I would like to thank everybody, our audience, our moderators here, for this opportunity in CHEST. I would like to start my presentation about cardiovascular outcomes in systemic sclerosis-induced pulmonary hypertension. My name again is Saiful Bekir, I'm a PGY-2 internal medicine resident at Staten Island University Hospital, Northwell Health in New York. I have no financial disclosure. This is our objective for today, identify the cardiovascular complications in systemic sclerosis-induced pulmonary hypertension. So first of all, our background would start with systemic sclerosis, we all know it's an autoimmune complex disease that is characterized by activation of both innate and adaptive immunity, affecting the whole body, affecting many systems of the body. Pulmonary arterial hypertension is the leading cause of death after displacing renal crisis after emergence of ACE inhibitors, and compared to idiopathic pulmonary arterial hypertension, systemic sclerosis-associated pulmonary arterial hypertension has increased mortality. The last thing I'll talk about, cardiac involvement is usually asymptomatic, but it's associated with worse prognosis. And we will talk in detail about what's the cardiac involvement in the next slides. So our methods started with, we got the National Inpatient Database from 2016 to 2018. Patients with systemic sclerosis were divided in two groups. Patients were divided in two groups based on the presence of pulmonary arterial hypertension. Patients with idiopathic pulmonary arterial hypertension or pulmonary hypertension groups 2 to 5 were excluded. Other exclusion criteria were like extremes of age, malignancies, or any missing data. ICD-10 codes were used to sample the baseline demographics and comorbidities. After that, univariate analysis, pre- and post-match were performed, and post-match multivariate analysis was performed after that. So going, we got like from the sample around 17,000 patients, 1,200 of them had like pulmonary arterial hypertension. On univariate analysis, we found that acute heart failure, tachyarrhythmias, conduction disorders, and tricuspid valvular disease are statically significant and higher in patients with pulmonary arterial hypertension. So after binary logistic regression, patients with pulmonary hypertension had only a higher conduction disorder and tachyarrhythmias with odds ratios shown there. So according, after reviewing the literature, pulmonary hypertension and systemic sclerosis, both of these diseases independently will increase the risk of arrhythmias. And also conduction abnormality are common there, mainly due to myocardial fibrosis. In addition to precence of pulmonary arterial hypertension will increase myocardial damage leading to worse conduction abnormalities. And it's worth mentioning here that mainly it was found on autopsies that patients with systemic sclerosis has a higher conduction abnormalities, mainly due to myocardial fibrosis, and it does not involve the conduction system. So we found that there is increasing susceptibility to atrial tachyarrhythmias, and it was mainly atrial flutter. And as we know, atrial flutter, it originates from the tricuspid annulus, and it's a region that is susceptible to damage in cases of right ventricle failure resulting from pulmonary arterial hypertension. In addition, pulmonary arterial hypertension, it's a surrogate of advanced systemic sclerosis, making it worse to find that these patients has a higher damage of the myocardial fibrils resulting in a higher risk of conduction disturbances. So also, on the other side, we found that on the analysis that pulmonary arterial hypertension is associated with the development of acute heart failure. However, multivariate analysis did not demonstrate this correlation. And this might be explained by the fact that the precipitants of acute heart failure are commonly present in the setting of systemic sclerosis associated pulmonary arterial hypertension. And the occurrence of heart failure are dependent on these factors and not on the pulmonary arterial hypertension itself. So going to the conclusion, pulmonary hypertension in systemic sclerosis patient is associated with a higher prevalence of conduction disorder and tachyarrhythmias. And the probable etiology of these finds can be attributed to structural damage and myocardial fibrosis, which is found in systemic sclerosis. And it's worse in patients with pulmonary arterial hypertension. And while this pathophysiological explanation of cardiac manifestation is rational, we need further studies to confirm the correlation between these entities. The limitation of our study is, first of all, it's a retrospective study. So hence, it's a point to selection bias. And the accuracy of data is dependent on the practices of coding. NIS inpatient data lacks long-term and outcomes. And the data for functional status of these patients are not available. But however, these limitations were largely reduced by the propensity matching. So just to take a home message, regular cardiovascular monitoring with a lower threshold for cardiac workup and foreclosure monitoring is recommended in patients with systemic sclerosis, particularly after the emergence of pulmonary hypertension. And emphasis should be placed on dedicated cardiovascular screening guidelines to prevent mortality and morbidity. Thank you. All right. Good afternoon, everyone. I'm presenting the topic, Impact of Diabetes Mellitus on Mortality in