Hypoalbuminemia as a Prognostic Marker in Alcoholic Cardiomyopathy: A TriNetX-Based Retrospective Analysis

Hypoalbuminemia as a Prognostic Marker in Alcoholic Cardiomyopathy: A TriNetX-Based Retrospective 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 Hypoalbuminemia as a Prognostic Marker in Alcoholic Cardiomyopathy: A TriNetX-Based Retrospective Analysis EKOW ESSIEN, Abena Agyekum, Karldon Nwaezeapu, Abraham Carboo, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6745450/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 Background Alcoholic cardiomyopathy (ACM) is a significant cause of heart failure with substantial morbidity and mortality. Hypoalbuminemia, a marker of malnutrition and systemic inflammation, may serve as a prognostic indicator in ACM patients. This study aimed to evaluate the prognostic significance of hypoalbuminemia in patients with alcoholic cardiomyopathy. Methods We conducted a retrospective cohort study using the TriNetX Research Network, analyzing data from 129 healthcare organizations. Adult patients (18–90 years) with alcoholic cardiomyopathy were stratified into two cohorts: hypoalbuminemia (albumin ≤ 3.40 g/dL; n = 5,754) and normal albumin (albumin ≥ 3.50 g/dL; n = 9,620). After propensity score matching, 5,241 patients remained in each cohort. Primary outcome was all-cause mortality. Secondary outcomes included cardiovascular complications, acute kidney injury, and hospital utilization over a 5-year follow-up period. Results Patients with hypoalbuminemia demonstrated significantly higher all-cause mortality compared to those with normal albumin levels (36.2% vs 15.1%; HR 3.341, 95% CI 3.072–3.633; p < 0.001). Hypoalbuminemia was associated with increased risks of cardiogenic shock (7.3% vs 4.3%; HR 2.241, 95% CI 1.883–2.667; p < 0.001), acute kidney injury (29.0% vs 18.8%; HR 2.157, 95% CI 1.943–2.395; p < 0.001), ventricular tachycardia (9.6% vs 8.7%; HR 1.510, 95% CI 1.313–1.738; p < 0.001), and pulmonary embolism (3.7% vs 3.0%; HR 1.692, 95% CI 1.362–2.103; p < 0.001). Paradoxically, patients with hypoalbuminemia had lower rates of pacemaker implantation (5.5% vs 8.3%; HR 0.847, 95% CI 0.726–0.988; p = 0.035). Conclusion Hypoalbuminemia serves as a powerful prognostic marker in alcoholic cardiomyopathy, associated with significantly increased mortality and cardiovascular complications. These findings suggest that albumin levels should be routinely monitored and nutritional interventions considered in ACM management to potentially improve outcomes. alcoholic cardiomyopathy hypoalbuminemia prognosis mortality heart failure Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Alcoholic cardiomyopathy (ACM) represents a distinct form of dilated cardiomyopathy caused by chronic alcohol consumption, accounting for approximately 21–36% of all dilated cardiomyopathy cases [ 1 , 2 ]. The condition is characterized by left ventricular dilatation, reduced ejection fraction, and progressive heart failure symptoms, with significant morbidity and mortality implications [ 3 ]. Despite advances in heart failure management, ACM continues to carry a poor prognosis, particularly in advanced stages. The pathophysiology of ACM involves multiple mechanisms including direct cardiotoxic effects of alcohol and its metabolites, oxidative stress, mitochondrial dysfunction, and protein synthesis impairment [ 4 , 5 ]. Chronic alcohol consumption also leads to malnutrition, systemic inflammation, and metabolic derangements that may compound cardiac dysfunction [ 6 ]. Among these, hypoalbuminemia emerges as a potential biomarker reflecting both nutritional status and disease severity. Albumin, synthesized exclusively by the liver, serves multiple physiological functions including oncotic pressure maintenance, antioxidant activity, and transport of various substances [ 7 ]. Hypoalbuminemia in cardiovascular disease has been associated with worse outcomes across various conditions, including heart failure, acute coronary syndromes, and cardiac surgery [ 8 , 9 ]. The mechanisms underlying this association include increased inflammatory burden, impaired drug distribution, compromised wound healing, and increased susceptibility to infections [ 10 ]. In the context of alcoholic cardiomyopathy, hypoalbuminemia may result from multiple factors including poor nutritional intake, malabsorption, hepatic dysfunction, chronic inflammation, and increased protein losses [ 11 ]. The combination of cardiac dysfunction and hypoalbuminemia may create a particularly high-risk phenotype, yet comprehensive data on this association remain limited. Previous studies examining hypoalbuminemia in heart failure have predominantly focused on ischemic or idiopathic dilated cardiomyopathy, with limited specific data on alcoholic etiology [ 12 , 13 ]. Given the unique pathophysiology and patient characteristics associated with ACM, dedicated investigation of hypoalbuminemia's prognostic role in this population is essential. Therefore, we conducted this large-scale retrospective analysis using the TriNetX Research Network to comprehensively evaluate the prognostic significance of hypoalbuminemia in patients with alcoholic cardiomyopathy. We hypothesized that hypoalbuminemia would be associated with increased mortality and cardiovascular complications in ACM patients. 2. Methods 2.1 Data Source This study utilized the TriNetX Research Network, a global federated health research platform providing access to electronic medical records across 129 healthcare organizations. The platform enables real-time analysis of de-identified patient data while maintaining privacy and security standards. Data encompass diagnoses, procedures, medications, laboratory values, and demographic information from diverse healthcare settings across multiple geographic regions. 2.2 Study Population We identified adult patients aged 18–90 years with alcoholic cardiomyopathy (ICD-10 code I42.6). Patients were stratified into two cohorts based on serum albumin levels: (1) hypoalbuminemia group with albumin ≤ 3.40 g/dL and (2) normal albumin group with albumin ≥ 3.50 g/dL, using the most recent albumin measurement. The albumin cutoff values were chosen based on established clinical thresholds for hypoalbuminemia [ 14 ]. The index event was defined as the concurrent presence of alcoholic cardiomyopathy diagnosis and the qualifying albumin level. Patients were followed for up to 5 years (1,825 days) after the index event, with outcomes analyzed starting 1 day after the index event to exclude prevalent cases. 