Good morning, everybody. Thank you all for being here. Our session is titled Sleep, Breathing, and the Heart, and we have a total of six presenters. So each one gets about eight minutes to present and two minutes for questions, so we have to stay on track. So, you know, I'll let you know when you're running close to your time. And please do, you know, talk about your conflicts of interest in the beginning, and if you have nothing to disclose, please say nothing to disclose. And I would encourage all the presenters to stay till the end. So, anybody in the audience, if you have questions, you can also ask them at the end. And please come up to the microphone for the audience if you do have any questions. So we can start with the first one. Questions are right after? Right after. Right after? Yeah. Okay. So Dr. Botros, yeah, please go ahead. Thank you. Okay. Okay, good morning, everyone. Thank you for coming so early. So I'm excited today to present our study entitled Sleep Hypoxemia as a Predictor for All-Cause Mortality. It's a secondary analysis of the Sleep Heart Health Study. My name is Jack Botros. I'm a Dental Sleep Medicine resident at USC. And I have nothing to disclose. Okay, so first of all, our study aims. So we wanted to compare the association of each of the following with the risk of all-cause mortality. First, HI. Second, sleep time percentage with oxygen saturation below 85%. And third, sleep duration with oxygen saturation below 85%. And compare that together. So first of all, to do that, we got access to the Sleep Health Study. And we analyzed about 50, more than 5,400 subjects. Those subjects were about 40 years of age or older with no history of sleep apnea treatment. This study, or this data set, included a baseline examination, including a home sleep study conducted between 95 and 98. The treatment status, whether treated or untreated for obstructive sleep apnea, was determined between 98 and 2001. And finally, the all-cause mortality was tracked from 2001 and until 2010. And we used 85% of sleep, of oxygen saturation, because this is the threshold that was provided in this data set. So to assess the aims of the study, we used a multivariable logistic regression analysis. And we adjusted this analysis for age, sex, BMI, cigarette pack years, treatment status, whether treated or untreated for obstructive sleep apnea. And finally, a cardiovascular score at baseline, which we calculated for each subject. And we gave each subject a point for each of the following. Having a pacemaker, heart failure, MI, hypertension, angina, coronary angioplasty, coronary artery bypass grafting, or any other heart surgery. So we have a score of eight for each subject regarding the cardiovascular score at baseline. So what do you find? First, regarding the AHI. So as you can see here, AHI, as used in the clinical practice, was not associated with all-cause mortality. We have mild, moderate, and severe AHI. Wasn't significantly associated with all-cause mortality in this study. However, there are some other covariates that were expected to be associated with all-cause mortality. For instance, age, cigarette pack years, our baseline cardiovascular score was also associated with the all-cause mortality at the end of the study. And finally, we found that being untreated for obstructive sleep apnea increased the odds of all-cause mortality by 70%. And that was statistically significant. The second aim for our study was sleep percentage below 85 of oxygen saturation. And we find that, as you can see here, it was nicely associated with all-cause mortality, with a subject having more than 20% of their sleep time below 85% of oxygen saturation, had threefold of increased odds of all-cause mortality. And the rest of the covariates had similar, had similar associations with all-cause mortality as the previous analysis. Finally is the sleep duration in minutes below 85% of oxygen saturation. And that also was associated with the risk or the odds of all-cause mortality, with subjects having more than half an hour or 30 minutes below this threshold, having more than twofold increased risk of all-cause mortality. And also, we have all the other covariates with similar outcomes. Also, when we did the same variables as continuous variables, we found similar results with HI was not associated even as continuous variable. Sleep duration and sleep percentage under 85% were also significantly associated with all-cause mortality as continuous variable rather than categorical variables. So, what are the conclusions of our study? First, sleep hypoxemia may be a predictor of all-cause mortality in OSA patients. As clinician, we need to include sleep hypoxemia and sleep saturation below 85% as recommended here or other thresholds that also might be associated for our evaluation of OSA initially and also for treatment outcomes. As researchers also, we need to include sleep hypoxemia in future indices that