Pulmonary Hypertension, a Systematic Review and Meta-Analysis. Thank you, everyone, for joining us today, this afternoon. I'd like to thank the moderators for the contribution here. I'm Dr. Smitesh Parthe. I'm from Mumbai, India. And as you can see, I have nothing to disclose, no financial disclosures. I am even wearing the same suit in the photo. So objectives. What I want after this eight-minute talk is that you guys get two things. The first is that we assess the influence that diabetes mellitus as a disease has as a comorbidity on survival in pulmonary hypertension patients. And second, to analyze if it's affecting any particular or specific demographic characteristics. So let's start with a brief background. Pulmonary hypertension, as we know, is a chronic progressive vascular disease characterized by endothelial remodeling, resulting in increased resistance of the pulmonary vasculature. We all know that. We also understand that it is associated with its whole multitude of comorbidities. For instance, we have hypertension, we have coronary artery disease, we have congestive heart failure, we have COPD, and then we have diabetes mellitus. And all of them affect the prognosis and survival in their own possible way. But coming back to diabetes mellitus, the talk of this hour, it needs no introduction. One of the most widely researched diseases worldwide. It has been linked to endothelial dysfunction, oxidative changes, inflammatory state, which are all key contributors to the pathogenesis of pulmonary hypertension. Before I go to the last point, it actually answers one important question. What are we doing here? Why did I do this paper? And what does this paper tell? What kind of research gap am I trying to fill? And that is that despite diabetes mellitus, it is well known that it has an impact on pathogenesis in pulmonary hypertension. We do not know the impact it has on mortality in this deadly disease, pulmonary artery hypertension. So what did we do? We conducted a systematic review. We searched the two most expansive databases, PubMed and Embase. We used multiple key terms like mortality, diabetes, pulmonary hypertension. We clubbed them together with an appropriate Boolean operators, and then we had ourselves a search protocol. Our goal was pretty clear. It was to establish a link between mortality in pH patients who had diabetes as a comorbidity, and those with pH without diabetes as a comorbidity. That was the main goal. So for this, we had a bunch of specific inclusion and exclusion criteria. I'll get there, but before that, a quick glance at the PRISMA table will let you know that we started with 901 studies, out of which we trickled down to 34, which were available for full-text screening, from which we ended up with seven that were included in the meta-analysis. For the inclusion criteria, to keep our research up-to-date, papers from only last 10 years were included. Papers in English language and full free papers, they are the ones we included. As I said earlier, we were looking for papers which had value and data, and mortality events in patients with pH and DM both. After that, out of those seven, we had one randomized control trial and six cohort studies. So for each study, we calculated a crude odds ratio using events and non-events mortality, and used a randomized effects model to account for variability within and between the studies. The outcomes were analyzed using the Mantel-Hazel method to get a dichotomous pooled odds ratio. We also anticipated heterogeneity, and therefore assisted using the Cochrane Q-value and the I-square statistics. So my favorite slide, the results section. Out of the 4,500 patients with pulmonary hypertension, we found that 682 were diabetics, while the remaining 3,900 were not. Our good friend the forest plot will tell you that the unadjusted odds ratio clearly indicates higher mortality, the odds ratio being 1.89, the P-value being significant in the diabetic groups compared to the non-diabetic group. The I-square, that is the heterogeneity, was also 66%. Our heterogeneity actually prompted us to do a sensitivity analysis. Now what that is, a sensitivity analysis basically tells you the impact that each study has on the summary outcome. So once we did that, we excluded the study Rosenkrais et al., and the resultant association was actually stronger, the odds ratio climbing to 2.07, while the I-square, that is heterogeneity, now being very good, that is 15%. Secondary results would include a demographic outlook on the population. The study population was analyzed, and we found that 67% were actually females, while 32% were males. Amongst those, hypertension was the most commonly associated comorbidity, 69% of the patients reporting it. It was also the most commonly associated comorbidity in the studies. Six out of the seven studies had hypertension as the most frequently reported comorbidity. The mean age of patients in the diabetics and the non-diabetics did not differ by much. It was around 55 plus minus 15 in both the populations. So to conclude, I would like to begin by talking about a very exciting feature that is the strength of our study. To our knowledge, we believe that this is the first ever systematic review and meta-analysis conducted on this topic. The second thing I would like to highlight is that all the included studies had a very low risk of biases, which was confirmed using the appropriate tools. We used the Cochrane tool for RCT and the