2.3 Outcomes The primary outcome was all-cause mortality during the follow-up period. Secondary outcomes included cardiogenic shock, heart failure progression, ventricular tachycardia, atrial fibrillation, acute kidney injury (AKI), pacemaker and implantable cardioverter-defibrillator (ICD) implantation, cerebrovascular disease, pulmonary embolism, chronic kidney disease (CKD), and pulmonary hypertension. Hospital admissions and ICU admissions were also evaluated as measures of healthcare utilization. For each outcome, patients with the specific condition prior to the index event were excluded from the respective analysis to ensure evaluation of incident events only. 2.4 Propensity Score Matching To minimize confounding and create comparable cohorts, propensity score matching was performed using baseline demographics and comorbidities. Matching variables included age, sex, race, ethnicity, and key comorbidities such as acute kidney failure, chronic kidney disease, metabolic disorders, and hypertensive diseases. Patients were matched 1:1 using nearest-neighbor matching without replacement. 2.5 Statistical Analysis Baseline characteristics were compared between matched groups using standardized mean differences, with values < 0.1 indicating good balance. For outcomes analysis, we employed three approaches: (1) risk analysis calculating event rates, risk differences, risk ratios, and odds ratios with 95% confidence intervals; (2) Kaplan-Meier survival analysis with log-rank tests and Cox proportional hazards models; and (3) number of instances analysis for recurrent events. Statistical significance was set at p < 0.05 for all analyses. All statistical procedures were conducted using the TriNetX platform's built-in analytics tools. 2.6 Ethical Considerations This study used de-identified data from the TriNetX Research Network and was exempt from Institutional Review Board approval according to 45 CFR 46.104(d)(4). The study was conducted in accordance with the Declaration of Helsinki and STROBE guidelines for observational studies. 3. Results 3.1 Baseline Characteristics Before propensity score matching, we identified 5,754 patients with alcoholic cardiomyopathy and hypoalbuminemia and 9,620 patients with alcoholic cardiomyopathy and normal albumin levels. After propensity matching, 5,241 patients remained in each cohort, with excellent balance achieved across demographic and clinical characteristics (Table 1 ). The matched cohorts showed no significant differences in age (mean 58.6 ± 12.8 vs 58.5 ± 12.1 years), sex distribution (male 82.7% vs 83.3%), or racial composition. Key comorbidities were also well-balanced, including acute kidney failure and chronic kidney disease (37.0% vs 37.4%), metabolic disorders (68.6% vs 69.3%), and hypertensive diseases (66.6% vs 67.6%). Table 1 Baseline Characteristics of Propensity-Matched Cohorts Characteristic Hypoalbuminemia (N = 5,241) Normal Albumin (N = 5,241) P-Value Std Diff. Demographics Age at Index (years) 58.6 ± 12.8 58.5 ± 12.1 0.723 0.007 Male sex 4,332 (82.7%) 4,367 (83.3%) 0.363 0.018 Female sex 767 (14.6%) 751 (14.3%) 0.657 0.009 Race White 3,028 (57.8%) 3,102 (59.2%) 0.142 0.029 Black or African American 1,225 (23.4%) 1,202 (22.9%) 0.594 0.010 American Indian/Alaska Native 76 (1.5%) 79 (1.5%) 0.808 0.005 Asian 98 (1.9%) 94 (1.8%) 0.771 0.006 Ethnicity Hispanic or Latino 355 (6.8%) 351 (6.7%) 0.876 0.003 Not Hispanic or Latino 3,935 (75.1%) 3,989 (76.1%) 0.219 0.024 Comorbidities Acute kidney failure and CKD 1,941 (37.0%) 1,960 (37.4%) 0.701 0.007 Metabolic disorders 3,594 (68.6%) 3,634 (69.3%) 0.398 0.016 Hypertensive diseases 3,490 (66.6%) 3,543 (67.6%) 0.271 0.022 3.2 Primary Outcome: All-Cause Mortality All-cause mortality occurred in 1,858 patients (36.2%) in the hypoalbuminemia group compared to 785 patients (15.1%) in the normal albumin group (Risk Ratio 2.397, 95% CI 2.226–2.581; p < 0.001) (Table 2 ). Kaplan-Meier survival analysis demonstrated significantly lower survival probability in the hypoalbuminemia group (46.48% vs 77.69% at 5 years; HR 3.341, 95% CI 3.072–3.633; p < 0.001). Median survival was 1,587 days in the hypoalbuminemia group, while median survival was not reached in the normal albumin group. 3.3 Secondary Outcomes Patients with hypoalbuminemia experienced significantly higher rates of major cardiovascular complications. Cardiogenic shock occurred in 331 patients (7.3%) in the hypoalbuminemia group versus 208 patients (4.3%) in the normal albumin group (HR 2.241, 95% CI 1.883–2.667; p < 0.001). Acute kidney injury was substantially more frequent in the hypoalbuminemia group, affecting 824 patients (29.0%) compared to 621 patients (18.8%) in the normal albumin group (HR 2.157, 95% CI 1.943–2.395; p < 0.001). Ventricular tachycardia occurred in 407 patients (9.6%) in the hypoalbuminemia group versus 382 patients (8.7%) in the normal albumin group (HR 1.510, 95% CI 1.313–1.738; p < 0.001). Similarly, pulmonary embolism was more common in the hypoalbuminemia group (3.7% vs 3.0%; HR 1.692, 95% CI 1.362–2.103; p < 0.001). Chronic kidney disease developed in 601 patients (15.7%) in the hypoalbuminemia group compared to 557 patients (14.1%) in the normal albumin group (HR 1.570, 95% CI 1.399–1.763; p < 0.001). Pulmonary hypertension was also more frequent in the hypoalbuminemia group (9.7% vs 8.3%; HR 1.589, 95% CI 1.378–1.832; p < 0.001). Interestingly, pacemaker and ICD implantation was less common in the hypoalbuminemia group (5.5% vs 8.3%; HR 0.847, 95% CI 0.726–0.988; p = 0.035), possibly reflecting competing mortality risk or reduced procedural candidacy. No significant differences were observed in heart failure progression, atrial fibrillation, or cerebrovascular disease between the groups. Table 2 Risk Ratios and Hazard Ratios of Primary and Secondary Outcomes Outcome Hypoalbuminemia (N varies) Normal Albumin (N varies) Risk Ratio (95% CI) Hazard Ratio (95% CI) P-Value All-cause mortality 1,858/5,138 (36.2%) 785/5,204 (15.1%) 2.397 (2.226–2.581) 3.341 (3.072–3.633) < 0.001 Cardiogenic shock 331/4,564 (7.3%) 208/4,784 (4.3%) 1.668 (1.409–1.974) 2.241 (1.883–2.667) < 0.001 Acute kidney injury 824/2,840 (29.0%) 621/3,306 (18.8%) 1.545 (1.410–1.692) 2.157 (1.943–2.395) < 0.001 Ventricular tachycardia 407/4,252 (9.6%) 382/4,369 (8.7%) 1.095 (0.958–1.251) 1.510 (1.313–1.738) < 0.001 Pulmonary embolism 182/4,893 (3.7%) 149/4,980 (3.0%) 1.243 (1.005–1.538) 1.692 (1.362–2.103) < 0.001 Chronic kidney disease 601/3,834 (15.7%) 557/3,961 (14.1%) 1.115 (1.002–1.240) 1.570 (1.399–1.763) < 0.001 Pulmonary hypertension 407/4,202 (9.7%) 360/4,356 (8.3%) 1.172 (1.024–1.342) 1.589 (1.378–1.832) < 0.001 Pacemaker/ICD implantation 271/4,943 (5.5%) 405/4,865 (8.3%) 0.659 (0.568–0.764) 0.847 (0.726–0.988) 0.035 Heart failure 297/1,074 (27.7%) 370/1,262 (29.3%) 0.943 (0.829–1.073) 1.253 (1.075–1.461) 0.004 Atrial fibrillation 403/3,100 (13.0%) 397/3,230 (12.3%) 1.058 (0.929–1.204) 1.479 (1.287-1.700) < 0.001 4. Discussion This large-scale retrospective analysis demonstrates that hypoalbuminemia serves as a powerful prognostic marker in patients with alcoholic cardiomyopathy, associated with