Atrial fibrillation is an independent risk factor for mortality among patients hospitalized for alcoholic cardiomyopathy: a nationwide in-patient analysis

Atrial fibrillation is an independent risk factor for mortality among patients hospitalized for alcoholic cardiomyopathy: a nationwide in-patient analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Atrial fibrillation is an independent risk factor for mortality among patients hospitalized for alcoholic cardiomyopathy: a nationwide in-patient analysis Kayode Emmanuel Ogunniyi, Olumide Akinmoju, Ikponmwosa Jude Ogieuhi, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7252791/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Alcoholic cardiomyopathy (ACM) is dilated cardiomyopathy resulting from chronic alcohol consumption and is associated with significant mortality. Atrial fibrillation (AF) frequently coexists with ACM, but its specific impact on patients hospitalized with ACM remains unclear. We aimed to evaluate the association of co-existing AF with short-term clinical outcomes in ACM. Methods A retrospective cohort study was performed using the United States National Inpatient Sample database for 2021. Inpatient mortality, total hospital charges, length of hospital stay, mechanical ventilation rates, and vasopressor use were compared between patients aged 18 or older, with and without atrial fibrillation. Univariate logistic and linear regression analyses were used for hypothesis testing; multivariate regression analyses were then used to adjust for confounders. Student T-test and Pearson’s chi-square test were used to compare population demographic features. Analyses were performed using STATA/BE 18.0. Significance was set at 0.05. Results Of 590 ACM admissions identified, 145(25%) had atrial fibrillation. There was no significant difference in age (53 vs. 50 years; p=0.32) or gender (p=0.44) between the subgroups. The in-hospital mortality rate was 10.3% and 1.1% among those with and without atrial fibrillation, respectively (Odds ratio, OR=10.2; p=0.049). When adjusted for age, race, gender, Charlson comorbidity index (baseline functional status), and size of healthcare facility in a multivariate logistic regression analysis, atrial fibrillation remained significantly associated with increased mortality risk (OR= 20.2; p<0.001) and became significantly associated with increased vasopressor support (OR=6.05; p=0.049) among ACM patients. There were no significant differences in total hospital charges (p=0.063) or length of hospital stay (p=0.081) on adjusted analyses. Conclusion Coexisting atrial fibrillation in patients hospitalized with alcoholic cardiomyopathy independently correlates with markedly higher in-hospital mortality and an increased need for vasopressor support. These patients require close monitoring and proactive management of atrial fibrillation. Further research is needed to elucidate this topic. Alcoholic Cardiomyopathy Atrial Fibrillation National Inpatient Sample In-hospital mortality Arrhythmia Dilated Cardiomyopathy 1. Introduction Alcohol cardiomyopathy (ACM) was first clinically reported in the 19th century with a prevalence in Bavarian beer drinkers, the “Münchener bierherz,” also with an epidemic of heart muscle failures associated with arsenic-contaminated beer in England [ 1 ]. ACM primarily affects individuals with prolonged alcohol use disorder. It accounts for approximately 20% of all dilated cardiomyopathy cases in certain places. ACM results from alcohol toxicity, with the onset typically occurring after a decade or more of heavy drinking, usually 80–100 g/day or more of alcohol. The effects of this toxicity on myocardial cells lead to cellular apoptosis, oxidative stress, and mitochondrial dysfunction, which underlie the resultant cardiomyopathy [ 2 ]. These structural and functional defects manifest clinically with symptoms of heart failure with reduced ejection fraction (HFrEF), marked by left ventricular dilation and systolic dysfunction, often accompanied by arrhythmias such as atrial fibrillation (AF) [ 3 ]. Patients with ACM tend to have a 5-year mortality rate of 49%, which is significantly higher compared to the other types of dilated cardiomyopathy. The mortality rate associated with ACM is multifaceted, which could be progressive heart failure, comorbidities, slow medical therapy, and arrhythmias such as AF. These findings encourage early detection and management of ACM patients for a better survival rate [ 4 ]. Atrial fibrillation increases the mortality rates of patients with ACM by almost 10 times more than ACM without Atrial fibrillation. Acetaldehyde, a byproduct of ethanol metabolism, causes the production of collagen, which increases the fibrosis of the myocardium and disrupts the electrical stability of the atrium; continuous occurrence leads to prolonged repolarization and high affinity for atrial fibrillation [ 1 ]. Reduced arterial functions affect ventricular filling, increasing diastolic dysfunction, which complicates cardiac output by worsening systolic function, leading to quicker heart failure. Heart failure is a common complication of AF with increased mortality risk [ 5 ]. Analyzing atrial biopsy confirmed fibrosis, intercellular space expansion, myofibrillar loss, and decreased cardiomyocyte density facilitated a reduced global left atrial voltage, a key indication for structural remodeling [ 6 ]. Assessing the clinical outcome of the study shows that atrial fibrillation coexisting with ACM has in-hospital mortality rates higher at 10.34%, compared to 1.12% in ACM patients without AF. This could directly influence the complexities of more cardiac failures, neurological complications and thromboembolic risk, most commonly ischemic stroke - where irregular rhythm causes blood pooling or circulatory stagnation and thrombus formation, especially in the left atrial appendage. This mechanism underscores the possibility of ischemic stroke and a decline in neurological functions [ 5 , 7 ]. The frequency of occurrence of these complications has been reported to be age and gender-related, occurring more among older patients and male patients even after a clinical intervention with an assisted device [ 8 ]. The decline in functional capacity affects the overall functionality of the body. It worsens atrial function and reduces exercise tolerance [ 9 ] This study highlights the gap in understanding the effects of atrial fibrillation on in-hospital patients with Alcoholic cardiomyopathy, two conditions that affect cardiac malfunctioning. Although both ACM and atrial fibrillation have well-documented mortality risks, the role of AF in adding an extra complication has not yet been fully studied. This research focuses on how AF is a major determining factor for in-hospital mortality risk for patients with ACM, emphasizing its role as an independent predictor. This study shows the relevance of timely and localized approaches for improving clinical outcomes and proactive management. It also heightens clinical awareness for patients with ACM and atrial fibrillation, with more indication for future guidelines and healthcare policies. This study aims to evaluate if atrial fibrillation is an independent predictor of mortality risk in hospitalized patients with alcohol cardiomyopathy by analyzing data from a nationwide inpatient study and controlling for primary characteristics and comorbidities. 