NIH scale for the cohorts. Limitations as of all papers, we also acknowledge our limitations. This was a systematic review, so our data is observational. Therefore, no causal influences can be drawn to this. Out of the seven studies, some were adjusted for factors like obesity and hypertension, while some were not. And finally, we also acknowledge that we searched only the main databases, like PubMed and MBase, but we did not search others like ISI Web of Knowledge or even Scopus. Future directions is actually a very interesting part. It tells us, what does our research do? Our research actually propels future research into the pathophysiological mechanisms of exactly how diabetes mellitus as a disease affects PH patients in regards to mortality or with prognosis. It might also propel future research into PH patients who had controlled or perhaps uncontrolled diabetics to see if there's a difference in outcomes or a difference in prognosis. And eventually, I hope that this might lead to some outcomes or some breakthrough in treatment protocols related to, again, diabetics in pulmonary hypertension patients. Thank you very much. That's it from my slide. Again, I'm Smitesh Parthe. I would like to connect with you all for future research. It's my LinkedIn and this, and thank you very much for bearing with me in the last eight minutes. Good afternoon, everyone. My name is Arsal Tarwani. I'm one of the first-year fellows at Cleveland Clinic Foundation. It's very nice to meet you all. Thank you for coming in, and thanks for the opportunity to present. So my study is focused on association of socioeconomic status with chronic thromboembolic pulmonary hypertension. I wanted to thank my mentor, Dr. Heracy, for giving me the opportunity to collaborate with him on this project. I have no conflicts of interest to disclose. So before I go into my project, I want to talk a little bit about background so that we're all on the same foundation level when we're looking at CTEF from a pulmonary hypertension perspective. From what we understand about CTEF is we understand it's a group four pulmonary hypertension disorder. We understand that it arises in a small proportion of patients after acute pulmonary embolism. 0.5 to 3% of patients are usually affected by it, and because of the rarity of the disease, we understand that it's an underdiagnosed entity and most commonly misdiagnosed as well. And one of the barriers to utilization and detection of CTEF in our general population is underutilization of VQ scan. However, it remains to be seen whether socioeconomic status is associated with poor outcomes or associated with any outcomes in CTEF. We understand that in various other pulmonary disorders, particularly cystic fibrosis, asthma, COPD, we know from literature that a low socioeconomic status is associated with poor outcomes in these patients. But we have, in literature, there's currently a lack of data defining association of socioeconomic status with CTEF, and that's what our study is going to be investigating. So we only looked at patient population that were being seen at Cleveland Clinic from 2011 to 2021. It was a retrospective observational study. These were patients diagnosed with CTEF. We defined CTEF as a mean P of greater than or equal to 20 with a PVR of greater than or equal to 3 and a wedge of less than 15 with pre-capillary pulmonary hypertension, and we need to have evidence of VQ mismatching or chronic thromboembolic disease, which is detected on a CT pulmonary angiogram. And we used standard clinical demographic data and hemodynamic data, which was collected during this process, and we'll explore this in the results as we talk about it. When it comes to determination of socioeconomic status, we looked at what was the time in which they presented and what was the patient's street address and zip code recorded at the time that they came in and were seen in our system. And the use of zip codes has been defined in literature as a reliable marker of socioeconomic status, and we understand that agency for healthcare research and quality has shown zip code to be a reliable marker for socioeconomic status. Now, using United States Census Bureau, going to data.census.gov, we used the American Community Survey, we used the inflation-adjusted median household income for the time they were seen first in clinics. So let's say they were seen in 2011, we go to 2011 median household income for that time and use American Community Survey to determine their median household income. And after that, we divided their median household income into quartiles, which are listed on the screen here, and we compared our continuous variables using t-test or Kruskal-Wallis test, and then our categorical variables were compared using the Fisher's exact test or using the chi-squared test. And our analysis were performing at a significance level of .05, and we used the SAS software. So after all of this, we had 352 patients that were included in our study. And the median household income combining for all these 352 patients was $50,671 U.S. and interquartile range was $23,129. We found that our mean age was 54 and a half years of age, and most patients were male and they were Caucasian, with predominantly 74% being Caucasian at the time. This is our results section, and I want to start off by first looking at the first row of this column, of this table. So if you look at the age, as our socioeconomic status improves, we're finding that