are assessing the severity of OSA rather than HI, including sleep hypoxemia might be beneficial also for future indices. And finally, this is another study confirming that OSA treatment also could be associated or reducing the risk of all-cause mortality. Finally, I'd like to thank you for your attention and also thank my collaborators, thank you. Hi, everybody, good morning. So, my presentation today is on sleep circulation time reflects cardiac function. My name is Serena Xia. I'm one of the professor at University of Southern California and I have nothing to disclose. So, the study objective today is that, for our study is that we wanted to use sleep circulation time to predict heart function. And by doing so, we're hoping to use sleep circulation time as a reference for early diagnosis and treatment of heart failure. So, some background is that we know that both heart failure with reduced and preserved ejection fraction can be associated with sleep apnea. And we wanted to use circulation time, which can be seen on the, which can be estimated on polysomnogram. And this is sleep circulation time is actually measured with the time between resumption of breathing after an apneic event and the subsequent oxygen saturation nadir. So, that red line over there where it was the resumption of breathing and then it goes down to the nadir of the oxygen saturation. So, normal sleep circulation time is measured as less than 20 seconds. What we use is we use everybody who's 18 years of age, at least 18 years of age with a BMI of less than 40 who have sleep apnea, which is defined as age of over five, who has both an in-lab sleep study plus a trans-thoracic echo within one year of each other. And we calculate circulation time, we measure the circulation time from the first, second, and third sleep cycles, so the stage N2, N3, and REM sleep. We measure the circulation time. And then we also record the left ventricular ejection fraction. So, we used Univariate Analysis, Wilcoxon Rank Sum, and the Jumden's Index for our statistical analysis. So, what we found is that there's a total of 87 subjects that were included, and 12 of them has a left ventricular ejection fraction of less than 40%, which is group A. And then we also have a group B, which has 69 subjects that has normal ejection fraction above 50%. And six subjects has between 40 to 50% of ejection fraction. So, what we found is that all 12 of the group A subject, which has ejection fraction less than 40%, has prolonged circulation time. So, we look at both the REM sleep stage and also the total sleep. So, for the REM sleep stage for group A patients with ejection fraction less than 40%, we found that there's a longer median time of 35 seconds compared to normal ejection fraction patients of 25.5 seconds. And if we look at total sleep, the circulation time for those with heart failure has a median circulation time of 29 seconds versus 24 seconds. And those are statistically significant. We then wanted to further determine is there an optimal cut point value that for both REM and total sleep circulation time? And we did that using Jumden's Index and that maximizes the sensitivity and specificity. And with that, we wanted to predict low ejection fraction. And with the Jumden's Index, we found that the REM circulation time average, the optimal cut point of that is 26.3 seconds. And that has sensitivity of one and specificity of 0.64. And that has a diagnostic accuracy of 0.84 using the area under receiver curve interpretation. So that 0.84 is an excellent discrimination value. And the same thing for the total sleep circulation time, the optimal cut point we found was 27% and that was an acceptable discrimination. So again, this is to emphasize that the cut point for REM sleep with excellent discrimination was 26.3 seconds and the optimal cut point for all sleep with acceptable discrimination was 27 seconds. So we did a univariant analysis to see for which we found that those with REM circulation time of above 26.3 seconds has 12 times more likelihood to have a low ejection fraction. And those with sleep circulation time of above 27 seconds is four times more likely to have low ejection fraction. Unfortunately, they're not statistically significant, but they're close to it. So in conclusion, we found that in sleep apnea patients with BMI less than 40, the sleep circulation time of over 27 seconds has a high probability to have low ejection fraction. And for REM circulation time of above 26.3 seconds, it is associated with low ejection fraction. So the clinical implication of that is that when we look at the sleep study and then we can also look at the sleep circulation time. And if we see the patients with sleep circulation time of above 26.3 seconds for the total sleep circulation, total sleep or 27 seconds for the, excuse me, 26.3 second for REM sleep and total sleep of 27 seconds, maybe we should have an earlier evaluation for their