2. Methodology 2.1 Data source For this study, data were sourced from the 2021 National Inpatient Sample (NIS) database, which is managed by the Agency for Healthcare Research and Quality (AHRQ) under the Healthcare Cost and Utilization Project (HCUP). The NIS serves as a comprehensive repository of patient discharge information from non-federal, short-term acute care hospitals across the United States. It is constructed using a stratified probability sampling design, where stratification considers various hospital attributes such as geographic region, urban versus rural location, hospital bed capacity (categorized as small, medium, or large), ownership type (government-owned or private), and teaching status. Within each defined stratum, 20% of hospitals are randomly selected, and the collected discharge data are weighted to ensure they accurately represent the national landscape. Since the NIS dataset is publicly available and fully de-identified, this research did not require ethical approval from an institutional review board or the acquisition of informed consent. 2.2 Study design and population This study is a retrospective cohort study of inpatient admissions for Alcoholic cardiomyopathy, comparing outcomes between those with atrial fibrillation and those without. The inclusion criteria were patients 18 years of age and older with a principal Alcoholic cardiomyopathy. A principal diagnosis is defined as the diagnosis on discharge or after hospitalization outcome after all insights from clinical, laboratory, imaging, and other evaluations are available. Diagnoses were identified using the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes and included in the study group. We used the ICD10-CM code “I42.6” to identify 590 patients with alcoholic cardiomyopathy as their principal diagnosis. We subdivided the study population based on the presence or absence of a secondary diagnosis of Atrial Fibrillation. We used the ICD10-CM codes "I48.0", "I48.1", "I48.2", "I48.91", "I48.3", "I48.4", "I48", "I48.11", "I48.19", "I48.20", "I48.21", "I48.9" and "I48.92", to identify those with a secondary diagnosis of atrial fibrillation. The covariates were identified using the appropriate codes. The supplementary table provides a full list of ICD10-CM codes. 2.3 Outcomes Outcomes were compared between the cohorts ACM with AF versus ACM without AF. The primary outcome was in-hospital mortality (death during the hospitalization encounter). Secondary outcomes were invasive mechanical ventilation, vasopressor requirements, length of hospital stay, and total hospital charges. 2.4 Statistical analysis Baseline characteristics of the study population were assessed by calculating means for continuous variables and proportions for categorical variables, including the prevalence of comorbidities. Given the sufficient sample size in this research, categorical proportions were evaluated using Pearson’s chi-square test, and continuous variables were compared utilizing Student's t-test based on the assumptions of the Central Limit Theorem. Univariate logistic and linear regression analyses were used for hypothesis testing, and multivariate regression analyses were used to adjust for confounders. The multivariate logistic regression model included age, gender, race, the Elixhauser comorbidity index, and the hospital bed size. The Elixhauser Comorbidity Index is a system that classifies a wide range of patient comorbidities using ICD diagnosis codes. It is extensively utilized to predict in-hospital mortality by accounting for multiple chronic conditions. By incorporating these diverse comorbid factors, the index enhances the accuracy of mortality risk assessments in clinical and administrative datasets. All statistical analyses used Stata® version 18 (StataCorp LP, College Station, TX). To account for the NIS's stratified sampling design, survey (svy) commands were employed. A two-tailed P value of 0.05 was established as the threshold for statistical significance in all tests. 3. Results 3.1 Population characteristics A total of 590 hospital admissions for alcoholic cardiomyopathy (ACM) were identified, comprising 145 patients (24.6%) with concurrent atrial fibrillation (AF)- AF group- and 445 patients (75.4%) without AF- non-AF group. As shown in Table 1 , there were no statistically significant differences in baseline demographic variables. The mean age in years of patients was 51 years. There was no significant difference in age (53 vs. 50 years; p = 0.32) or gender (p = 0.44) between the subgroups. Similarly, there was no statistically significant difference in hospital bed size (p = 0.160), race (p = 0.287), or median household income for the patient’s ZIP code which represented their socioeconomic status (p = 0.33). However, the Elixhauser comorbidity index stands out, indicating a statistically significant difference between the AF and non-AF groups (p < 0.0001). Although none of the AF patients presented hypertension, hypertension also stands out as a significant factor for mortality with a statistical significance of (p = 0.047). (Table 1 ) Table 1 CHARACTERISTICS OF THE STUDY POPULATION VARIABLE ACM WITH AF ACM WITHOUT AF TOTAL ACM ADMISSIONS p-Value Total 145 445 590 Age mean +-SD (years) 53.31 +- 13.92 50.53 +-12.74 51.21+- 13.03 0.32 Gender 0.44 Female 13.79% 20.22% 18.64% Male 86.21% 79.78% 81.36% Hospital Bed size 0.160 Small 24.14% 14.61% 19.6% Medium 17.24% 34.83% 27.7% Large 58.62% 58.62% 52.7% Race 0.287 Caucasian 78.57% 57.47% 66.87368 Black/ African American 17.86% 25.29% 17.83835 Hispanic 3.57% 11.49% 8.77446 Asian or Pacific Islander 0% 0% 3.29413 Native American 0% 3,45% 0.50222 Others 0% 2.30% 2.71716 Median Household Income for Patient’s ZIP code (Socioeconomic Status) 0.33 Quartile 1 21.43% 40.70% 35.96% Quartile 2 21.43% 16.28% 17.54% Quartile 3 32.14% 23.26% 25.44% Quartile 4 25.00% 19.77% 21.05% Elixhauser Comorbidity Index (means +-SD) 7.31+- 2.07 5.26 +- 1.76 5.76 +- 2.03 < 0.0001 COMORBIDITIES Liver Cirrhosis 17.24 14.61 15.25 0.732 Diabetes Mellitus (Types 1 and 2) 20.69 11.24 13.56 0.197 Previous Myocardial Infarction 17.24 7.87 10.17 0.147 Hypertension 0 12.36 9.32 0.047 3.2 Clinical outcomes In-hospital mortality was markedly higher among ACM patients with AF (10.34% vs. 1.12%), and statistically significant both on unadjusted analysis (Odds ratio 10.15; p = 0.049) and after adjusting for covariates (OR = 20.18; 95% CI = 5.2-78.35; p < 0.001). Use of vasopressors was more than sixfold more likely among the AF cohort (OR 6.05; p = 0.049). There was no statistically significant difference in the length of stay or total hospital charges after multivariate adjustment. (Table 2 ). Notably, all admissions requiring mechanical circulatory support (n = 10) presented with AF. Table 2 CLINICAL OUTCOMES Outcome Incidence ACM WITH AF n = 145 ACM WITHOUT AF n = 445 Odds ratio or Difference p-Value PRIMARY OUTCOME In-Hospital Mortality (%) 10.34 1.12 10.15 0.049 SECONDARY OUTCOMES Mechanical Ventilation (%) 6.90 (n = 10) 2.24 (n = 10) 3.22 0.253 Length of Stay (days) 8.62 5.13 3.485867 0.050 Hospital Charges ( $ ) 159331 66705 92625.02 0.037 Vasopressor requirements (%) 6.90 (n = 10) 1.12 (n = 5) 6.518542 0.132 A TOTAL OF 10 ADMISSIONS HAD MECHANICAL CIRCULATORY SUPPORT, AND THEY ALL HAD ATRIAL FIBRILLATION Table 3 shows the unadjusted and adjusted estimates of clinical outcomes and Table 4 , the multivariate analysis of mortality risk. Table 3 UNADJUSTED AND ADJUSTED ESTIMATES OF CLINICAL OUTCOMES Outcome Incidence Unadjusted OR/ Difference Confidence Interval p-value Adjusted OR/ Difference Confidence Interval p-value PRIMARY OUTCOME In-Hospital Mortality (%) 10.15 1.01-101.83 0.049 20.18 5.20- 78.35 < 0.001 SECONDARY OUTCOMES Mechanical Ventilation (%) 3.22 0.43–23.98 0.253 2.17 0.28–16.72 0.457 Length of Stay (days) 3.49 0.0048 6.9669 0.050 2.05 -0.26–4.36 0.081 Hospital Charges ( $ ) 92625 5614- 179635 0.037 61211 -3350 - +125773 0.063 Vasopressor requirements (%) 6.52 0.57- 74.86 0.132 6.05 1.01–36.22 0.049 Table 4 MULTIVARIATE ANALYSIS OF MORTALITY RISK VARIABLE ODDS RATIO p-Value Confidence Interval Atrial Fibrillation 37.94 < 0.001 10.17–141.53 Age 1.096525 0.066 0.994–1.210 Race 4.31831 0.012 1.37 − 13.59 Female 2.09 0.573 0.16 − 27.18 Hospital Bed size 1.73 0.156 0.68 − 4.41 Charlson Comorbidity Index (Baseline Morbidity Burden) 1.18 0.653 0.57 − 2.43 ATRIAL FIBRILLATION WAS PREDICTIVE OF MORTALITY BUT NOT THE PATIENTS’ OVERALL ILLNESS/MORBIDITY BURDEN [CHARLSON COMORBIDITY INDEX WAS NOT SIGNIFICANT] 4. Discussion Our results show that the presence of atrial fibrillation (AF) is a strong predictor of in-hospital mortality among patients hospitalized with alcoholic cardiomyopathy (ACM). Even after adjusting for age, gender, race, hospital bed size, and the Elixhauser Comorbidity Index, AF was associated with an approximately 20-fold increase in the odds of in-hospital mortality (adjusted OR: 20.18; 95% CI 5.20–78.35; p < 0.001), compared to patients without AF. These findings reinforce prior observations that arrhythmias in ACM can sharply worsen clinical outcomes [ 10 ] and highlight AF as a key risk factor meriting early recognition and aggressive management in this population. From a clinical perspective, our data indicate that AF in ACM substantially increases the severity of hospitalization and the likelihood of adverse outcomes. Although patients with AF showed higher unadjusted rates of mechanical ventilation and longer hospital stays, these differences did not reach statistical significance after adjustment. Interestingly, vasopressor requirements became significant after accounting for confounders (adjusted OR: 6.05; 95% CI 1.01–36.22; p = 0.049), suggesting that hemodynamic instability may be one mechanism by which AF contributes to mortality in hospitalized ACM patients. These results extend the current body of knowledge on how AF interacts with underlying structural heart disease in patients with severe alcohol-related myocardial injury. Chronic excessive alcohol consumption can exert direct toxic effects on cardiomyocytes by disrupting calcium homeostasis, mitochondrial function, and oxidative pathways [ 2 , 11 ]. The resulting ventricular and atrial remodeling characterized by fibrosis, myocyte hypertrophy, and electrical conduction abnormalities creates a substrate highly prone to arrhythmic events like AF [ 3 , 12 ]. Our findings suggest that once AF develops, it exacerbates hemodynamic compromise and potentially accelerates the clinical course toward higher mortality. 4.1 Comparison of study results with available evidence There is a relative paucity of data on the outcomes of patients with alcoholic cardiomyopathy. To our knowledge, no study has specifically evaluated atrial-fibrillation-related differences in in-hospital mortality among these patients. This study aligns with emerging data on the poor prognosis of patients with ACM and concomitant arrhythmias. While previous investigations have often grouped multiple arrhythmias together [ 10 ], more focused studies have shown that AF specifically compounds risks in ACM [ 13 ]. Guzzo-Merello et al. demonstrated that AF independently predicted death or transplantation in ACM [ 13 ], and other studies have found similar trends for heightened mortality once AF coexists with alcohol-induced cardiac dysfunction [ 14 ]. Our results contribute a nuanced perspective by examining in-hospital mortality and resource utilization, showing the immediate clinical impact of AF in a real-world, nationally representative population. Moreover, although prior work has documented the high overall mortality in ACM that approaches 50% at five years [ 4 ], our research illuminates the short-term consequences faced by these patients during acute hospitalizations. The lack of significance for adjusted length of stay and total hospital charges suggests that, while AF patients may initially present with more severe disease requiring intensive interventions, other hospital-level factors could also modulate resource use. On the other hand, the statistically significant association between AF and vasopressor requirements reinforces the notion that these patients often need significant hemodynamic support. 4.2 Implication of study results for clinical practice & direction for future research Our findings show the critical need for systematic rhythm surveillance, prompt identification of AF, and optimized management in patients admitted with ACM. Guideline-directed heart failure therapies, including beta-blockers and, when indicated, anticoagulation for AF, could help alleviate the hemodynamic burden and potentially reduce in-hospital mortality [ 13 ]. In addition, efforts to address alcohol cessation are paramount, as ongoing alcohol consumption may perpetuate myocardial damage and atrial remodeling. Nonetheless, questions remain regarding the best management strategies in this population, especially given that ACM patients may have lower rates of guideline-directed therapies [ 4 ]. Prospective studies with accurate phenotyping of ACM patients and standardized AF management protocols would help clarify how intensifying or optimizing therapy might improve outcomes. 5. Strengths and limitations of the study The strengths of this study include a nationally representative sample and holistic risk adjustment using the Elixhauser Comorbidity Index. However, certain limitations inherent to administrative databases warrant caution. Diagnostic coding inaccuracies, potential duplication of patient encounters, and limited granularity on clinical parameters (e.g., degree of alcohol consumption or echocardiographic indices beyond the presence of cardiomyopathy) can introduce bias. Moreover, our retrospective design precludes any inference of causality between AF and higher mortality. It is possible that AF serves as a marker of more advanced disease rather than an active driver of poor outcomes. Prospective multicenter studies are needed to substantiate these findings. Such research could clarify which subgroups of ACM patients are at particularly high risk and whether early rhythm control or more aggressive heart failure therapies can mitigate mortality. 6. Conclusion In summary, AF is a powerful, independent predictor of in-hospital mortality in patients with ACM, conferring an increased risk even after adjustment for multiple confounders. Alcoholic cardiomyopathy patients with co-existing AF were also more likely to require vasopressor support, suggesting hemodynamic vulnerability. These observations reinforce the need for clinical vigilance and aggressive arrhythmia and heart failure management in hospitalized ACM patients. Future research should focus on elucidating optimal treatment algorithms and evaluating how comprehensive arrhythmia management might mitigate short-term mortality and improve long-term outcomes in this high-risk population. Abbreviations ACM : Alcoholic Cardiomyopathy AF : Atrial Fibrillation HFrEF : Heart Failure with reduced Ejection Fraction NIS : National Inpatient Sample Declarations Ethics approval and consent to participate: As this analysis was conducted on publicly available deidentifed data, it was exempted from ethics committee approval (https://hcup-us.ahrq.gov/). Consent for publication: Not applicable Clinical trial number: not applicable. Availability of data and materials: The dataset analyzed during the current study is available at the HCUP website: https://hcup-us.ahrq.gov/. Competing interests: The authors declare that they have no competing interests Funding: No funding was received for this study Code availability: Not applicable Authors' contributions: KEO worked to conceive and design the study, analyze and interpret data, draft and revise the manuscript, and approve the final manuscript. KEO and IJO conceived and designed the study, helped draft and revise the manuscript, and approved the final manuscript. OA developed the study protocol, analyzed and interpreted the data, revised the manuscript, and approved the final manuscript. OZT, PA, CAA and JN helped with the analysis and interpretation of the data, revised the manuscript for important intellectual content, and approved the final manuscript. The authors (KEO, OA, IJO, OZT, PA, CAA, ISB, OMA, AO, BAA, VOA, FR, JN) are solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of the paper and its final contents. All authors (KEO, OA, IJO, OZT, PA, CAA, ISB, OMA, AO, EBT, BAA, VOA, FR, JN) wrote and approved the first and final manuscript. References Klatsky AL. Alcohol and cardiovascular diseases: a historical overview. Ann N Y Acad Sci. 2002;957:7–15. Domínguez F, Adler E, García-Pavía P. Alcoholic cardiomyopathy: an update. Eur Heart J. 2024;45(26):2294–305. 