of thoracic ultrasound on clinical management of critically ill patients, or as we call it, the Ultraman study. And before we start, I'd also like to say that I have no disclosures at this point. And for making this presentation, in the beginning, I did a quick PubMed search. There should be a logo of PubMed right here, but I did a very simple search to see what the literature on thoracic ultrasound has been in the last decades, and it was really noticeable to me that in 2000, there were only four papers in PubMed, and this has really exploded since to several hundreds in the years following. And this is kind of reflective of what I think we all see as an academic and bedside emergence of thoracic ultrasound. And it's logical because it's rapid, it's repeatable, it's non-invasive, and it's low cost. And it gives us quite a bit of information about the circulatory, respiratory, and volume status. It is set in some literature to exceed the capabilities of physical examination, and even to parallel that of more costly and invasive modalities, such as, for example, the chest x-ray. Some literature even suggests it's reduced time to diagnosis, and it decreases the uptake of alternatives. So that sounds quite good, and I think with that body of literature, we can kind of agree that in the right hands, with the right machine, in the right settings, and the right context as well, it can make an impact for patients. But of course, there are limitations, such as the interoperator variability, the risk of interpretive error, and especially on the ICU that we have a very complex and dynamic setting. So clinicians really need to take into account the potential downstream impact of, for example, erroneous or indeterminate findings, and also the clinical context in which we act, as well as the disease prevalence that we're looking at. So what we see actually is that the clinical utility extends beyond what we would normally consider diagnostic accuracy. And there's a very nice framework for this by Fryback and Thornbury, stemming from 1991, and it develops test efficacy, or it categorizes test efficacy in three layers, test attributes, which kind of talks about diagnostic accuracy and the development and validation of that, and then decision making, and in the end, health outcomes. And the issue, well, not the issue, but what you see is that available evidence mostly concentrates around those test attributes. There's very little on decision-making health outcomes, whilst the clinical impact is completely the reverse. So what we're seeing now for thoraxic ultrasound is that we've, with that literature that I've just showed you, that explosion in PubMed, that we've kind of are exiting the test attribute phase, and we're going into decision-making, and its impact on diagnostic and therapeutic clinical decision-making, and trying to transition a little bit towards health outcomes. And what we did a while ago was we performed a systematic review on the impact of lung and thoracic ultrasound on clinical decision-making, different departments. And as a part of that study, we found that there were five studies only that evaluated this impact on clinical management in the ICU, with a total of 504 patients. And they had quite interesting results. 44% of examinations changed diagnosis, 42% changed management, and 51% of those changes were non-invasive. But, of course, there were a few limitations. There was a high methodological heterogeneity and a moderate to high risk of bias throughout the entire systematic review. In total, we noted that there was a low sample size, it was a very high spread, and I think that the whole systematic review was dominated by one study. That's a study that is on the top right, a study by Kshiruchacki and colleagues, and they only assessed lung ultrasound, so only one organ, and they only did it with one operator. So that was interesting because, obviously, cardiac lung and cable findings kind of interrelate and are very suited towards ICU pathology, which is cardiopulmonary pathology. And furthermore, what we noticed in all of these studies were changes in management were assessed on case report forms, but there was no follow-up. So, of course, writing on a case report form that you've changed your management is not necessarily associated with actually executing that or, in the end, having outcome relating to that. And what we wanted to do, so this is quite encouraging, but it's not a consistent effect. We wanted to see if we could kind of improve or near that with our own study, and that's this study that was recently published in Critical Care Medicine, and the purpose was to investigate the impact of thoracic ultrasound and clinical management in the ICU. It was a prospective international observational study across four centers, of which three were in the Netherlands and one was in Italy, and the patients were all adults who received a clinically indicated thoracic ultrasound, and in this particular investigation, we defined thoracic ultrasound as being either cardiac, lung, cable, or diaphragm, or a combination of those four. So, what we also did is we had a case report form, and the case report form was split up into two parts. The upper part of the case report form asked to detail the operator and training level, your reason for your thoracic ultrasound, and your current diagnosis and treatment plan, and that current diagnosis and treatment plan reflects the current clinical impression that you have of the patient you're doing the thoracic ultrasound on. Then after your thoracic ultrasound, what we see lower in the form, you write down your findings and then what the clinical contribution of thoracic ultrasound