our patients are getting significantly older. In terms of looking at distribution within each quartile of males and females, it more or less is equal here, but analyzing for the whole cohort of this population, males are 52.5% versus females. And then when we look at our race demographic, we find that if you look at the lowest socioeconomic status, we're looking at African American individuals being represented here, but as the socioeconomic status is improving, we're finding that there's less representation here. And as the socioeconomic status improves, we're finding that the Caucasians are more likely to be represented. But that finding is not significant here, and then when you look at the BMI, there is no significant association of the BMI with any income quartile here. When we look at the NYHA class, most of these patients, regardless of the quartile, are going to be NYHA class three and four at the time of presentation, but this association is not really significant between the quartiles. And I wanna draw your attention towards NT Pro BNP and six-minute walk distance. Even though the NT Pro BNP has no significant difference between these income quartiles, if you look at the six-minute walk distance, remember when I said that as you look at the age, these patients are likely gonna get significantly older with each income quartile, but when you look at the six-minute walk distance, you're finding that patients in the higher income quartile are likely going to do, going to accomplish a higher six-minute walk distance, and that association was significantly different between these income quartiles. Then we look at the hemodynamics here. There are a lot of variables we looked at when we looked at the hemodynamics here, and we looked at the RA pressure, the mean PA pressure, and over here, it really is not really different between any income quartile over here, but as we draw attention, the PBR also was not really different, but regardless of how you calculate the cardiac output, the FICS, cardiac output by thermodilution or by FICS, it significantly shows that as you increase the income quartile, the cardiac output and the cardiac index and mixed meanness is basically going to improve here as well. We looked at PTE and BPA as well, and we found that basically there is no difference between any of these as well in terms of mechanical intervention being offered as well. We looked at pulmonary thromboid and artrectomy mortality between the income quartiles as well, and the higher ones were basically associated with, there's no difference between the two and equal representation of mortality was basically seen in all income quartiles. This graph was looking at long-term survival and hospitalization between the income quartiles, and here, none of these income quartiles showed any significant difference between hospitalization or long-term survival. With regards to discussion, I'll just keep it very brief here because of lack of time. So from what we understand is, the reason why we think that the six minute walk distance for these patients may be lower and the severity of outcomes in terms of cardiac output and cardiac index and mixed meanness is worse is because of perhaps delays in diagnosis. We're looking at symptom onset to the time of diagnosis, to symptom onset to the time of right heart gap to investigate this. Maybe there is an intrinsic factor here which is associated with this, with high inflammatory burden which is seen in the lower socioeconomic status. And a reason for no difference in survival could be due to therapeutic modalities offered at our institution. And our strength of studies is the first time that we're looking at it, and our limitations are that perhaps socioeconomic index, looking at occupation and education of our patients as a socioeconomic index may be a better marker for looking at long-term outcomes of our patients. Sorry if I went overboard with my time. These are my references. Good afternoon one and all, and thank you so much for participating in today's session on severity and outcomes of disease and pulmonary vascular disease. My name is Kaushik Kumar. I'm a resident internal medicine at MedStar Health, and I'm excited and privileged to present our data on outcomes of hospitalizations with acute respiratory distress syndrome, with and without pulmonary hypertension. I have no financial disclosures. So acute respiratory distress syndrome and pulmonary hypertension are not novel entities in critical care, yet their confluence within a single patient presents a unique clinical challenge. Acute respiratory distress syndrome is characterized by an acute lung injury that can happen due to underlying illnesses like pneumonia, sepsis, or trauma. Approximately 10% of the ICU admissions globally are attributed to acute respiratory distress syndrome, and almost 190,600 patients identified annually in US alone. Pulmonary hypertension is a known consequence that can exacerbate ARDS via multiple mechanisms like pulmonary vasoconstriction, thromboembolism, and interstitial edema. Our objective was to identify if pulmonary hypertension in ARDS patients serves as a predictor for worse outcomes, given that the pulmonary hypertension is likely contributing to illnesses in acute respiratory distress syndrome. Our primary data source was nationwide inpatient sample between 2016 to 2018, and this timeframe was chosen to exclude the influence of COVID-19 and coincide with the adoption of ICD-10 