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J Cardiovasc Transl Res. 2021;14(1):120–4. Harada M, Nattel S. Implications of Inflammation and Fibrosis in Atrial Fibrillation Pathophysiology. Cardiac Electrophysiology Clinics. 2021;13(1):25–35. Sulaiman S, Yousef N, Benjamin MM, Sundararajan S, Wingert R, Wingert M, et al. Burden of arrhythmia and electrophysiologic procedures in alcoholic cardiomyopathy hospitalizations. International Journal of Cardiology. 2020;304:61–8. Piano MR, Phillips SA. Alcoholic cardiomyopathy: Pathophysiologic insights. Cardiovasc Toxicol. 2014;14(4):291–308. Voskoboinik A, Prabhu S, Ling L han, Kalman JM, Kistler PM. Alcohol and Atrial Fibrillation: A Sobering Review. Journal of the American College of Cardiology. 2016;68(23):2567–76. Guzzo-Merello G, Segovia J, Dominguez F, Cobo-Marcos M, Gomez-Bueno M, Avellana P, et al. Natural History and Prognostic Factors in Alcoholic Cardiomyopathy. JACC: Heart Failure. 2015;3(1):78–86. Fang W, Luo R, Tang Y, Hua W, Fu M, Chen W, et al. The Prognostic Factors of Alcoholic Cardiomyopathy: A single-center cohort study. Medicine (Baltimore). 2018;97(31):e11744. Additional Declarations No competing interests reported. Supplementary Files SUPPLEMENTARYTABLEOFCODESALCOHOLICCARDIOMYOPATHY.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Sinai","correspondingAuthor":false,"prefix":"","firstName":"Francesco","middleName":"","lastName":"Rotatori","suffix":""},{"id":501248635,"identity":"81302950-34be-4038-8c0d-b938d8e523fb","order_by":13,"name":"Jay Nfonoyim","email":"","orcid":"","institution":"Richmond University Medical Center/Mount Sinai","correspondingAuthor":false,"prefix":"","firstName":"Jay","middleName":"","lastName":"Nfonoyim","suffix":""}],"badges":[],"createdAt":"2025-07-30 12:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7252791/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7252791/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92091352,"identity":"b9c6dd6d-4e84-4769-8b3f-2ffb3db7a5cb","added_by":"auto","created_at":"2025-09-24 13:39:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1083315,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7252791/v1/2a440d98-2792-48a8-b79d-9c91a41a8d8d.pdf"},{"id":89596754,"identity":"99ce6183-3793-4ce3-b26d-70ba96cf1e76","added_by":"auto","created_at":"2025-08-21 16:59:49","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":15265,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYTABLEOFCODESALCOHOLICCARDIOMYOPATHY.docx","url":"https://assets-eu.researchsquare.com/files/rs-7252791/v1/f25066100cd5823eb76240a3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Atrial fibrillation is an independent risk factor for mortality among patients hospitalized for alcoholic cardiomyopathy: a nationwide in-patient analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAlcohol cardiomyopathy (ACM) was first clinically reported in the 19th century with a prevalence in Bavarian beer drinkers, the \u0026ldquo;M\u0026uuml;nchener bierherz,\u0026rdquo; also with an epidemic of heart muscle failures associated with arsenic-contaminated beer in England [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. ACM primarily affects individuals with prolonged alcohol use disorder. It accounts for approximately 20% of all dilated cardiomyopathy cases in certain places. ACM results from alcohol toxicity, with the onset typically occurring after a decade or more of heavy drinking, usually 80\u0026ndash;100 g/day or more of alcohol. The effects of this toxicity on myocardial cells lead to cellular apoptosis, oxidative stress, and mitochondrial dysfunction, which underlie the resultant cardiomyopathy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These structural and functional defects manifest clinically with symptoms of heart failure with reduced ejection fraction (HFrEF), marked by left ventricular dilation and systolic dysfunction, often accompanied by arrhythmias such as atrial fibrillation (AF) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Patients with ACM tend to have a 5-year mortality rate of 49%, which is significantly higher compared to the other types of dilated cardiomyopathy. The mortality rate associated with ACM is multifaceted, which could be progressive heart failure, comorbidities, slow medical therapy, and arrhythmias such as AF. These findings encourage early detection and management of ACM patients for a better survival rate [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAtrial fibrillation increases the mortality rates of patients with ACM by almost 10 times more than ACM without Atrial fibrillation. Acetaldehyde, a byproduct of ethanol metabolism, causes the production of collagen, which increases the fibrosis of the myocardium and disrupts the electrical stability of the atrium; continuous occurrence leads to prolonged repolarization and high affinity for atrial fibrillation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Reduced arterial functions affect ventricular filling, increasing diastolic dysfunction, which complicates cardiac output by worsening systolic function, leading to quicker heart failure. Heart failure is a common complication of AF with increased mortality risk [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Analyzing atrial biopsy confirmed fibrosis, intercellular space expansion, myofibrillar loss, and decreased cardiomyocyte density facilitated a reduced global left atrial voltage, a key indication for structural remodeling [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAssessing the clinical outcome of the study shows that atrial fibrillation coexisting with ACM has in-hospital mortality rates higher at 10.34%, compared to 1.12% in ACM patients without AF. This could directly influence the complexities of more cardiac failures, neurological complications and thromboembolic risk, most commonly ischemic stroke - where irregular rhythm causes blood pooling or circulatory stagnation and thrombus formation, especially in the left atrial appendage. This mechanism underscores the possibility of ischemic stroke and a decline in neurological functions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The frequency of occurrence of these complications has been reported to be age and gender-related, occurring more among older patients and male patients even after a clinical intervention with an assisted device [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The decline in functional capacity affects the overall functionality of the body. It worsens atrial function and reduces exercise tolerance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThis study highlights the gap in understanding the effects of atrial fibrillation on in-hospital patients with Alcoholic cardiomyopathy, two conditions that affect cardiac malfunctioning. Although both ACM and atrial fibrillation have well-documented mortality risks, the role of AF in adding an extra complication has not yet been fully studied. This research focuses on how AF is a major determining factor for in-hospital mortality risk for patients with ACM, emphasizing its role as an independent predictor. This study shows the relevance of timely and localized approaches for improving clinical outcomes and proactive management. It also heightens clinical awareness for patients with ACM and atrial fibrillation, with more indication for future guidelines and healthcare policies.