was. So the hierarchy of the form only allowed you to say that there was a change of diagnosis or a change in management when it actually changed your clinical impression compared to previously. Lastly, the changes that were actually wanted to be made were noted and the changes to diagnosis as well. So this flowchart that I think will appear now kind of summarizes this process again. So here we have the adults with a clinical indication for a thoracic ultrasound, the clinical impression was written down, the thoracic ultrasound is performed by the clinician, and then the findings, and the differences between this clinical impression and the findings, that was the primary outcome, and those were the management changes. So by doing that, we were trying to stay as close to thoracic ultrasound attributable changes. So we wanted to exclude changes that were already anticipated based on previous suspicions by, well, excellent physicians or, yeah. And the second outcome that we wanted to look at was whether these changes that they actually suggested on the case report were executed within eight hours. So we wanted to verify the occurrence of the changes. And lastly, we wanted to see if there were any verifiable patient-centered outcomes based on this that we could measure. And of course, fluid balance or fluid management is a critical target in the ICU, and it's easy to measure. So this is what we took for a tertiary outcome. So the results, this is the baseline, oh, this is not the baseline table yet, but here we have, we had 725 examinations in 534 patients, and these were performed by a total of 111 operators across those four centers. So it's not just one operator doing this and not just four, it's a whole group. What's interesting in this baseline is, so this represents all those ICU patients that have an indication for an ultrasound, and 66 of those are ventilated, 10% of those don't have a medical history, and most of those have a medical reason for admission, and what should be noted here is that COVID-19, of course, this study was performed during COVID-19, so 20% of admissions were with COVID-19. And some examination characteristics, it's quite interesting to see that 72% of the reasons for thoracic ultrasound were diagnostics. This is also reflective of what we see in the clinics when we want to solve a clinical uncertainty or we want to solve an undifferentiated crisis, then we need rapid bedside ultrasound to make decisions. The main domain that we found was respiratory with 55%, and then the highly anticipated red box shows us what the main pathologies were, and atelectasis, obviously very common in the ICU with patients in the supine position, 32%, and then pleural fusions and pulmonary edema. And then for the primary result, so what we found was 28 of those 725 ultrasound examinations had no clinical contribution, whereas almost half confirmed the clinical impression and the other half changed the clinical impression. So that's quite a huge number on the confirmation and change side, and if we put that into a graph form to kind of give an overview of the types of changes, we can see that 23% of those 725 examinations had a change in diagnosis, of which the most frequent were respiratory, so that matches the primary domain that most thoracic ultrasound operators have in mind, and those 725 had 39% management changes, of which most were non-invasive, but still a significant proportion were invasive, and of these management changes, 89% were executed in the eight hours afterwards, and what I think and we think as a group is quite notable as well is that a lot of those non-invasive changes are related to fluid management, and that leads us to our tertiary outcome, which is the change in fluid balance. So what we see here in the bottom is we see the intent of the physician, whether the physician wanted a change of management that was positive, neutral, or negative. Now we see the actual change in fluid balance within eight hours, and we see that it's quite easy for ICU physicians to have a positive fluid balance within eight hours of almost a litre, with the interquartile range staying way above the zero line. For neutral, we see the interquartile range going both sides of the zero line, and what is interesting about the negative fluid balance intent is that the interquartile range extends just a little bit above the zero line, which I think confirms with what we see in clinics when we try to de-resuscitate a patient, we notice that this is quite difficult in the initial eight hours of the de-resuscitation, and we also of course have to take into account the huge amount of fluid creep that occur on the ICU where all the vitamins, the antibiotics, every medication we give also leads to an increased fluid balance. Across the whole group, there was a net fluid balance increase of 200, and those patients that did not have any changes of management related to fluid management, so they were unguided, so to say, had also almost 200 fluid balance. So the main findings are 49% change clinical impression, 39% of those clinical impressions, well 39% of the total, lead to a change of management, which most are non-invasive. 