substantially increased mortality and major cardiovascular complications. Our findings provide important insights into risk stratification and potential therapeutic targets in ACM management. The nearly 2.5-fold increased mortality risk associated with hypoalbuminemia in ACM patients is striking and consistent with previous studies in other heart failure populations [ 15 , 16 ]. The magnitude of this association (HR 3.341) exceeds that reported in many traditional cardiovascular risk factors, highlighting the profound prognostic significance of hypoalbuminemia in this vulnerable population. Several mechanisms may explain the adverse outcomes associated with hypoalbuminemia in ACM. First, hypoalbuminemia reflects severe malnutrition, common in chronic alcohol users due to poor dietary intake, malabsorption, and alcohol's direct effects on nutrient metabolism [ 17 ]. Malnutrition compromises immune function, wound healing, and overall physiological reserve, predisposing to infections and other complications. Second, hypoalbuminemia indicates heightened inflammatory burden, as albumin is a negative acute-phase reactant [ 18 ]. Chronic inflammation accelerates atherosclerosis, promotes cardiac remodeling, and contributes to heart failure progression. In ACM, the combination of alcohol-induced inflammation and systemic inflammatory response may create a particularly toxic milieu. Third, hypoalbuminemia alters drug pharmacokinetics, potentially affecting the efficacy of heart failure medications [ 19 ]. Many cardiovascular drugs are protein-bound, and reduced albumin levels may lead to altered drug distribution and clearance, potentially compromising therapeutic effectiveness. The increased risk of cardiogenic shock, acute kidney injury, and other cardiovascular complications in hypoalbuminemic ACM patients likely reflects the multisystem impact of severe nutritional and inflammatory derangement. Cardiogenic shock represents end-stage heart failure, and the 2.2-fold increased risk suggests that hypoalbuminemia identifies patients at highest risk for acute decompensation. The substantially higher AKI risk (HR 2.157) in hypoalbuminemic patients is concerning but not unexpected. Hypoalbuminemia contributes to intravascular volume depletion, reduced renal perfusion, and increased susceptibility to nephrotoxic insults [ 20 ]. In ACM patients, concurrent alcohol-related kidney disease may compound this risk. Interestingly, patients with hypoalbuminemia had lower rates of pacemaker and ICD implantation despite higher arrhythmia burden. This apparent paradox may reflect competing mortality risk, with hypoalbuminemic patients having shorter survival times that preclude device implantation. Alternatively, these patients may be considered poor candidates for invasive procedures due to their overall poor condition and limited life expectancy. The clinical implications of our findings are significant. First, albumin measurement should be incorporated into routine assessment of ACM patients as a simple, inexpensive prognostic tool. Hypoalbuminemia identifies a high-risk subgroup requiring intensive monitoring and potentially more aggressive interventions. Second, nutritional assessment and intervention should be prioritized in ACM patients, particularly those with hypoalbuminemia. While albumin replacement alone is unlikely to improve outcomes, comprehensive nutritional rehabilitation including protein supplementation, micronutrient correction, and alcohol cessation support may modify the underlying pathophysiology [ 21 ]. Third, the profound mortality increase associated with hypoalbuminemia suggests these patients may benefit from earlier consideration of advanced heart failure therapies, including mechanical circulatory support or cardiac transplantation evaluation, where appropriate [ 22 ]. Several limitations should be acknowledged. As an observational study, residual confounding cannot be excluded despite robust propensity matching. The specific causes of hypoalbuminemia (malnutrition vs. liver disease vs. inflammation) could not be definitively determined from available data. Alcohol consumption patterns, duration, and cessation status were not available, limiting assessment of these important variables. Additionally, laboratory values represent single time points, and albumin fluctuations over time could not be assessed. The administrative coding-based approach may have missed some outcomes or included miscoded events. Finally, the specific mechanisms linking hypoalbuminemia to adverse outcomes in ACM require further investigation through prospective studies. Despite these limitations, our study provides compelling evidence for hypoalbuminemia as a prognostic marker in ACM, with important clinical implications for risk stratification and management strategies. 5. Conclusion Hypoalbuminemia serves as a powerful prognostic marker in patients with alcoholic cardiomyopathy, associated with substantially increased all-cause mortality and major cardiovascular complications. The magnitude of risk associated with hypoalbuminemia exceeds many traditional cardiovascular risk factors, highlighting its clinical importance in this population. These findings suggest that serum albumin should be routinely measured in ACM patients for risk stratification and prognostication. Patients with hypoalbuminemia require intensive monitoring and may benefit from comprehensive nutritional interventions, earlier advanced heart failure therapy consideration, and aggressive management of comorbidities. Future research should focus on prospective validation of these findings, investigation of interventions to correct hypoalbuminemia and improve outcomes, and elucidation of the specific mechanisms linking hypoalbuminemia to adverse outcomes in alcoholic cardiomyopathy. Additionally, development of risk prediction models incorporating albumin levels may enhance clinical decision-making in this high-risk population. Our results provide real-world evidence supporting the prognostic value of a simple, readily available laboratory marker in alcoholic cardiomyopathy, with potential implications for improving patient care and outcomes in this challenging condition. Declarations Ethics approval and consent to participate: This study did not require ethics committee approval or informed consent, as it used de-identified data from the TriNetX Research Network and was deemed exempt from Institutional Review Board approval under 45 CFR 46.104(d)(4). No participants under the age of 16 were included Funding No external funding was received for this study. Author Contribution All authors reviewed the manuscript References Guzzo-Merello G, Cobo-Marcos M, Gallardo E, et al. Alcoholic cardiomyopathy. World J Cardiol. 2014;6(8):771–781. doi: 10.4330/wjc.v6.i8.771 . Piano MR. Alcoholic cardiomyopathy: incidence, clinical characteristics, and pathophysiology. 