\u003c/p\u003e\u003cp\u003eThis study aims to evaluate if atrial fibrillation is an independent predictor of mortality risk in hospitalized patients with alcohol cardiomyopathy by analyzing data from a nationwide inpatient study and controlling for primary characteristics and comorbidities.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data source\u003c/h2\u003e\u003cp\u003eFor this study, data were sourced from the 2021 National Inpatient Sample (NIS) database, which is managed by the Agency for Healthcare Research and Quality (AHRQ) under the Healthcare Cost and Utilization Project (HCUP). The NIS serves as a comprehensive repository of patient discharge information from non-federal, short-term acute care hospitals across the United States. It is constructed using a stratified probability sampling design, where stratification considers various hospital attributes such as geographic region, urban versus rural location, hospital bed capacity (categorized as small, medium, or large), ownership type (government-owned or private), and teaching status. Within each defined stratum, 20% of hospitals are randomly selected, and the collected discharge data are weighted to ensure they accurately represent the national landscape. Since the NIS dataset is publicly available and fully de-identified, this research did not require ethical approval from an institutional review board or the acquisition of informed consent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study design and population\u003c/h2\u003e\u003cp\u003eThis study is a retrospective cohort study of inpatient admissions for Alcoholic cardiomyopathy, comparing outcomes between those with atrial fibrillation and those without. The inclusion criteria were patients 18 years of age and older with a principal Alcoholic cardiomyopathy. A principal diagnosis is defined as the diagnosis on discharge or after hospitalization outcome after all insights from clinical, laboratory, imaging, and other evaluations are available.\u003c/p\u003e\u003cp\u003eDiagnoses were identified using the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes and included in the study group. We used the ICD10-CM code \u0026ldquo;I42.6\u0026rdquo; to identify 590 patients with alcoholic cardiomyopathy as their principal diagnosis. We subdivided the study population based on the presence or absence of a secondary diagnosis of Atrial Fibrillation. We used the ICD10-CM codes \"I48.0\", \"I48.1\", \"I48.2\", \"I48.91\", \"I48.3\", \"I48.4\", \"I48\", \"I48.11\", \"I48.19\", \"I48.20\", \"I48.21\", \"I48.9\" and \"I48.92\", to identify those with a secondary diagnosis of atrial fibrillation.\u003c/p\u003e\u003cp\u003eThe covariates were identified using the appropriate codes. The supplementary table provides a full list of ICD10-CM codes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Outcomes\u003c/h2\u003e\u003cp\u003eOutcomes were compared between the cohorts ACM with AF versus ACM without AF. The primary outcome was in-hospital mortality (death during the hospitalization encounter). Secondary outcomes were invasive mechanical ventilation, vasopressor requirements, length of hospital stay, and total hospital charges.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\u003cp\u003eBaseline characteristics of the study population were assessed by calculating means for continuous variables and proportions for categorical variables, including the prevalence of comorbidities. Given the sufficient sample size in this research, categorical proportions were evaluated using Pearson\u0026rsquo;s chi-square test, and continuous variables were compared utilizing Student's t-test based on the assumptions of the Central Limit Theorem. Univariate logistic and linear regression analyses were used for hypothesis testing, and multivariate regression analyses were used to adjust for confounders. The multivariate logistic regression model included age, gender, race, the Elixhauser comorbidity index, and the hospital bed size. The Elixhauser Comorbidity Index is a system that classifies a wide range of patient comorbidities using ICD diagnosis codes. It is extensively utilized to predict in-hospital mortality by accounting for multiple chronic conditions. By incorporating these diverse comorbid factors, the index enhances the accuracy of mortality risk assessments in clinical and administrative datasets.\u003c/p\u003e\u003cp\u003eAll statistical analyses used Stata\u0026reg; version 18 (StataCorp LP, College Station, TX). To account for the NIS's stratified sampling design, survey (svy) commands were employed. A two-tailed P value of 0.05 was established as the threshold for statistical significance in all tests.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Population characteristics\u003c/h2\u003e\u003cp\u003eA total of 590 hospital admissions for alcoholic cardiomyopathy (ACM) were identified, comprising 145 patients (24.6%) with concurrent atrial fibrillation (AF)- AF group- and 445 patients (75.4%) without AF- non-AF group. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, there were no statistically significant differences in baseline demographic variables. The mean age in years of patients was 51 years. There was no significant difference in age (53 vs. 50 years; p\u0026thinsp;=\u0026thinsp;0.32) or gender (p\u0026thinsp;=\u0026thinsp;0.44) between the subgroups. Similarly, there was no statistically significant difference in hospital bed size (p\u0026thinsp;=\u0026thinsp;0.160), race (p\u0026thinsp;=\u0026thinsp;0.287), or median household income for the patient\u0026rsquo;s ZIP code which represented their socioeconomic status (p\u0026thinsp;=\u0026thinsp;0.33). However, the Elixhauser comorbidity index stands out, indicating a statistically significant difference between the AF and non-AF groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Although none of the AF patients presented hypertension, hypertension also stands out as a significant factor for mortality with a statistical significance of (p\u0026thinsp;=\u0026thinsp;0.047). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCHARACTERISTICS OF THE STUDY POPULATION\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVARIABLE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACM WITH AF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACM WITHOUT AF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTOTAL ACM ADMISSIONS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge mean +-SD (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53.31 +- 13.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.53 +-12.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51.21+- 13.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e 0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.79%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.22%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.64%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86.21%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.78%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.36%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHospital Bed size\u003c/b\u003e 0.160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.61%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.24%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.83%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLarge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.62%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.62%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRace\u003c/b\u003e 0.287\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaucasian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78.57%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57.47%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.87368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack/ African