89% is executed within eight hours, and change in fluid management mostly leads to a complete change in fluid balance. So this corroborates the existing evidence that we already have for the clinical impact of thoracic ultrasound, but also kind of builds a bridge from changes in clinical decision-making to some of those verifiable patient-centered changes. And it's nice to compare this to some of the other studies that already have done similar things. The first one is on the left top, that's by Dr. Leskiewicz and team, I hear now that sometimes my audio is going quiet, so I'm going to try to talk a bit louder and try to keep my head still, that might also help. So we have the study by Zaleskiewicz and the team in which they assessed over 1,000 examinations, and what they did was not only thoracic ultrasound, they also looked at 70% of those non-procedural ultrasounds were thoracic ultrasound, but 30% were abdominal and trapezoidal, so it's not exactly the same. They did it on one day that could have been anticipated by 142 ICUs, and they judged therapeutic impact according to their ultrasound position. Then we have the study on the right top, which is talking about the impact of lung ultrasound on decision-making, and they had 254 examinations with a single lung ultrasound examination, single operator, and they classified everything according to the net reclassification parameter that is a bit more difficult to comprehend. What is notable with both of them is there is no feasibility follow-up, no report on downstream effects, and it's harder to say whether these changes are attributed to thoracic ultrasound or whether they're just attributed to excellent conditions with an ultrasound in there. So, what I think we did in our study with the confirmation of clinical impression that we found in 50% of the times, I think it's a very important outcome as it eliminates diagnostic uncertainty, it might eliminate a delay, and it might eliminate the need for further investigation. The change of clinical impressions, of course, is more important because it shows that this is a, ultrasound is a, thoracic ultrasound is a true diagnostic modality that really changes patients' behaviors and has consequences that are non-invasive but also sometimes life-saving, such as emergency thoracotomy that we had a few times. Eighty-nine of those were translated into verifiable action, so that means that 11% were not executed. Unfortunately, we don't have the data to record what actually was the problem with these, and they could be related to the patient. For example, patient priorities have changed, could be related to logistics, so there was no way available to perform the actual changes. And lastly, of course, the thoracic ultrasound could simply be erroneous and lead to, well, us not performing. And then lastly, the fluid change that reflects the clinician's intent. The question, of course, being would these changes have been, have occurred in the standard diagnostic pathway, and if they would have, would they have occurred as readily as we have made them occur with arthroxia? Of course, there are some limitations to be noted. So, still, just like the other studies, this is physician-reported behavior, and it remains subjective, even if we have feasibility and fluid balance that we check after. We made a clear CRF hierarchy to try to prevent that, but, yeah, it remains subjective. Second question is, would these changes have occurred in the absence of thoracic ultrasound by use of conventional parameters? Well, maybe, maybe at a later time, maybe with more costly or invasive parameters, such as lab, et cetera. And the question, obviously, is, does this really trickle down to patients? Because few imaging modalities have actually demonstrated an improvement. So, the conclusion here that we drew as a group is that the impact of thoracic ultrasound between confirmation and change is convincingly large, to at least be of clinical importance. It was a very nice editorial written by colleagues from Critical Care Medicine, and it was called From Black Man to Ultraman, where they compared the Ultraman study to the initial phases of how the Schwann-Ganz catheter or pulmonary artery catheter was received. But we really saw that it had changes in physician's behavior, but in the end, the outcomes were not what we wanted. And so, the question is, can the same be said about thoracic ultrasound? But, of course, it's more difficult to find a matching and reliable outcome metric, because we can also see the thoracic ultrasound as a physical extension of the physical examination that has a very wide array of indications, that is very repeatable, non-invasive, is cheap, and it's quite low effort. So, there is a difference, and the question is now, moving forward, is it a randomized controlled trial? Is that the only litmus test so we can really say, okay, this is clinically utile, or are we comfortable with the amount of evidence that we have now to say we are a conscientious clinician that knows the indications, that knows the limitations, and that also is aware of the clinical context, may be able to improve the patient? And I think that brings us also to the polling question. So, the question is, is an RCT required to further confirm the utility of thoracic ultrasound in critically ill patients? And for our guests to answer, either no, there is sufficient evidence for full ICU implementation, no, more evidence is needed, and especially on the downstream impact, yes, or I don't know. Okay, so most of the people, almost 100% of the people who voted are saying we do need to look at more downstream impact, and I can definitely find myself in that, and I know that there are some RCTs on the way right now that are examining, especially in terms of balance, what the impact of ultrasound is. Thank you. Well, first of all, thank you to Ryan and Micah for some great presentations today, and for the audience, if you would like to ask a question at any time, please use the question box and type in your question, and I'll answer it to our speakers. I have a question for Ryan first. In your paper, it looked like there were a variety of countries all around the world, and each of them