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The 2016 International Society for Heart Lung Transplantation listing criteria for heart transplantation: A 10-year update. J Heart Lung Transplant. 2016;35(1):1–23. doi: 10.1016/j.healun.2015.10.023 . Additional Declarations No competing interests reported. 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6745450","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":465509202,"identity":"729895a5-d869-4280-bc37-6ac345af247b","order_by":0,"name":"EKOW ESSIEN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYDACHhBRwSYHog48IF7LGT5jsJYEorUwtsklNoA4RGnh5zl8TOJjm1n6/LDDD4G22MnpNhDQItnbliY541xa7sbbaQZALcnGZgcIaDE4z2N2m6fsWO7G2QkgLQcStxHSYg/S8oftf7rh7PQPxGkx4O0xu83QxpYgL51DpC0SZ46l/+w5w2a4QTqn4ECCARF+4e9JPmzwo4JNXn52+uYPHyrs5AhqQbgQrNKAWOUgIN9AiupRMApGwSgYUQAAoe1Gu8rk1HsAAAAASUVORK5CYII=","orcid":"","institution":"Aurora Health Care","correspondingAuthor":true,"prefix":"","firstName":"EKOW","middleName":"","lastName":"ESSIEN","suffix":""},{"id":465509203,"identity":"023148d2-577a-4467-9f3c-5334178e082a","order_by":1,"name":"Abena Agyekum","email":"","orcid":"","institution":"SUNY Downstate Health Sciences University","correspondingAuthor":false,"prefix":"","firstName":"Abena","middleName":"","lastName":"Agyekum","suffix":""},{"id":465509204,"identity":"fc3f27ad-6464-4129-aa92-40947a31e71c","order_by":2,"name":"Karldon Nwaezeapu","email":"","orcid":"","institution":"Trinity Health","correspondingAuthor":false,"prefix":"","firstName":"Karldon","middleName":"","lastName":"Nwaezeapu","suffix":""},{"id":465509205,"identity":"a987215c-24a2-4474-81fe-2f1f9f687b3b","order_by":3,"name":"Abraham Carboo","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Abraham","middleName":"","lastName":"Carboo","suffix":""},{"id":465509206,"identity":"6fb65bf1-2c24-446a-8a3a-1eedd7d82fa3","order_by":4,"name":"Godbless Ajenaghughrure","email":"","orcid":"","institution":"TriHealth","correspondingAuthor":false,"prefix":"","firstName":"Godbless","middleName":"","lastName":"Ajenaghughrure","suffix":""},{"id":465509207,"identity":"bfe4b31a-7d86-46a1-a49b-70d8f0916820","order_by":5,"name":"Justice Owusu-Achiaw","email":"","orcid":"","institution":"37 Military Hospital","correspondingAuthor":false,"prefix":"","firstName":"Justice","middleName":"","lastName":"Owusu-Achiaw","suffix":""},{"id":465509208,"identity":"42626778-0d89-44dc-930f-a3f74c04ddc6","order_by":6,"name":"Edmund Bediako","email":"","orcid":"","institution":"The Shelburne Hospital","correspondingAuthor":false,"prefix":"","firstName":"Edmund","middleName":"","lastName":"Bediako","suffix":""}],"badges":[],"createdAt":"2025-05-25 19:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6745450/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6745450/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84219055,"identity":"b734be98-0764-4134-8e10-f16e729a1a18","added_by":"auto","created_at":"2025-06-09 11:21:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall Survival in Alcoholic Cardiomyopathy Patients Stratified by Albumin Levels\u003c/strong\u003e Kaplan-Meier survival curves showing significantly reduced survival in patients with hypoalbuminemia compared to those with normal albumin levels (5-year survival: 46.48% vs 77.69%; HR 3.341, 95% CI 3.072-3.633; p\u0026lt;0.001). Median survival was 1,587 days in the hypoalbuminemia group versus not reached in the normal albumin group.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6745450/v1/4fc7f60197e2bc5692f21d84.png"},{"id":84220225,"identity":"7ed3f668-b01f-4407-b817-7ef3bdcf913b","added_by":"auto","created_at":"2025-06-09 11:29:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14398,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTime to Cardiogenic Shock Stratified by Albumin Levels \u003c/strong\u003eKaplan-Meier curves demonstrating higher incidence of cardiogenic shock in patients with hypoalbuminemia (5-year event-free survival: 85.41% vs 93.42%; HR 2.241, 95% CI 1.883-2.667; p\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6745450/v1/777e9d5779b45bfc0da932c5.png"},{"id":84219059,"identity":"5bf57ce7-cddc-4a1d-aebe-3798419657cd","added_by":"auto","created_at":"2025-06-09 11:21:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56242,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTime to Acute Kidney Injury Stratified by Albumin Levels \u003c/strong\u003eKaplan-Meier curves showing substantially higher rates of acute kidney injury in hypoalbuminemic patients (5-year event-free survival: 50.04% vs 73.04%; HR 2.157, 95% CI 1.943-2.395; p\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6745450/v1/69aff5f4826e2093f1fe970c.png"},{"id":84219057,"identity":"a88ce9c0-5c92-4b06-a608-54e53d34be45","added_by":"auto","created_at":"2025-06-09 11:21:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":77867,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTime to Ventricular Tachycardia Stratified by Albumin Levels \u003c/strong\u003eKaplan-Meier curves illustrating increased incidence of ventricular tachycardia in patients with hypoalbuminemia (5-year event-free survival: 80.34% vs 86.31%; HR 1.510, 95% CI 1.313-1.738; p\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6745450/v1/f980754f6d9390e7c6f56f13.png"},{"id":103742533,"identity":"70628126-42e1-4a92-b5cc-561fc86133e5","added_by":"auto","created_at":"2026-03-02 11:12:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1112401,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6745450/v1/11addda6-a71c-49a9-bcf6-29f6304a18c1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hypoalbuminemia as a Prognostic Marker in Alcoholic Cardiomyopathy: A TriNetX-Based Retrospective Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAlcoholic cardiomyopathy (ACM) represents a distinct form of dilated cardiomyopathy caused by chronic alcohol consumption, accounting for approximately 21\u0026ndash;36% of all dilated cardiomyopathy cases [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The condition is characterized by left ventricular dilatation, reduced ejection fraction, and progressive heart failure symptoms, with significant morbidity and mortality implications [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite advances in heart failure management, ACM continues to carry a poor prognosis, particularly in advanced stages.\u003c/p\u003e \u003cp\u003eThe pathophysiology of ACM involves multiple mechanisms including direct cardiotoxic effects of alcohol and its metabolites, oxidative stress, mitochondrial dysfunction, and protein synthesis impairment [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Chronic alcohol consumption also leads to malnutrition, systemic inflammation, and metabolic derangements that may compound cardiac dysfunction [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among these, hypoalbuminemia emerges as a potential biomarker reflecting both nutritional status and disease severity.