American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.29%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.83835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHispanic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.57%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.49%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.77446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.29413\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNative American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,45%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.50222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.30%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.71716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedian Household Income for Patient\u0026rsquo;s ZIP code (Socioeconomic Status)\u003c/b\u003e 0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuartile 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuartile 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.28%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.54%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuartile 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.26%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.44%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuartile 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.77%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.05%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eElixhauser Comorbidity Index (means +-SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.31+- 2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.26 +- 1.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.76 +- 2.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCOMORBIDITIES\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver Cirrhosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.732\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes Mellitus (Types 1 and 2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.197\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrevious Myocardial Infarction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.147\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Clinical outcomes\u003c/h2\u003e\u003cp\u003eIn-hospital mortality was markedly higher among ACM patients with AF (10.34% vs. 1.12%), and statistically significant both on unadjusted analysis (Odds ratio 10.15; p\u0026thinsp;=\u0026thinsp;0.049) and after adjusting for covariates (OR\u0026thinsp;=\u0026thinsp;20.18; 95% CI\u0026thinsp;=\u0026thinsp;5.2-78.35; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Use of vasopressors was more than sixfold more likely among the AF cohort (OR 6.05; p\u0026thinsp;=\u0026thinsp;0.049).\u003c/p\u003e\u003cp\u003eThere was no statistically significant difference in the length of stay or total hospital charges after multivariate adjustment. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Notably, all admissions requiring mechanical circulatory support (n\u0026thinsp;=\u0026thinsp;10) presented with AF.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCLINICAL OUTCOMES\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome Incidence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACM WITH AF n\u0026thinsp;=\u0026thinsp;145\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACM WITHOUT AF n\u0026thinsp;=\u0026thinsp;445\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOdds ratio or Difference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003ePRIMARY OUTCOME\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-Hospital Mortality (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSECONDARY OUTCOMES\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMechanical Ventilation (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.90 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.24 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.253\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength of Stay (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.485867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospital Charges (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e159331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92625.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVasopressor requirements (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.90 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12 (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.518542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eA TOTAL OF 10 ADMISSIONS HAD MECHANICAL CIRCULATORY SUPPORT, AND THEY ALL HAD ATRIAL FIBRILLATION\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the unadjusted and adjusted estimates of clinical outcomes and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the multivariate analysis of mortality risk.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUNADJUSTED AND ADJUSTED ESTIMATES OF CLINICAL OUTCOMES\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome Incidence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eUnadjusted OR/ Difference\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eConfidence Interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eAdjusted OR/ Difference\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eConfidence Interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePRIMARY OUTCOME\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-Hospital Mortality (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01-101.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.20- 78.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSECONDARY OUTCOMES\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMechanical Ventilation (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.43\u0026ndash;23.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.28\u0026ndash;16.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength of Stay (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0048 6.9669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.26\u0026ndash;4.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.081\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospital Charges (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92625\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5614- 179635\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3350 - +125773\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVasopressor requirements (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.57- 74.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.01\u0026ndash;36.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMULTIVARIATE ANALYSIS OF MORTALITY RISK\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVARIABLE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eODDS RATIO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAtrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.17\u0026ndash;141.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.096525\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.994\u0026ndash;1.210\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.31831\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.37 \u0026minus;\u0026thinsp;13.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.16 \u0026minus;\u0026thinsp;27.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHospital Bed size\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.68 \u0026minus;\u0026thinsp;4.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCharlson Comorbidity Index (Baseline Morbidity Burden)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.57 \u0026minus;\u0026thinsp;2.