coding system. That allowed for more accurate identification of ARDS via ICD codes. We retrospectively identified US hospitalizations using the ICD codes, and we focused on adult patients diagnosed with ARDS. They were further characterized based on the coexistence of pulmonary hypertension. Our outcomes for interest were in-hospital mortality, length of stay, and cost implications of these diagnoses. All data were de-identified and publicly available, adhering to ethical guidelines. Again, we focused on comparing the outcomes between patients with ARDS with and without pulmonary hypertension, and we used multivariate logistic and linear regression models adjusting for several confounding factors, including age, biological sex, comorbidities, insurance status, and hospital characteristics. Summary statistics were used to describe the study cohort with bivariate analysis conducted to determine association between the outcome and explanatory variables. Again, hospital charges were converted to costs using appropriate HCUP, Hospital Care Utilization Project conversion tables, and study preparation followed recommendations of the equator strobe guidelines for observational studies. We identified a total of 156,687 patients with ARDS, out of which 16.8% patients were identified to have concomitant diagnosis of pulmonary hypertension, and during our analysis, we identified that patients with ARDS and concomitant pulmonary hypertension were more likely to be older and more likely to be female with higher comorbidities. We can see from the plot here on your extreme left there's in-hospital mortality on the y-axis, and there's age on the x-axis. The blue color depicts ARDS alone, and the red color depicts outcomes with the patients' ARDS with concomitant pulmonary hypertension. And as for our primary outcome, we can see that ARDS alone patients had a mortality of 24.6% and concomitant pulmonary hypertension, 36.8%. Our key secondary outcomes were length of stay. For ARDS alone, there were 10 days, and with patients with a pulmonary hypertension, they had an average length of stay as 12 days. Total hospitalization costs, again, were higher for patients with ARDS and pulmonary hypertension at $210,165. Again, this slide kind of goes over the adjusted analysis, and we calculated the odds ratio for in-hospital mortality. We can see that odds of death were 52% higher in patients with ARDS and pulmonary hypertension group, and we can see that patients with ARDS and pulmonary hypertension required a longer stay. That was 37% higher than patients with ARDS alone. As for total hospital expenditures, the mean expenditure was higher by $19,406 for patients with ARDS and concomitant pulmonary hypertension. This table kind of goes over the results. Again, one might anticipate that the coexisting clinical conditions and critical illness, such as ARDS and pulmonary hypertension could worsen outcomes, but really our goal was to identify by what magnitude does pulmonary hypertension impact patients' outcomes with ARDS. And as from our results, we found that patients with ARDS and concomitant pulmonary hypertension, they had worse outcomes in multiple metrics. We primarily focused on in-hospital mortality rates, length of stay, and total hospital utilization from the cost perspective. Despite advancements in management of ARDS, prevalence remains really high, and we are being mindful of RV failure, acute cormonal, which is the extreme of pulmonary hypertension. Prior studies, there were a few randomized control studies done to identify really how bad does pulmonary hypertension affect patients with ARDS, but really they were targeted on oxygenation as is with all the ARDS studies, rather than focusing on pulmonary hemodynamics. And as is, for limitations, as is with retrospective observational data with large database such as National Inpatient Sample, our data lacks echocardiographic profile of the patient's right heart cath data, lab test imaging. So these granular data that can further characterize a patient with pulmonary hypertension, which does limit our depth of findings, and then there are obviously coding inaccuracies with ARDS diagnosis, usually JAT diagnosis for ICD. And so just to go over our conclusion, the takeaway points our clinician should be vigilant with in identifying patients with pulmonary hypertension early on, so for management of ARDS. Potentially, pulmonary hypertension can be a surrogate for disease severity in patients with ARDS, and there are substantial financial implications of this as well. And future studies can be focused on prospective designs, and really what I'm really interested about is ICU survivorship, and it can be focused on how patients do after their discharge from the ICU. These are the people that I want to really thank, Dr. Elizabeth Zephra for her guidance and mentorship, and Healthcare Utilization Project. Thank you very much. Thank you. All right. Good afternoon. I'm going to be discussing the effect of AKI on hospital-based outcomes in patients admitted with pulmonary embolism. My name is Mike Goulet. I'm one of the pulmonary critical care fellows at Temple in Philadelphia. I have no financial disclosures. The lesson objective today is to understand the impact of AKI on in-hospital mortality and length of stay in patients admitted with acute PE. So just wanted to take a quick second to refresh our memories about the risk stratification element from the ESE guidelines. I'm sure