\u003c/p\u003e \u003cp\u003eAlbumin, synthesized exclusively by the liver, serves multiple physiological functions including oncotic pressure maintenance, antioxidant activity, and transport of various substances [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Hypoalbuminemia in cardiovascular disease has been associated with worse outcomes across various conditions, including heart failure, acute coronary syndromes, and cardiac surgery [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The mechanisms underlying this association include increased inflammatory burden, impaired drug distribution, compromised wound healing, and increased susceptibility to infections [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the context of alcoholic cardiomyopathy, hypoalbuminemia may result from multiple factors including poor nutritional intake, malabsorption, hepatic dysfunction, chronic inflammation, and increased protein losses [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The combination of cardiac dysfunction and hypoalbuminemia may create a particularly high-risk phenotype, yet comprehensive data on this association remain limited.\u003c/p\u003e \u003cp\u003ePrevious studies examining hypoalbuminemia in heart failure have predominantly focused on ischemic or idiopathic dilated cardiomyopathy, with limited specific data on alcoholic etiology [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given the unique pathophysiology and patient characteristics associated with ACM, dedicated investigation of hypoalbuminemia's prognostic role in this population is essential.\u003c/p\u003e \u003cp\u003eTherefore, we conducted this large-scale retrospective analysis using the TriNetX Research Network to comprehensively evaluate the prognostic significance of hypoalbuminemia in patients with alcoholic cardiomyopathy. We hypothesized that hypoalbuminemia would be associated with increased mortality and cardiovascular complications in ACM patients.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data Source\u003c/h2\u003e \u003cp\u003eThis study utilized the TriNetX Research Network, a global federated health research platform providing access to electronic medical records across 129 healthcare organizations. The platform enables real-time analysis of de-identified patient data while maintaining privacy and security standards. Data encompass diagnoses, procedures, medications, laboratory values, and demographic information from diverse healthcare settings across multiple geographic regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Population\u003c/h2\u003e \u003cp\u003eWe identified adult patients aged 18\u0026ndash;90 years with alcoholic cardiomyopathy (ICD-10 code I42.6). Patients were stratified into two cohorts based on serum albumin levels: (1) hypoalbuminemia group with albumin\u0026thinsp;\u0026le;\u0026thinsp;3.40 g/dL and (2) normal albumin group with albumin\u0026thinsp;\u0026ge;\u0026thinsp;3.50 g/dL, using the most recent albumin measurement. The albumin cutoff values were chosen based on established clinical thresholds for hypoalbuminemia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe index event was defined as the concurrent presence of alcoholic cardiomyopathy diagnosis and the qualifying albumin level. Patients were followed for up to 5 years (1,825 days) after the index event, with outcomes analyzed starting 1 day after the index event to exclude prevalent cases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Outcomes\u003c/h2\u003e \u003cp\u003eThe primary outcome was all-cause mortality during the follow-up period. Secondary outcomes included cardiogenic shock, heart failure progression, ventricular tachycardia, atrial fibrillation, acute kidney injury (AKI), pacemaker and implantable cardioverter-defibrillator (ICD) implantation, cerebrovascular disease, pulmonary embolism, chronic kidney disease (CKD), and pulmonary hypertension. Hospital admissions and ICU admissions were also evaluated as measures of healthcare utilization.\u003c/p\u003e \u003cp\u003eFor each outcome, patients with the specific condition prior to the index event were excluded from the respective analysis to ensure evaluation of incident events only.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Propensity Score Matching\u003c/h2\u003e \u003cp\u003eTo minimize confounding and create comparable cohorts, propensity score matching was performed using baseline demographics and comorbidities. Matching variables included age, sex, race, ethnicity, and key comorbidities such as acute kidney failure, chronic kidney disease, metabolic disorders, and hypertensive diseases. Patients were matched 1:1 using nearest-neighbor matching without replacement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics were compared between matched groups using standardized mean differences, with values\u0026thinsp;\u0026lt;\u0026thinsp;0.1 indicating good balance. For outcomes analysis, we employed three approaches: (1) risk analysis calculating event rates, risk differences, risk ratios, and odds ratios with 95% confidence intervals; (2) Kaplan-Meier survival analysis with log-rank tests and Cox proportional hazards models; and (3) number of instances analysis for recurrent events.\u003c/p\u003e \u003cp\u003eStatistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all analyses. All statistical procedures were conducted using the TriNetX platform's built-in analytics tools.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Ethical Considerations\u003c/h2\u003e \u003cp\u003eThis study used de-identified data from the TriNetX Research Network and was exempt from Institutional Review Board approval according to 45 CFR 46.104(d)(4). The study was conducted in accordance with the Declaration of Helsinki and STROBE guidelines for observational studies.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline Characteristics\u003c/h2\u003e \u003cp\u003eBefore propensity score matching, we identified 5,754 patients with alcoholic cardiomyopathy and hypoalbuminemia and 9,620 patients with alcoholic cardiomyopathy and normal albumin levels. After propensity matching, 5,241 patients remained in each cohort, with excellent balance achieved across demographic and clinical characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe matched cohorts showed no significant differences in age (mean 58.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8 vs 58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1 years), sex distribution (male 82.7% vs 83.3%), or racial composition. Key comorbidities were also well-balanced, including acute kidney failure and chronic kidney disease (37.0% vs 37.4%), metabolic disorders (68.6% vs 69.3%), and hypertensive diseases (66.6% vs 67.6%).