cardiac function with an echocardiogram. Thank you. Hello, thanks for coming this morning. My name is Amr Abunassar. I'm an internal medicine resident. Today I'll be talking about the polysomnographic and clinical characteristics for patients with left atrial enlargement and central sleep apnea with or without AFib during the sleep study. Again, I have nothing to disclose. So this is the team. I wanna acknowledge them all, especially my mentor, Dr. Javahiri. So basically, central sleep apnea is prevalent in patients with heart failure and AFib and could be associated with adverse outcomes. Left atrial enlargement has been shown to correlate with increased carbon dioxide chemosensitivity and higher loop gain, which promotes or could promote central sleep apnea. The correlation between central sleep apnea and left atrial enlargement is very important. The correlation between central sleep apnea and left atrial enlargement in patients with heart failure with reduced ejection fraction has been studied. In this study in 2014, they looked at these patients and found that this correlation. So our study aims to describe the clinical and polysomnographic characteristic for patients with central sleep apnea and left atrial enlargement with normal ejection fraction. We wanna compare these characteristics in patient with or without AFib during the sleep study, and we wanted to assess the correlation between left atrial volume index and central sleep apnea index. So in our study, we had 36 patients of left atrial enlargement that were part of a cohort of 66 patients that were diagnosed with a central sleep apnea or PEP emergent central sleep apnea. Five of these patients had reduced ejection fraction and we excluded them. And we define presence of central sleep apnea as five per hour of central sleep apnea index. 31 patients were divided in two groups based on the presence of AFib at the time of the sleep study, and the sleep study was done with our sleep physician, Dr. Jawahiri, and echoes were evaluated by a cardiologist blindly. So we looked at the anterior-posterior diameter as it was about 2.7 to 3.8 in females, three to four in males, and normal index was 28. And we used these tests to compare both groups and we used the Pearson correlation coefficient. And the P-value was less than 0.05, was significant. So looking at both groups, just the characteristics, the clinical characteristics, including even the sleepiness scale, Epworth sleepiness scale, they were pretty much similar, except that one of the patients that had AFib during the sleep study did not have chronic AFib at baseline and was basically diagnosed during the sleep study. Four, or sorry, eight of the patients that had AFib, no AFib during the sleep study, did have chronic AFib in their history. They were, both groups were obese, they had hypertension prevalent. They were also basically similar in diabetes prevalence, coronary artery disease, and COPD. So, looking at the echo data, here we look at the left atrial size. Basically the patients who had AFib, they had a bigger left atrium in size, and an index as well. And both groups were statistically significant difference, but otherwise they were similar. So, we wanted to look at the potential causes for left atrial enlargement in group one that did not have AFib during the sleep study. So, as I said, there were eight of these patients that had AFib, chronic AFib, and four of them had cardioversion prior to the sleep study. They were within, one had like a year, and the rest were like more than a year before the sleep study. Three had rare and paroxysmal AFib, and one had remote post-CABG AFib. That was about seven years before this study. We looked at the, also the other causes can be diastolic dysfunction in nine of these patients, and 12 of them had left ventricular hypertrophy, and diastolic heart failure diagnosis in 13 of these patients. Then we looked at, you know, in the echoes, we had 12 of these patients had valvular abnormalities as follows, most of them mild to trace. We had one patient with moderate to severe mitral stenosis, and hypertension was in 18 of these patients, 18 out of 21. So, looking at the sleep study data now, the, again, similar characteristics in the sleep study except of the presence of Chyne-Stokes breathing observed during the sleep study. Here, the central sleep apnea index was about 15 and 27, plus or minus, but again, no statistical significance, and HI as well. Looking at the CPAP titration, because all these patients went in to get a CPAP, and basically, CPAP eliminated mostly the obstructive apneas but had central apneas in most of them. Mean index was 21 to 22 in both groups. 