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eATRIAL FIBRILLATION WAS PREDICTIVE OF MORTALITY BUT NOT THE PATIENTS\u0026rsquo; OVERALL ILLNESS/MORBIDITY BURDEN [CHARLSON COMORBIDITY INDEX WAS NOT SIGNIFICANT]\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur results show that the presence of atrial fibrillation (AF) is a strong predictor of in-hospital mortality among patients hospitalized with alcoholic cardiomyopathy (ACM). Even after adjusting for age, gender, race, hospital bed size, and the Elixhauser Comorbidity Index, AF was associated with an approximately 20-fold increase in the odds of in-hospital mortality (adjusted OR: 20.18; 95% CI 5.20\u0026ndash;78.35; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared to patients without AF. These findings reinforce prior observations that arrhythmias in ACM can sharply worsen clinical outcomes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and highlight AF as a key risk factor meriting early recognition and aggressive management in this population.\u003c/p\u003e\u003cp\u003eFrom a clinical perspective, our data indicate that AF in ACM substantially increases the severity of hospitalization and the likelihood of adverse outcomes. Although patients with AF showed higher unadjusted rates of mechanical ventilation and longer hospital stays, these differences did not reach statistical significance after adjustment. Interestingly, vasopressor requirements became significant after accounting for confounders (adjusted OR: 6.05; 95% CI 1.01\u0026ndash;36.22; p\u0026thinsp;=\u0026thinsp;0.049), suggesting that hemodynamic instability may be one mechanism by which AF contributes to mortality in hospitalized ACM patients.\u003c/p\u003e\u003cp\u003eThese results extend the current body of knowledge on how AF interacts with underlying structural heart disease in patients with severe alcohol-related myocardial injury. Chronic excessive alcohol consumption can exert direct toxic effects on cardiomyocytes by disrupting calcium homeostasis, mitochondrial function, and oxidative pathways [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The resulting ventricular and atrial remodeling characterized by fibrosis, myocyte hypertrophy, and electrical conduction abnormalities creates a substrate highly prone to arrhythmic events like AF [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Our findings suggest that once AF develops, it exacerbates hemodynamic compromise and potentially accelerates the clinical course toward higher mortality.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Comparison of study results with available evidence\u003c/h2\u003e\u003cp\u003eThere is a relative paucity of data on the outcomes of patients with alcoholic cardiomyopathy. To our knowledge, no study has specifically evaluated atrial-fibrillation-related differences in in-hospital mortality among these patients. This study aligns with emerging data on the poor prognosis of patients with ACM and concomitant arrhythmias. While previous investigations have often grouped multiple arrhythmias together [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], more focused studies have shown that AF specifically compounds risks in ACM [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Guzzo-Merello et al. demonstrated that AF independently predicted death or transplantation in ACM [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and other studies have found similar trends for heightened mortality once AF coexists with alcohol-induced cardiac dysfunction [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our results contribute a nuanced perspective by examining in-hospital mortality and resource utilization, showing the immediate clinical impact of AF in a real-world, nationally representative population.\u003c/p\u003e\u003cp\u003eMoreover, although prior work has documented the high overall mortality in ACM that approaches 50% at five years [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], our research illuminates the short-term consequences faced by these patients during acute hospitalizations. The lack of significance for adjusted length of stay and total hospital charges suggests that, while AF patients may initially present with more severe disease requiring intensive interventions, other hospital-level factors could also modulate resource use. On the other hand, the statistically significant association between AF and vasopressor requirements reinforces the notion that these patients often need significant hemodynamic support.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Implication of study results for clinical practice \u0026amp; direction for future research\u003c/h2\u003e\u003cp\u003eOur findings show the critical need for systematic rhythm surveillance, prompt identification of AF, and optimized management in patients admitted with ACM. Guideline-directed heart failure therapies, including beta-blockers and, when indicated, anticoagulation for AF, could help alleviate the hemodynamic burden and potentially reduce in-hospital mortality [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In addition, efforts to address alcohol cessation are paramount, as ongoing alcohol consumption may perpetuate myocardial damage and atrial remodeling.\u003c/p\u003e\u003cp\u003eNonetheless, questions remain regarding the best management strategies in this population, especially given that ACM patients may have lower rates of guideline-directed therapies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Prospective studies with accurate phenotyping of ACM patients and standardized AF management protocols would help clarify how intensifying or optimizing therapy might improve outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Strengths and limitations of the study","content":"\u003cp\u003eThe strengths of this study include a nationally representative sample and holistic risk adjustment using the Elixhauser Comorbidity Index. However, certain limitations inherent to administrative databases warrant caution. Diagnostic coding inaccuracies, potential duplication of patient encounters, and limited granularity on clinical parameters (e.g., degree of alcohol consumption or echocardiographic indices beyond the presence of cardiomyopathy) can introduce bias. Moreover, our retrospective design precludes any inference of causality between AF and higher mortality. It is possible that AF serves as a marker of more advanced disease rather than an active driver of poor outcomes. Prospective multicenter studies are needed to substantiate these findings. Such research could clarify which subgroups of ACM patients are at particularly high risk and whether early rhythm control or more aggressive heart failure therapies can mitigate mortality.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn summary, AF is a powerful, independent predictor of in-hospital mortality in patients with ACM, conferring an increased risk even after adjustment for multiple confounders. Alcoholic cardiomyopathy patients with co-existing AF were also more likely to require vasopressor support, suggesting hemodynamic vulnerability. These observations reinforce the need for clinical vigilance and aggressive arrhythmia and heart failure management in hospitalized ACM patients.\u003c/p\u003e\u003cp\u003eFuture research should focus on elucidating optimal treatment algorithms and evaluating how comprehensive arrhythmia management might mitigate short-term mortality and improve long-term outcomes in this high-risk population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eACM\u003c/strong\u003e: Alcoholic Cardiomyopathy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAF\u003c/strong\u003e: Atrial Fibrillation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHFrEF\u003c/strong\u003e: Heart Failure with reduced Ejection Fraction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNIS\u003c/strong\u003e: National Inpatient Sample\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate: \u003c/strong\u003eAs this analysis was conducted on publicly available deidentifed data, it was exempted from ethics committee approval (https://hcup-us.ahrq.gov/).