\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\u003eBaseline Characteristics of Propensity-Matched Cohorts\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypoalbuminemia (N\u0026thinsp;=\u0026thinsp;5,241)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal Albumin (N\u0026thinsp;=\u0026thinsp;5,241)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd Diff.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\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 \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at Index (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,332 (82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,367 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e767 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e751 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\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=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,028 (57.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,102 (59.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,225 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,202 (22.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican Indian/Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e355 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e351 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,935 (75.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,989 (76.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eAcute kidney failure and CKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,941 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,960 (37.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,594 (68.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,634 (69.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,490 (66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,543 (67.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022\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=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Primary Outcome: All-Cause Mortality\u003c/h2\u003e \u003cp\u003eAll-cause mortality occurred in 1,858 patients (36.2%) in the hypoalbuminemia group compared to 785 patients (15.1%) in the normal albumin group (Risk Ratio 2.397, 95% CI 2.226\u0026ndash;2.581; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Kaplan-Meier survival analysis demonstrated significantly lower survival probability in the hypoalbuminemia group (46.48% vs 77.69% at 5 years; HR 3.341, 95% CI 3.072\u0026ndash;3.633; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Median survival was 1,587 days in the hypoalbuminemia group, while median survival was not reached in the normal albumin group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Secondary Outcomes\u003c/h2\u003e \u003cp\u003ePatients with hypoalbuminemia experienced significantly higher rates of major cardiovascular complications. Cardiogenic shock occurred in 331 patients (7.3%) in the hypoalbuminemia group versus 208 patients (4.3%) in the normal albumin group (HR 2.241, 95% CI 1.883\u0026ndash;2.667; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAcute kidney injury was substantially more frequent in the hypoalbuminemia group, affecting 824 patients (29.0%) compared to 621 patients (18.8%) in the normal albumin group (HR 2.157, 95% CI 1.943\u0026ndash;2.395; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eVentricular tachycardia occurred in 407 patients (9.6%) in the hypoalbuminemia group versus 382 patients (8.7%) in the normal albumin group (HR 1.510, 95% CI 1.313\u0026ndash;1.738; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, pulmonary embolism was more common in the hypoalbuminemia group (3.7% vs 3.0%; HR 1.692, 95% CI 1.362\u0026ndash;2.103; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eChronic kidney disease developed in 601 patients (15.7%) in the hypoalbuminemia group compared to 557 patients (14.1%) in the normal albumin group (HR 1.570, 95% CI 1.399\u0026ndash;1.763; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Pulmonary hypertension was also more frequent in the hypoalbuminemia group (9.7% vs 8.3%; HR 1.589, 95% CI 1.378\u0026ndash;1.832; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eInterestingly, pacemaker and ICD implantation was less common in the hypoalbuminemia group (5.5% vs 8.3%; HR 0.847, 95% CI 0.726\u0026ndash;0.988; p\u0026thinsp;=\u0026thinsp;0.035), possibly reflecting competing mortality risk or reduced procedural candidacy.\u003c/p\u003e \u003cp\u003eNo significant differences were observed in heart failure progression, atrial fibrillation, or cerebrovascular disease between the groups.\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\u003eRisk Ratios and Hazard Ratios of Primary and Secondary Outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypoalbuminemia (N varies)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal Albumin (N varies)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRisk Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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\u003e\u003cb\u003eAll-cause mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,858/5,138 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e785/5,204 (15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.397 (2.226\u0026ndash;2.581)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.341 (3.072\u0026ndash;3.633)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiogenic shock\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e331/4,564 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e208/4,784 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.668 (1.409\u0026ndash;1.974)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.241 (1.883\u0026ndash;2.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcute kidney injury\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e824/2,840 (29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e621/3,306 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.545 (1.410\u0026ndash;1.692)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.157 (1.943\u0026ndash;2.395)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVentricular tachycardia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e407/4,252 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e382/4,369 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.095 (0.958\u0026ndash;1.251)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.510 (1.313\u0026ndash;1.738)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary embolism\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e182/4,893 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149/4,980 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.243 (1.005\u0026ndash;1.538)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.692 (1.362\u0026ndash;2.