12 of them had a PEP emergency central sleep apnea, and two in the other group, two of 10. So, there was no difference in demographics or comorbidities between both groups, and the index was higher in group two, central sleep apnea index was higher compared to group one, but not significant, and there was a positive correlation between left atrial volume index and central sleep apnea index, but non-statistically significant, but close. In conclusion, basically, we conclude that left atrial enlargement by itself is a risk factor for central sleep apnea or CPAP emergent central sleep apnea. Based on animal and human studies, enlarged left atrium associated, and associated increased left atrial pressure increased the loop gain promoting central sleep apnea. We found a positive but not significant correlation between left atrial volume index and central sleep apnea index, and this is work in progress. And clinicians should be aware of the left atrial enlargement due to various causes and the potential relationship to central sleep apnea. Central sleep apnea may occur with or without hunter-shine-stalks breeding. Thank you. I'm ready for questions. Good morning, everyone. Thank you for being here. My name is Alize, and I'm here to present an epidemiologic study assessing the trends in mortality related to both sleep apnea and heart failure over the past two decades. A little bit about me, I'm currently a chief resident at UMass Bay State. And I have no disclosures. So the objective of this study was to assess the trends in mortality related to sleep apnea, mortality related to heart failure, and then mortality related to both conditions present concomitantly, and identify any socio-demographic risk factors among patients with both these conditions. So as we all know, sleep apnea is an increasingly common condition, and it can be present in up to one in every three middle-aged adults. The prevalence of the disease has been increasing over the past two decades, and studies have estimated that it's, the prevalence has increased by about 50% since 2000. There have been a lot of studies assessing the association between sleep apnea and heart failure, and studies estimate that about 50% of all patients with heart failure have sleep apnea. Sleep apnea is also a known risk enhancer for cardiovascular mortality in patients with all cardiovascular diseases, including heart failure. However, to our knowledge to date, there hasn't been any nationwide estimate of the degree of mortality burden associated with sleep apnea in heart failure patients, and more importantly, there hasn't been any nationwide estimate of the trend in mortality, especially given all the advancements that have been made in diagnostic and therapeutic modalities for both these conditions. So for this study, we accessed CDC Wonder. This is a publicly available database by the CDC which records death certificates from all US counties and uses ICD codes to identify underlying causes of death as well as contributing causes of death. We queried all deaths related to heart failure individually, sleep apnea individually, and then both combined. And we analyzed all adults who were over the age of 25 and had passed away since, I'm sorry, year 1999 to 2019. We excluded years 2020 to 2021 because the data for all diseases really was significantly skewed because of the pandemic. We also closely looked at certain demographics among individuals with both heart failure and sleep apnea. So we analyzed gender, age group. For ethnicities, unfortunately, there wasn't enough data to assess for trends among Asian-Americans, but we included non-Hispanic white, non-Hispanic African-American, and then Hispanic and Latino individuals. And then for region, we simply stratified the metropolitan versus non-metropolitan individuals. For analysis, we used CDC Wonder to get age-adjusted mortality rates per 100,000 by standardizing the population to the U.S. population back in year 2000. We used the Joint Point Regression Program to assess the trends in AAMR. So the program assesses any statistically significant change in mortality rate and reports it as an annual percent change. And then we calculated a weighted average of all of these APCs. So over the past two decades, there have been about six million deaths related to heart failure, about 200,000 related to sleep apnea, and 53,000 for patients who had both sleep apnea and heart failure just based on death certificates. Looking at the trends, so overall, over the first 10 years, so from years 2000 to 2010, there was an overall decrease in heart failure-related mortality which eventually plateaued, although this was not statistically significant. We did, however, see a significant increase in mortality related to sleep apnea as well as combined sleep apnea and heart failure. Looking more closely at some of the sociodemographic factors in individuals with both sleep apnea and heart failure, men consistently had higher mortality rates compared to women, but both the groups had a similar increase in mortality over 20 years. We also noticed consistently higher mortality rates among non-Hispanic black individuals. However, the highest AAPC, meaning the highest