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication: \u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number: \u003c/strong\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The dataset analyzed during the current study is available at the HCUP website: https://hcup-us.ahrq.gov/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests: \u003c/strong\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No funding was received for this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability: \u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e KEO worked to conceive and design the study, analyze and interpret data, draft and revise the manuscript, and approve the final manuscript. KEO and IJO conceived and designed the study, helped draft and revise the manuscript, and approved the final manuscript. OA developed the study protocol, analyzed and interpreted the data, revised the manuscript, and approved the final manuscript. OZT, PA, CAA and JN helped with the analysis and interpretation of the data, revised the manuscript for important intellectual content, and approved the final manuscript. The authors (KEO, OA, IJO, OZT, PA, CAA, ISB, OMA, AO, BAA, VOA, FR, JN) are solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of the paper and its final contents. All authors (KEO, OA, IJO, OZT, PA, CAA, ISB, OMA, AO, EBT, BAA, VOA, FR, JN) wrote and approved the first and final manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKlatsky AL. Alcohol and cardiovascular diseases: a historical overview. Ann N Y Acad Sci. 2002;957:7\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDom\u0026iacute;nguez F, Adler E, Garc\u0026iacute;a-Pav\u0026iacute;a P. Alcoholic cardiomyopathy: an update. Eur Heart J. 2024;45(26):2294\u0026ndash;305.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFern\u0026aacute;ndez-Sol\u0026agrave; J, Estruch R. Journal of Alcoholism \u0026amp; Drug Dependence. 2017;5(6):1000293. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4172/2329-6488.1000293\u003c/span\u003e\u003cspan address=\"10.4172/2329-6488.1000293\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFernandes A, Manivannan A, Schou M, Fosb\u0026oslash;l E, K\u0026oslash;ber L, Gustafsson F, et al. Clinical Trajectories and Long-Term Outcomes of Alcoholic Versus Other Forms of Dilated Cardiomyopathy. Heart, Lung and Circulation. 2024;33(3):368\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePranata R, Deka H, Siswanto BB. Cardiovascular and Neurological Complications Associated with Atrial Fibrillation. IJC. 2017;164\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYamaguchi T. Atrial structural remodeling and atrial fibrillation substrate: A histopathological perspective. J Cardiol. 2024;S0914-5087(24)00096\u0026thinsp;\u0026ndash;\u0026thinsp;0.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcIntyre WF, Healey J. Stroke Prevention for Patients with Atrial Fibrillation: Beyond the Guidelines. J Atr Fibrillation. 2017;9(6):1475.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlumer V, Ortiz Bezara M, Kittipibul V, Greene SJ, Fudim M, Hernandez GA, et al. Impact of Atrial Fibrillation on In-Hospital Mortality and Thromboembolic Complications after Left Ventricular Assist Device Implantation. J Cardiovasc Transl Res. 2021;14(1):120\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarada M, Nattel S. Implications of Inflammation and Fibrosis in Atrial Fibrillation Pathophysiology. Cardiac Electrophysiology Clinics. 2021;13(1):25\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSulaiman S, Yousef N, Benjamin MM, Sundararajan S, Wingert R, Wingert M, et al. Burden of arrhythmia and electrophysiologic procedures in alcoholic cardiomyopathy hospitalizations. International Journal of Cardiology. 2020;304:61\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePiano MR, Phillips SA. Alcoholic cardiomyopathy: Pathophysiologic insights. Cardiovasc Toxicol. 2014;14(4):291\u0026ndash;308.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVoskoboinik A, Prabhu S, Ling L han, Kalman JM, Kistler PM. Alcohol and Atrial Fibrillation: A Sobering Review. Journal of the American College of Cardiology. 2016;68(23):2567\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuzzo-Merello G, Segovia J, Dominguez F, Cobo-Marcos M, Gomez-Bueno M, Avellana P, et al. Natural History and Prognostic Factors in Alcoholic Cardiomyopathy. JACC: Heart Failure. 2015;3(1):78\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFang W, Luo R, Tang Y, Hua W, Fu M, Chen W, et al. The Prognostic Factors of Alcoholic Cardiomyopathy: A single-center cohort study. Medicine (Baltimore). 2018;97(31):e11744.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alcoholic Cardiomyopathy, Atrial Fibrillation, National Inpatient Sample, In-hospital mortality, Arrhythmia, Dilated Cardiomyopathy","lastPublishedDoi":"10.21203/rs.3.rs-7252791/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7252791/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlcoholic cardiomyopathy (ACM) is dilated cardiomyopathy resulting from chronic alcohol consumption and is associated with significant mortality. Atrial fibrillation (AF) frequently coexists with ACM, but its specific impact on patients hospitalized with ACM remains unclear. We aimed to evaluate the association of co-existing AF with short-term clinical outcomes in ACM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective cohort study was performed using the United States National Inpatient Sample database for 2021. Inpatient mortality, total hospital charges, length of hospital stay, mechanical ventilation rates, and vasopressor use were compared between patients aged 18 or older, with and without atrial fibrillation. Univariate logistic and linear regression analyses were used for hypothesis testing; multivariate regression analyses were then used to adjust for confounders. Student T-test and Pearson’s chi-square test were used to compare population demographic features. Analyses were performed using STATA/BE 18.0. Significance was set at 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 590 ACM admissions identified, 145(25%) had atrial fibrillation. There was no significant difference in age (53 vs. 50 years; p=0.32) or gender (p=0.44) between the subgroups. The in-hospital mortality rate was 10.3% and 1.1% among those with and without atrial fibrillation, respectively (Odds ratio, OR=10.2; p=0.049).\u003c/p\u003e\n\u003cp\u003eWhen adjusted for age, race, gender, Charlson comorbidity index (baseline functional status), and size of healthcare facility in a multivariate logistic regression analysis, atrial fibrillation remained significantly associated with increased mortality risk (OR= 20.2; p\u0026lt;0.001) and became significantly associated with increased vasopressor support (OR=6.05; p=0.049) among ACM patients.\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in total hospital charges (p=0.063) or length of hospital stay (p=0.081) on adjusted analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCoexisting atrial fibrillation in patients hospitalized with alcoholic cardiomyopathy independently correlates with markedly higher in-hospital mortality and an increased need for vasopressor support. These patients require close monitoring and proactive management of atrial fibrillation. Further research is needed to elucidate this topic.\u003c/p\u003e","manuscriptTitle":"Atrial fibrillation is an independent risk factor for mortality among patients hospitalized for alcoholic cardiomyopathy: a nationwide in-patient analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 16:51:45","doi":"10.21203/rs.3.rs-7252791/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bbc88dde-426e-4c4c-9f2b-0c30aa4c6061","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-24T13:38:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-21 16:51:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7252791","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7252791","identity":"rs-7252791","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}