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic kidney disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e601/3,834 (15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e557/3,961 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.115 (1.002\u0026ndash;1.240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.570 (1.399\u0026ndash;1.763)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary hypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e407/4,202 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360/4,356 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.172 (1.024\u0026ndash;1.342)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.589 (1.378\u0026ndash;1.832)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePacemaker/ICD implantation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e271/4,943 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e405/4,865 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.659 (0.568\u0026ndash;0.764)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.847 (0.726\u0026ndash;0.988)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeart failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e297/1,074 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e370/1,262 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.943 (0.829\u0026ndash;1.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.253 (1.075\u0026ndash;1.461)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\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\u003e403/3,100 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e397/3,230 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.058 (0.929\u0026ndash;1.204)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.479 (1.287-1.700)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\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"},{"header":"4. Discussion","content":"\u003cp\u003eThis large-scale retrospective analysis demonstrates that hypoalbuminemia serves as a powerful prognostic marker in patients with alcoholic cardiomyopathy, associated with substantially increased mortality and major cardiovascular complications. Our findings provide important insights into risk stratification and potential therapeutic targets in ACM management.\u003c/p\u003e \u003cp\u003eThe nearly 2.5-fold increased mortality risk associated with hypoalbuminemia in ACM patients is striking and consistent with previous studies in other heart failure populations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The magnitude of this association (HR 3.341) exceeds that reported in many traditional cardiovascular risk factors, highlighting the profound prognostic significance of hypoalbuminemia in this vulnerable population.\u003c/p\u003e \u003cp\u003eSeveral mechanisms may explain the adverse outcomes associated with hypoalbuminemia in ACM. First, hypoalbuminemia reflects severe malnutrition, common in chronic alcohol users due to poor dietary intake, malabsorption, and alcohol's direct effects on nutrient metabolism [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Malnutrition compromises immune function, wound healing, and overall physiological reserve, predisposing to infections and other complications.\u003c/p\u003e \u003cp\u003eSecond, hypoalbuminemia indicates heightened inflammatory burden, as albumin is a negative acute-phase reactant [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Chronic inflammation accelerates atherosclerosis, promotes cardiac remodeling, and contributes to heart failure progression. In ACM, the combination of alcohol-induced inflammation and systemic inflammatory response may create a particularly toxic milieu.\u003c/p\u003e \u003cp\u003eThird, hypoalbuminemia alters drug pharmacokinetics, potentially affecting the efficacy of heart failure medications [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Many cardiovascular drugs are protein-bound, and reduced albumin levels may lead to altered drug distribution and clearance, potentially compromising therapeutic effectiveness.\u003c/p\u003e \u003cp\u003eThe increased risk of cardiogenic shock, acute kidney injury, and other cardiovascular complications in hypoalbuminemic ACM patients likely reflects the multisystem impact of severe nutritional and inflammatory derangement. Cardiogenic shock represents end-stage heart failure, and the 2.2-fold increased risk suggests that hypoalbuminemia identifies patients at highest risk for acute decompensation.\u003c/p\u003e \u003cp\u003eThe substantially higher AKI risk (HR 2.157) in hypoalbuminemic patients is concerning but not unexpected. Hypoalbuminemia contributes to intravascular volume depletion, reduced renal perfusion, and increased susceptibility to nephrotoxic insults [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In ACM patients, concurrent alcohol-related kidney disease may compound this risk.\u003c/p\u003e \u003cp\u003eInterestingly, patients with hypoalbuminemia had lower rates of pacemaker and ICD implantation despite higher arrhythmia burden. This apparent paradox may reflect competing mortality risk, with hypoalbuminemic patients having shorter survival times that preclude device implantation. Alternatively, these patients may be considered poor candidates for invasive procedures due to their overall poor condition and limited life expectancy.\u003c/p\u003e \u003cp\u003eThe clinical implications of our findings are significant. First, albumin measurement should be incorporated into routine assessment of ACM patients as a simple, inexpensive prognostic tool. Hypoalbuminemia identifies a high-risk subgroup requiring intensive monitoring and potentially more aggressive interventions.\u003c/p\u003e \u003cp\u003eSecond, nutritional assessment and intervention should be prioritized in ACM patients, particularly those with hypoalbuminemia. While albumin replacement alone is unlikely to improve outcomes, comprehensive nutritional rehabilitation including protein supplementation, micronutrient correction, and alcohol cessation support may modify the underlying pathophysiology [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThird, the profound mortality increase associated with hypoalbuminemia suggests these patients may benefit from earlier consideration of advanced heart failure therapies, including mechanical circulatory support or cardiac transplantation evaluation, where appropriate [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. As an observational study, residual confounding cannot be excluded despite robust propensity matching. The specific causes of hypoalbuminemia (malnutrition vs. liver disease vs. inflammation) could not be definitively determined from available data. Alcohol consumption patterns, duration, and cessation status were not available, limiting assessment of these important variables.