increase in mortality over 20 years, was actually observed among non-Hispanic white individuals. Among, looking at ages, individuals over the age of 75 had the highest mortality rate and the steepest decline in mortality rate over the past 20 years. And then finally, patients residing in non-metropolitan area had a higher overall mortality rate, but both groups had a similar increase in mortality over the past 20 years. Of course, this study does have certain limitations. So the study primarily relies on death certificates and ICD codes which may have led to some under-reporting of sleep apnea because it's not generally thought of as an underlying or a contributing cause of death. And it also might have led to some bias because death certificate reporting is very subjective, you know, waiting from provider to provider. And then finally, classification of outcomes could not differentiate between mortality related to obstructive versus centrally-seated apnea because ICD-10 codes do not differentiate between the two. And we also could not adjust for confounders. So the increase in mortality could simply be due to the increase in obesity, for example, but with this database, we cannot adjust for confounders. So in summary, we highlight the increasing burden of sleep apnea and heart failure-related mortality despite advances made in both managing and diagnosing the conditions. We also identify high-risk groups, which is adults over the age of 75, men, and non-Hispanic black individuals which might especially benefit from any further efforts made in this field. And we hope that our results would encourage clinicians to have a lower degree of suspecting sleep apnea in heart failure individuals and be more proactive about opting for diagnosis in managing these patients. Also want to give a special mention to all my co-authors who unfortunately could not be here today but contributed significantly to this study. Thank you so much. Thank you. Thank you. Good morning, everyone. Today I'm going to share one of our research projects on obstructive sleep apnea in patients with group 2 pulmonary hypertension. My name is Zeynep. I'm one of the first-year pulmonary and critical care fellows at Mayo Clinic. I have nothing to disclose today. So objectives of this study include the relationship between obstructive sleep apnea in group 2 pulmonary hypertension and the effect of PAP therapy in pH-related clinical markers. A little bit of a background. As many of us know that uncontrolled obstructive sleep apnea has been associated with increased risk of developing cardiovascular diseases and worse outcomes related to those diseases. I would like to take a brief moment to summarize one of the outcomes of one of the previous retrospective cohort studies with a five-year study period here because this was the original study that influenced the research work that I'm going to share today. So we have shown that OSA significantly increases the risk of PE occurrences and recurrences. Within that study, although it was not statistically significant, obstructive sleep apnea treatment with PAP therapy may have some modifying effect on PE recurrences. So we decided to follow those patients for a longer period of time. Instead of five years, we followed them for 10 years. And we were able to show the treatment with PAP independently alleviated the risk of PE recurrences. And as we all know that OSA is strongly associated with pulmonary hypertension and the prevalence reaches as high as 70%. Unfortunately, the available literature is limited to show significant benefit of PAP in pH patients. So that led us to develop two hypothesis for this project. The primary hypothesis was OSA would be associated with worse clinical and diagnostic markers of pH, but treatment with PAP therapy may have some alleviating factor of those risks in patients with group two pH. So this study was approved by Mayo Clinic IRB. We retrospectively analyzed the Mayo Clinic Florida pH registered patients and the study period was 10 years. We investigated the presence of obstructive sleep apnea diagnosis, the severity of it, PAP use and compliance and eventually we compared the diagnostic and clinical findings. These are the data that we abstracted from patients charts, including the right heart cath echocardiogram results and some of the pertinent clinical and lab testing for those pH patients. For the statistical analysis, we use JMP version 16. For non-parametric data, we use Fisher's exact testing and not Wilcoxon and we set alpha at 0.05. This is the baseline characteristic of this cohort. So we had 255 group two pulmonary hypertension patients. About 60% had also OSA diagnosis. Of those patients, PAP therapy was recommended, about 84% of it, but only 64% were compliant with their PAP therapy. Of those 151 OSA patients, 60% had moderate to severe OSA and of those moderate to severe OSA patients, about 60%, 57% were compliant with their PAP