{"paper_id":"3d0e8368-08a0-41e9-a361-e95d49e2def3","body_text":"Disparities in Outcomes of Alcohol-Associated Cirrhosis: Increased Mortality and Procedural Burden in a Nationwide Study | 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 Disparities in Outcomes of Alcohol-Associated Cirrhosis: Increased Mortality and Procedural Burden in a Nationwide Study Idan Grossmann, Karolina Kaczmarczyk, Katherine Margolin, Harshavardhan Sanekommu, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9012817/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: Alcohol-associated cirrhosis is a leading cause of liver-related hospitalizations and mortality globally. Despite its prevalence, the determinants of clinical outcomes, procedural utilization, and disparities by race and gender remain incompletely characterized. This study aimed to compare in-hospital outcomes and resource utilization between patients with alcohol-associated cirrhosis and those with cirrhosis from other etiologies. Methods: We conducted a retrospective cohort study using the National Inpatient Sample (NIS) from 2016 to 2019. Adult hospitalizations with cirrhosis were stratified by etiology (alcohol-associated vs. other). Primary outcomes included in-hospital mortality, length of stay, and hospitalization costs. Secondary outcomes included utilization of upper gastrointestinal endoscopy (EGD), variceal interventions, transjugular intrahepatic portosystemic shunt (TIPS), hemodialysis, liver transplantation, and blood product transfusions. Multivariable logistic and Poisson regression models were used to assess associations, adjusting for demographics, comorbidities, and hospital characteristics. Results: Among 1,428,425 cirrhosis-related hospitalizations, 733,495 (51.4%) were alcohol-associated. Patients with alcohol-associated cirrhosis were younger (mean age 55.8 vs. 64.0 years), more likely to be male, and had higher Medicaid coverage. In-hospital mortality was higher in alcohol-associated cirrhosis (9.0% vs. 8.4%; adjusted OR 1.13, 95% CI 1.10–1.16, p < 0.001). These patients underwent more EGD (16% vs. 11%; OR 1.50), variceal interventions (11% vs. 8.2%; OR 1.30), TIPS (1.4% vs. 1.1%; OR 1.19), and blood transfusions (17% vs. 13%; OR 1.27), but had lower odds of liver transplantation (1.1% vs. 1.5%; OR 0.57). Female sex and minority race were independently associated with disparities in mortality and procedural utilization, with pronounced effects among alcohol-associated cirrhosis patients. Conclusion: Alcohol-associated cirrhosis is the most common cause of cirrhosis-related hospitalizations and in-hospital mortality and is associated with a higher procedural burden. Notable racial and gender disparities exist in both outcomes and access to advanced procedures. These findings highlight the need for targeted strategies to improve equity and optimize care in patients with alcohol-related cirrhosis. Trial Registration: Not applicable. This study is a retrospective analysis of a publicly available, de-identified administrative database and does not involve a prospective healthcare intervention. Alcohol-associated cirrhosis National Inpatient Sample (NIS) Liver transplantation outcomes. Figures Figure 1 Figure 2 Background Liver cirrhosis accounts for approximately 1.16 million deaths annually [ 1 , 2 ]. Between 2008 and 2014, the financial burden of liver cirrhosis-related hospitalizations in the United States increased by 30.2% to $ 7.37 billion. Patients with cirrhosis also experience longer hospital stays, reflecting the complexity of the disease and the management required [ 3 ]. There is a serious stigma issue and awareness gap surrounding cirrhosis, which results in underdiagnosis and diminished opportunities for early management. Public knowledge of cirrhosis is still poor, and only one in three individuals with the condition are aware of their diagnosis [ 4 ]. Among the various etiologies for liver cirrhosis, alcohol associated cirrhosis (AAC) is responsible for almost 60% of all cirrhosis patients in Europe, North America, and Latin America [ 5 ]. Patients with AAC experience worse clinical outcomes than those with cirrhosis from other causes, including having higher short-term mortality and a greater likelihood of readmission [ 6 , 7 ]. Admissions related to AAC had significantly increased rates of intensive care utilization and advanced procedures, such as endoscopic interventions for variceal bleeding and transjugular intrahepatic portosystemic shunt (TIPS) placement, compared to the cirrhosis of other causes [ 8 ]. Despite the rapidly increasing