\u003c/p\u003e \u003cp\u003eAdditionally, laboratory values represent single time points, and albumin fluctuations over time could not be assessed. The administrative coding-based approach may have missed some outcomes or included miscoded events. Finally, the specific mechanisms linking hypoalbuminemia to adverse outcomes in ACM require further investigation through prospective studies.\u003c/p\u003e \u003cp\u003eDespite these limitations, our study provides compelling evidence for hypoalbuminemia as a prognostic marker in ACM, with important clinical implications for risk stratification and management strategies.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eHypoalbuminemia serves as a powerful prognostic marker in patients with alcoholic cardiomyopathy, associated with substantially increased all-cause mortality and major cardiovascular complications. The magnitude of risk associated with hypoalbuminemia exceeds many traditional cardiovascular risk factors, highlighting its clinical importance in this population.\u003c/p\u003e \u003cp\u003eThese findings suggest that serum albumin should be routinely measured in ACM patients for risk stratification and prognostication. Patients with hypoalbuminemia require intensive monitoring and may benefit from comprehensive nutritional interventions, earlier advanced heart failure therapy consideration, and aggressive management of comorbidities.\u003c/p\u003e \u003cp\u003eFuture research should focus on prospective validation of these findings, investigation of interventions to correct hypoalbuminemia and improve outcomes, and elucidation of the specific mechanisms linking hypoalbuminemia to adverse outcomes in alcoholic cardiomyopathy. Additionally, development of risk prediction models incorporating albumin levels may enhance clinical decision-making in this high-risk population.\u003c/p\u003e \u003cp\u003eOur results provide real-world evidence supporting the prognostic value of a simple, readily available laboratory marker in alcoholic cardiomyopathy, with potential implications for improving patient care and outcomes in this challenging condition.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003eThis study did not require ethics committee approval or informed consent, as it used de-identified data from the TriNetX Research Network and was deemed exempt from Institutional Review Board approval under 45 CFR 46.104(d)(4). No participants under the age of 16 were included\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo external funding was received for this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors reviewed the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGuzzo-Merello G, Cobo-Marcos M, Gallardo E, et al. Alcoholic cardiomyopathy. World J Cardiol. 2014;6(8):771\u0026ndash;781. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4330/wjc.v6.i8.771\u003c/span\u003e\u003cspan address=\"10.4330/wjc.v6.i8.771\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePiano MR. Alcoholic cardiomyopathy: incidence, clinical characteristics, and pathophysiology. 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J Heart Lung Transplant. 2016;35(1):1\u0026ndash;23. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.healun.2015.10.023\u003c/span\u003e\u003cspan address=\"10.1016/j.healun.2015.10.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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, hypoalbuminemia, prognosis, mortality, heart failure","lastPublishedDoi":"10.21203/rs.3.rs-6745450/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6745450/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAlcoholic cardiomyopathy (ACM) is a significant cause of heart failure with substantial morbidity and mortality. Hypoalbuminemia, a marker of malnutrition and systemic inflammation, may serve as a prognostic indicator in ACM patients. This study aimed to evaluate the prognostic significance of hypoalbuminemia in patients with alcoholic cardiomyopathy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort study using the TriNetX Research Network, analyzing data from 129 healthcare organizations. Adult patients (18\u0026ndash;90 years) with alcoholic cardiomyopathy were stratified into two cohorts: hypoalbuminemia (albumin\u0026thinsp;\u0026le;\u0026thinsp;3.40 g/dL; n\u0026thinsp;=\u0026thinsp;5,754) and normal albumin (albumin\u0026thinsp;\u0026ge;\u0026thinsp;3.50 g/dL; n\u0026thinsp;=\u0026thinsp;9,620). After propensity score matching, 5,241 patients remained in each cohort. Primary outcome was all-cause mortality. Secondary outcomes included cardiovascular complications, acute kidney injury, and hospital utilization over a 5-year follow-up period.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePatients with hypoalbuminemia demonstrated significantly higher all-cause mortality compared to those with normal albumin levels (36.2% vs 15.1%; HR 3.341, 95% CI 3.072\u0026ndash;3.633; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hypoalbuminemia was associated with increased risks of cardiogenic shock (7.3% vs 4.3%; HR 2.241, 95% CI 1.883\u0026ndash;2.667; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), acute kidney injury (29.0% vs 18.8%; HR 2.157, 95% CI 1.943\u0026ndash;2.395; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ventricular tachycardia (9.6% vs 8.7%; HR 1.510, 95% CI 1.313\u0026ndash;1.738; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and pulmonary embolism (3.7% vs 3.0%; HR 1.692, 95% CI 1.362\u0026ndash;2.103; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Paradoxically, patients with hypoalbuminemia had lower rates of pacemaker implantation (5.5% vs 8.3%; HR 0.847, 95% CI 0.726\u0026ndash;0.988; p\u0026thinsp;=\u0026thinsp;0.035).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHypoalbuminemia serves as a powerful prognostic marker in alcoholic cardiomyopathy, associated with significantly increased mortality and cardiovascular complications. These findings suggest that albumin levels should be routinely monitored and nutritional interventions considered in ACM management to potentially improve outcomes.\u003c/p\u003e","manuscriptTitle":"Hypoalbuminemia as a Prognostic Marker in Alcoholic Cardiomyopathy: A TriNetX-Based Retrospective Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 11:20:57","doi":"10.21203/rs.3.rs-6745450/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":"39c21010-85f4-4518-8e73-4c48c8cf68ca","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T11:11:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-09 11:20:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6745450","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6745450","identity":"rs-6745450","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}