therapy. And this was one of our major tables for this study. Unfortunately, we were not able to show any significant difference in mean pulmonary arterial blood pressures in obstructive sleep apnea group versus non-obstructive sleep apnea. So we were not able to prove our first hypothesis, which was OSA is associated with worst clinical and diagnostic markers of pH. The only clinically significant variable here, what the right heart marker was, cardiac output, which was elevated in OSA group compared to non-OSA. There was no difference in echocardiogram markers, but six minute walk distance was longer or the test results were better in non-OSA group compared to OSA. Then we were wondering why we didn't see any significant difference in mean pulmonary arterial pressures. We decided to run some subgroup analysis for those variables. This time we compared the PAP compliant OSA patients with PAP non-compliant ones and non-OSA patients. And in this table, as you can see, mean pulmonary arterial pressure was significantly lower in the PAP compliant group compared to non-compliant ones. And there was no statistically significant difference when those patients were compared to non-OSA patients. The results were similar in six minute walk distance test. The test results were better in PAP compliant patients compared to non-compliant ones. And there was no statistically significant difference in non-OSA patients. Before I further discuss those two tables, I would like to remind the baseline characteristic of this cohort. So 255 group two pulmonary hypertension patients, 60% also had OSA diagnosis. Among those patients, 64% were compliant with their PAP therapy. And 151 OSA patients, about 60% had moderate to severe obstructive sleep apnea. Among those group, about 60% were compliant with their PAP therapy. So just considering that data, we decided to run some additional analysis considering maybe there is some influence on the severity of obstructive sleep apnea may have some influence on mean pulmonary arterial blood pressure. So in fact, the mean pulmonary arterial pressures were significantly lower in the mild OSA group compared to moderate to severe patients. And then we did another subgroup analysis within the moderate to severe sleep apnea patients to see if PAP compliance have any effect on those pressures. And mean pulmonary arterial pressures were significantly lower in the PAP compliant group compared to non-compliant ones. So results in summary, except for the cardiac output, we didn't see any significant difference in right heart cath markers when we compared the OSA patients with non-OSA patients. We didn't include this result in the tables about six minute walk distance. Test results were negatively correlated with mean pulmonary arterial pressures. And the distance was longer in non-OSA patients. PAP compliant patients had significantly lower mean pulmonary arterial pressures and better six minute walk distance results compared to non-compliant ones. Moderate to severe obstructive sleep apnea patients had higher mean pulmonary arterial pressures and PAP compliant ones actually had lower mean pulmonary arterial pressures. So in conclusion, patients who had untreated obstructive sleep apnea has higher PA pressures. The severity of obstructive sleep apnea may correlate with severity of the mean pulmonary arterial pressures. And third, PAP compliance may decrease the PA pressures and help improving the functional status of those patients with group two PH. That's all I have. Thank you very much. Thank you very much. Thank you, Dr. Lal. I'm Rishabh, I'm one of the internal medicine trainees at the Brooklyn Hospital Center. So we did a retrospective database analysis. We talked a lot about so many related studies which were very helpful. In our study, in this retrospective database analysis, we focused on, the outcome of our study was analyzing the tachyarrhythmias in patients who were admitted inpatient for a diagnosis of dilated cardiomyopathy. We thought that dilated cardiomyopathy and is less studied when we look at the association for sleep apnea. And our intention was to see if the outcomes of tachyarrhythmias affected patient outcomes in these patients, and was a driving factor for worse outcomes or more hospitalizations. So the learning objectives for today would be understanding the significance of this association between dilated cardiomyopathy and obstructive sleep apnea. We also, our main outcome measure, the primary outcome was to look at if this comorbidity contributes to arrhythmias either directly or increases the arrhythmia susceptibility in patients with an underlying dilated cardiomyopathy, leading to adverse patient outcomes. And the focus here is to assess sleep apnea as a risk factor in this patient population, trying to extract out the population of non-ischemic cardiomyopathy and towards the idiopathic etiologies. So as we know, we've highlighted the