burden of AAC, there is a paucity of national data comparing inpatient outcomes, resource utilizations, and disparities between AAC and other causes of cirrhosis (OC). While prior studies have described outcomes and disparities among patients with cirrhosis, few have directly compared AAC with OC, and etiology-specific differences in care delivery remain poorly characterized. We use the National Inpatient Sample (NIS) from 2016 to 2019 to compare in-hospital outcomes and resource utilization between patients admitted with AAC and OC. Improved characterization of etiology-specific outcomes may help inform targeted clinical strategies and health system planning for this growing population. Methods Data Availability and Data Source We conducted a retrospective cohort study utilizing data from the National Inpatient Sample (NIS), a component of the Healthcare Cost and Utilization Project (HCUP), for the years 2016 to 2019. The NIS is the largest publicly available all-payer inpatient healthcare database in the United States, encompassing approximately 20% of all discharges from U.S. community hospitals. The database includes de-identified patient information such as demographics, hospital characteristics, primary and secondary diagnoses and procedures, discharge status, length of stay, and total hospital charges. Sampling weights were applied to produce national estimates in accordance with HCUP methodology. Study Population Adult patients (aged ≥ 18 years) hospitalized with complications of cirrhosis were identified using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes. Patients were stratified based on the etiology of cirrhosis into two groups: alcohol-associated cirrhosis and cirrhosis due to other causes. Patients with missing demographic information or transferred to other facilities were excluded from the analysis. The full list of diagnostic codes used is provided in Supplementary Tables 1 and 2 . Hospital and Patient Characteristics Baseline patient characteristics included demographic, clinical, and hospital-level variables available within the National Inpatient Sample (NIS). Patient-level variables included age (analyzed as a continuous variable), sex (male or female), race/ethnicity (Non-Hispanic White, Black, Hispanic, Asian or Pacific Islander, Native American, and Other), and primary payer (Medicare, Medicaid, private/commercial insurance, and others, including self-pay). Comorbidity burden was assessed using the Elixhauser Comorbidity Index and modeled as a continuous variable in multivariable analyses. Hospital-level characteristics included hospital region (Northeast, Midwest, South, and West), hospital location (urban vs rural), teaching status (teaching vs non-teaching), and bed size (small, medium, large), as defined by HCUP. These variables were incorporated into adjusted models to account for potential confounding related to institutional characteristics. All baseline characteristics were compared between hospitalizations for alcohol-associated cirrhosis and cirrhosis due to other etiologies using survey-adjusted statistical methods. Outcomes The primary outcomes were all-cause in-hospital mortality, length of stay (LOS), and total hospitalization costs. In-hospital mortality was defined as death during the index hospitalization. LOS was measured in days. Hospitalization costs were calculated using HCUP cost-to-charge ratios applied to total hospital charges. Secondary outcomes included inpatient procedural utilization, identified using ICD-10-PCS codes, including upper gastrointestinal endoscopy (EGD), endoscopic variceal interventions, transjugular intrahepatic portosystemic shunt (TIPS) placement, hemodialysis, liver transplantation, and blood product transfusions. Procedural outcomes were analyzed as binary variables. A secondary analysis evaluated racial and sex-based disparities in mortality and access to advanced procedures among patients with alcohol-associated cirrhosis. Statistical Analysis All analyses incorporated survey design elements, including discharge weights, to yield nationally representative estimates and adjust for clustering at the hospital level. Descriptive statistics were presented as weighted means (with standard errors) for continuous variables and weighted frequencies (with percentages) for categorical variables. Univariate comparisons were made using survey-adjusted t-tests for continuous variables and Rao-Scott χ² tests for categorical variables. We employed multivariate logistic regression to assess the association between cirrhosis etiology and in-hospital