we're all familiar with these. But basically, when we are risk stratifying a patient with acute PE, we start with sort of our bedside evaluation. We can use our PE severity index as listed there. And then we move on to an assessment of the right ventricle. So we look for evidence of RV dysfunction via imaging and via cardiac biomarkers. Once we have that information, we can risk stratify our patients into a low, intermediate high or high risk of 30-day or in-hospital death. One interesting aspect of this risk stratification algorithm is within that intermediate risk cohort, so you are a patient who is PESI positive but hemodynamically stable, when you go from an intermediate low to an intermediate high risk category, there isn't a tremendous increase in 30-day mortality, which I found interesting. And this is illustrated nicely by Beccatini et al. in 2016. So this was actually in response to the 2014 ESE guidelines, which sort of lay out this same risk stratification algorithm. But as you can see there from the chart on the left looking at 30-day mortality, when you go from an intermediate risk, I'm sorry, intermediate low risk to intermediate high risk, there's not a very large jump in that 30-day mortality. The intermediate low mortality here was around 6% and intermediate high was about 7.7. So not quite as high as you may expect. So we need more information. You know, we need other biomarkers or other variables that can help identify patients who are going to do poorly, especially within this sort of intermediate risk category. One potential variable to consider is renal function at the time of presentation. So we know from older literature cited in the, you know, nephrology world and the K-DIGO guidelines that AKI by itself is an independent risk factor for mortality in hospitalized patients regardless if you have a PE or not. But that seems to be relevant in PE patients as well. So I picked out a few studies I found were particularly interesting and just to sort of briefly summarize some findings. In that top one by Kostriubiak et al. in 2010, they found that in patients who were hemodynamically stable, who had a positive troponin, if your EGFR was less than 35, your mortality was around 48%. If your EGFR was greater than 35, your mortality was only around 11%. So there was a huge difference there when you stratify these patients with their renal function. In the second study there, also Kostriubiak et al. from 2019, they found that EGFR was an independent risk factor for mortality and they found that EGFR was significantly lower in non-survivors with a QPE compared to survivors. And then when EGFR was added to the ESC risk stratification algorithm, it helped to identify, helped to better identify low and high risk groups. And then lastly, by Chopard et al. from 2021, they found that in specifically intermediate low risk and high risk groups, there was a significant increase in mortality when your EGFR was less than 60. So for our study, and these were all European studies, the ends were, ranged from about 200 to about 2,000. So we wanted to look at some U.S. data in a very large sample size. So we also used the Nationwide Inpatient Sample. We did a retrospective cohort analysis of 516,000 admissions with a principal ICD-10 code of QPE from 2016 to 2018, also including, you know, the time where ICD-10 was implemented and excluding COVID. We used Stata software for our statistical analysis. We used a chi-squared test for categorical variables, t-test for continuous variables, logistic regression for categorical outcomes, and linear regression for continuous outcomes. And what we found was that there was a significant association between AKI and mortality. So on the left, you see that if you had a principal diagnosis code of QPE and you did not have an AKI, risk of death was 1.9% in the hospital. So this is all looking at in-hospital mortality, not necessarily 30-day mortality. If you did have an AKI, risk of death was much increased at 10.66%. So that gives us an odd ratio of 5.3, and this was statistically significant with a p-value of less than 0.01. We also took a look at length of stay and found that, on average, you stayed in the hospital 2.1 days longer if you had an AKI compared to if you did not. This was adjusted for comorbidities that you see listed there, also statistically significant. So I think that our study adds to a growing body of literature that suggests AKI is an important, or renal function, rather, is an important variable to consider in acute PE patients. I think the strengths of our study are this very large sample size. You know, the nationwide inpatient sample is a great tool for research. But the limitation, as was sort of mentioned in the last talk, based largely on ICD-10 coding. So we didn't have the ability to sort of dig much deeper and say, you know, which patients were high risk, intermediate risk, low risk within our sample. And it, you know, relies on the accuracy of coding by the providers and billers and coders. So I think that is a big limitation to not be able to get more granular data. But in conclusion, per our study, in US patients hospitalized with acute PE from 2016 to 2018, a diagnosis of AKI was associated with a significantly increased risk of mortality and a longer length of stay. Thank you very much.

cardiovascular complications

systemic sclerosis

pulmonary hypertension

prevalence

conduction disorder

tachyarrhythmias

acute heart failure

PH