prevalence burden, and we're aware of the prevalence burden of sleep disordered breathing with heart failure. As per one of the meta-analysis, severe OSA was shown to be associated with increased all-cause cardiovascular mortality. Despite this, OSA remains underdiagnosed and undertreated. AHA does have some guidelines to consider sleep studies for patients with NYHA 2 to 4 category heart failure with suspected sleep disordered breathing. Prior studies have also indicated arrhythmia burden being higher in patients with OSA when compared to the general population. As I already, let's look at our database. So I just wanted to give a brief mechanism as to just for our understanding, we wanted to first have a basis why this association would occur. So we looked at certain things, like in sleep apnea, as we know, there's intermittent hypoxia and there's upper airway collapse. Some of these effects, this is like a simplified kind of mechanism where I try to show that because of the overstimulation of the sympathetic nervous system and due to the upper airway occlusion increase in the negative interthoracic pressures, we sort of increase the LV afterload as well as the myocardial oxygen demand, thereby leading to more cardiac remodeling, LV hypertrophy, septal thickening in a heart which already has some structural abnormalities when it's dilated. For methods we use for our analysis, we use the NIS database. It's a publicly available national inpatient sample comprises of approx 20% of annual, they release it every year annually. It captures inpatient hospitalization, hospital stays and is useful for estimating prevalence data related to all these diagnoses. Study population was, we used adult population. We just included patients hospitalized for dilated cardiomyopathy and we looked at obstructive sleep apnea as the secondary diagnosis or comorbidity. And our outcome variable were arrhythmias and we tend to stratify them into both tachy and brady which I'll subsequently. For the analysis we used status version 17, chi-square testing was for categorical variables and the parity test for continuous. And our results were obtained through multivariable regression analysis to estimate the odds ratio and risk. So we generated a good sample size, as you can see for patients hospitalized with dilated cardiomyopathy in 2020. Some of the, I didn't put up like a table for like the baseline characteristics but some of the characteristics I've mentioned here like their mean age group of 64 years. We looked at comorbidities, obesity, some of the metabolic comorbidities, hypothyroidism, alcohol abuse, smoking were some of the relevant ones. In terms of like the arrhythmias, I'll show you in the subsequent table one, we looked at multiple like both tachy as well as brady. And finally we ran the multivariate regression analysis which revealed a positive and significant odds ratio for developing specifically tachyarrhythmias. So in our analysis we noted that the significant tachyarrhythmias because our population was stratified into dilated cardiomyopathy with and without OSA. We found atrial fibrillation, atrial flutter and VTAC was significantly higher prevalence in those patients with OSA. This is a similar depiction of highlighting the increased prevalence in our study group. And in terms of odds ratio, when we, after we adjusted for like relevant clinical comorbidities and the Charson Comorbidity Index to balance out both the cases and control group, we noted an increased odds ratio with a statistical significance for tachyarrhythmias in patients with DCM and OSA. So in conclusion, our study was able to answer our initial hypothesis that OSA in fact does increase the arrhythmia burden in patients who have an underlying structural abnormality in this dilated cardiomyopathy. And in our initial analysis, at least the intention was to identify the non-ischemic cardiomyopathy etiologies to kind of highlight this association. And based on this, we definitely suggest that we should have like a lower threshold in screening patients for OSA, especially in patients with structural abnormalities such as dilated cardiomyopathy. And although additional research prospective studies are required to validate our findings because it's a retrospective analysis, database analysis and we did not have qualitative data in our study such as like the severity of sleep apnea or whether what was their treatment status. But we do intend to in the next step because this was our initial analysis, we do want to also stratify sleep apnea into central as well as obstructive sleep apnea and see like what's the effect in patients with dilated cardiomyopathy on tachyarrhythmias. Yes, that would be our next step over here. Thank you. Thank you Dr. Sena.

obstructive sleep apnea

cardiovascular conditions

all-cause mortality

heart failure

left atrial enlargement

sleep hypoxemia

positive airway pressure therapy

tachyarrhythmias