have different health systems and insurance out there. How did the health systems really affect your data? And for someplace like me in the United States where there isn't universal health care, you know, is there differences between the United States that you might have seen, or any hints versus other countries that do have universal health insurance? Yeah, thanks, Tony. I think that's a really good question, and it's one that is incredibly difficult to answer given the state of the literature that we have at the moment, and in fact, actually, that central question about whether insurance makes a difference or not is one of the reasons why we thought that actually might be a huge confounder to our central question here, which is why we excluded studies that just used insurance as an exposure criteria for socioeconomic status. What I can say about the state of the literature at the moment is that we have studies from areas which have universal health care and from areas that have an insurance-based model, and we've got studies from each of those areas that say that there's no association between socioeconomic status and outcomes, and also that there are some other studies that say that there is an association. I think, to be honest, to answer that question, we would probably need a prospective trial that didn't suffer from the same problems with the heterogeneity that we've seen in terms of how we define socioeconomic status, but that's certainly one to watch out for. Thank you very much. Yeah, it's a very difficult question to answer, I'm sure. Next for Micah, I have a question for you. It seems like thoracic ultrasound is a very potential tool for caring for our ICU patients. Where do you see it being used most, and should it be used serially or not, or should it just be a one-and-done point-of-care test? Yeah, thank you for this interesting question. It kind of also brings us back to the matter of how we define usefulness for this tool and for other diagnostic tools. When we go back to that framework from Freiberg and Thornbury from 1991, they gave us these three levels of increasingly impactful options. Of course, my paper, or our paper, focuses on the aspect of purely the diagnostic and therapeutic decision-making. But what we find interesting in the study is that the majority of these clinically-indicated thoracic ultrasounds are used for diagnostic examinations. And I think this is very recognizable from a clinical perspective, because we often take out the ultrasounds when we face undifferentiated crises that require these fast bedside decisions. Unfortunately, the current paper did not examine which type of examination has the best chance of changing diagnostic and therapeutic management. So we have a post-hoc analysis pending that may kind of provide us some answers to this question. But, yeah, if I were to speculate, I would say that probably diagnostic examinations more often lead to bigger invasive changes in management, whilst those serial investigations that you mentioned, or kind of monitoring within the framework of one diagnosis, these examinations probably often lead to smaller changes such as fluid balance. And then, obviously, the question is, what will be the most impactful in patients and society? And that remains to be answered. The obvious answer would be the invasive changes, but I don't think we should underestimate what could be the impact of, for example, fluid optimization on patient length of stay or even mortality. No, thank you very much. And to kind of get with that fluid balance, I think one of the things that I see as a practicing pharmacist is the dissemination of information is not – with ultrasounds, it's kind of hard to get, at least at my institution. And especially when you talk about fluid balance. Antibiotics have a lot of fluids in them. For example, if you're treating steno-trophomonas with trimethoprim, sulfamethoxazole, typically in Ohio, that's 500 to 1,000 mLs per dose, depending on their kidney function, where you might use levofloxacin if they're only IV, and it's 150 mLs, a huge difference per day. And some of that is not communicated to me as a pharmacist. So what can we do to help disseminate the results for the whole team to have the best outcomes on our patient? Definitely. And the example that you make is very fitting. And I do think some of the magic of ultrasound is, of course, the ability to be used at bedside and make direct decisions, direct observations. But I think when you consider it as a serious tool that you want to implement in your ICU, then it's essential to have an electronic system, that you have to save your images and videos and ensure that there is really good dissemination for the rest of your team. And obviously that follows that it's not only your electronic video files, but it should be in patient status, and these findings should be discussed during these meetings. So I think it's also part of the responsibility of serious consequences to the ultrasound user. Well, thank you very much for answering that. Yes, I would completely agree. Going on to the next question, this is for Ryan. And I think you presented some great information, but looking on with social disparities, especially economic disparities and just the fact that global warming, we're starting to feel a lot of it currently. It's predicted to have a lot of adverse health effects, especially the increase in pulmonary disease and exacerbations. What steps can you think that can be taken to impact some of these, especially with smoking and the increase of effects on lower social economic status throughout the world? Yeah, that's a great question. I think that one that probably gets to the core of what we're trying to do with this sort of research, because I think we're potentially, unlike what Mike has presented, which is something that really clearly directly influences the patient's management in front of us. I think that quite often for us that are working in a hospital environment, we're not really able to exert a direct modifier over the problems that we find whenever we find that there's health inequalities. From the climate change perspective, I think that we've got good evidence that climate change is probably going to disproportionately affect the poorest in the world and not only worldwide, but probably within each country as well. I think, to be honest, this research is perhaps a little bit spaced from that, but I suppose what we hope that this kind of work can add is to allow an advocacy within healthcare organisations that these are problems that matter to us as well. And if we can somehow add our voice, and I think that we still have quite a strong voice in healthcare whenever we're thinking about social policy, whenever we think about government policy, I think the evidence that potentially social policies have a direct result for our patients can be quite strong as we advocate for change. So I think that's probably where this fits in on that kind of policy level. Well, perfect. Thank you very much for that. Now for Maika, her question is, I think it's really interesting that there's a lot of interoperator variability with these ultrasounds specifically that we see. Where do you see this being used in conjunction with artificial intelligence? Yeah, I think this is quite a painful point in ultrasound usage. And it's also one that extends to several levels, as in there's different probes that you can use. There's different machines that you can use, especially in sub-segment of thoracic ultrasound. We see that these kind of things make a huge difference for the display of artifacts in lung ultrasound. And of course, there's also different operators, different training levels. So this is a big issue. I think we need more data-driven evidence to kind of match the indications with the settings and probe and protocol that you use. Another thing is that I think increasing training, especially in concordance with the recent literature by, for example, Roba in intensive care medicine, to really see what are the basics and what are the advanced things. And then, of course, after that comes the AI models that are now in development. And there are already several in development. Even on the newest machines, you can already use them to, for example, count B-lines. And these are very interesting because, of course, they're going to create consistency or more consistency if you use it with the same machine. But everyone also, a lot of different AI models are also out there. And they have their distinct differences. So I think right now we should be cautious to kind of universally embrace AI models. And, yeah, let the evidence speak which are appropriate. Well, thank you very much. And Ryan, a question for you is what lessons can we learn from the COVID-19 pandemic? I think we're starting to see some more and more literature out there with socioeconomic status. What things should we be looking for or should we be thinking about that we've learned from the pandemic? Yes. And I think clearly COVID-19 has probably been the defining challenge of our age, certainly for those of us that have worked in critical care during those first waves. I think it's been a huge opportunity here as well to shine a light on how socioeconomic status can impact health outcomes. And I think actually even if you have a look at the papers that we've included in our meta-analysis, you'll see that there's been a huge uptick in interest. And we've actually been able to, I think, strengthen our meta-analysis by including some of those papers that were triggered by COVID-19. I think in terms of a disease itself, as I say, it really shines a light on this problem. We know that poorer people and people who are more socioeconomically deprived, they're more likely to be infected with COVID probably down to features of their employment and for the housing. They're more likely to be hospitalized with COVID, even if it's less severe disease, again, probably down to aspects of social support. They're more likely to die from this disease. And I think, unfortunately, they're more likely to be failed by our healthcare systems because of issues of overcrowding or probably also because of issues where they do not have the provision of healthcare and they don't have the provision of critical care that is seen in more affluent communities. And I think really that, I suppose, gives us a lesson for all of us who are working in health, that outcomes of COVID like any disease are socially mediated. And as I've said before, my previous answer, I would hope that allows us to be empowered, to be advocates for trying to improve those social conditions through any avenue that we do have. Well, thank you. And thank you to both Ryan and Micah for great presentations today and for the audience for attending. Again, anyone who joined us for today's webcast will receive a followup email that will include an evaluation. Please take five minutes to complete the evaluation. Your feedback is greatly appreciated. And on a final note, please join us for our next Journal Club Critical Care Medicine on Thursday, April 27th. And that concludes today's presentation. Thanks. Thanks everyone. Thank you very much.

socioeconomic status

mortality rate

health inequalities

access to care

thoracic ultrasound

clinical management

respiratory pathology

patient-centered outcomes