mortality and procedural utilization. LOS was modeled using Poisson regression, and hospitalization costs were analyzed using generalized linear modeling with a gamma distribution and log-link function. All models were adjusted for patient demographics (age, sex, race/ethnicity, payer status) and the Elixhauser Comorbidity Index. In a secondary analysis, we evaluated the presence of potential racial and gender disparities in in-hospital mortality and procedural utilization (EGD, TIPS, dialysis, and liver transplant) across the entire cohort. Statistical significance was defined as a two-sided P value < 0.05. All statistical analyses were performed using Stata/SE version 16.1 (StataCorp LLC, College Station, TX, USA). Results Patients We identified a total of 1,428,425 hospitalizations for complications related to cirrhosis. Of these, 733,495 (51.4%) hospitalizations were attributed to AAC, while 694,930 (48.6%) were related to other etiologies of cirrhosis (Fig. 1 ). Patients with AAC were significantly younger (mean age 55.8) and were more likely to be male (70%). Both groups were predominantly White. Patients with AAC were more frequently insured by Medicaid (34%) and less commonly covered by Medicare (32%) (Table 1 ). Table 1 General characteristics of the study cohort (ETOH vs other cirrhosis) Total hospitalizations Other Cirrhosis ETOH Cirrhosis P value * 694,930 733,495 Age, years - mean (SE) 64.0 (0.05) 55.8 (0.04) < 0.001 Female 326,265 (47%) 218,500 (30%) < 0.001 Race/ethnicity, n (%) Non-Hispanic White 451,640 (65%) 491,810 (67%) < 0.001 Black 77,250 (11%) 65,310 (8.9%) Hispanic 113,225 (16%) 128,565 (18%) Asian 23,105 (3.3%) 9,340 (1.3%) Native American 7,010 (1.0%) 17,305 (2.4%) Other 22,700 (3.3%) 21,165 (2.9%) Primary payer, n (%) Medicare 404,235 (58%) 237,190 (32%) < 0.001 Medicaid 121,840 (18%) 246,500 (34%) Private/commercial 124,610 (18%) 161,420 (22%) Other (including self-pay) 43,360 (6.2%) 87,160 (12%) Elixhauser comorbidity score - mean (SE) 5.3 (0.01) 5.5 (0.01) < 0.001 In-hospital outcomes Mortality, n (%) 58,140 (8.4%) 65,810 (9.0%) < 0.001 Length of stay in days (mean ± SE) 6.8 (0.03) 7.0 (0.03) < 0.001 Primary outcomes In-hospital mortality was higher in AAC compared to OC (9.0% vs 8.4%; p < 0.001), and AAC remained independently associated with increased odds of in-hospital mortality after adjustment (aOR 1.13; 95% CI 1.10–1.16). Although mean length of stay and median hospitalization costs were slightly higher in unadjusted comparisons for AAC, adjusted models showed modestly lower length of stay and costs for AAC relative to OC (adjusted ratio 0.98 [95% CI 0.97–0.99] and 0.93 [95% CI 0.92–0.95], respectively) (Table 2 ). Table 2 Primary Outcomes Other Cirrhosis ETOH Cirrhosis Adjusted OR/RR * 95% CI P-value n = 694,930 n = 733,495 In-hospital Mortality 58,140 (8.4%) 65,810 (9.0%) 1.13 1.10, 1.16 < 0.001 Length of Stay - mean (SE) 6.8 (0.03) 7.0 (0.03) 0.98 0.97, 0.99 < 0.001 Hospitalization cost (US $ , 2019 **) - median (IQR) 11,430 (6,779 − 20,937) 11,697 (6,939 − 21,680) 0.93 0.92, 0.95 < 0.001 Resource utilization Compared with other cirrhosis etiologies, patients with AAC were significantly more likely to undergo EGD(16% vs. 11%; adjusted OR 1.50, 95% CI 1.46–1.53, p < 0.001) and variceal ligation or other endoscopic control of bleeding (11% vs. 8.2%; adjusted OR 1.30, 95% CI 1.27–1.34). AAC was also associated with increased utilization of TIPS (adjusted OR 1.19, 95% CI 1.10–1.28, p < 0.001), red blood cell transfusions (adjusted OR 1.27, 95% CI 1.24–1.31, p < 0.001), platelet transfusions, and fresh frozen plasma transfusions. Conversely, patients with ETOH cirrhosis were less likely to undergo hemodialysis (adjusted OR 0.47, 95% CI 0.46–0.49) or liver transplantation during hospitalization (adjusted OR 0.57, 95% CI 0.53–0.62,) (Table 3 ) Table 3 Utilization of Procedures Upper Gastrointestinal Endoscopy (EGD) Other Cirrhosis ETOH Cirrhosis Adjusted OR * 95% CI P-value 73,960 (11%) 116,315 (16%) 1.5 1.46, 1.53 < 0.001 Variceal Ligation or Other Control of bleeding 56,995 (8.2%) 84,005 (11%) 1.3 1.27, 1.34 < 0.001 Insertion of Sengstaken tube /esophageal tamponade 145 (< 0.1%) 340 (< 0.1%) 2 1.28, 3.14 0.003 Transjugular Intrahepatic Portosystemic shunt 7,950 (1.1%) 10,515 (1.4%) 1.19 1.10, 1.28 < 0.001 Hemodialysis 80,585 (12%) 46,580 (6.4%) 0.47 0.46, 0.49 < 0.001 Liver Transplant 10,670 (1.5%) 8,270 (1.1%) 0.57 0.53, 0.62 < 0.001 Red Blood Cell Transfusion 93,165 (13%) 123,935 (17%) 1.27 1.24, 1.31 < 0.001 Platelets Transfusion 24,445 (3.5%) 35,125 (4.8%) 1.19 1.14, 1.24 < 0.001 Fresh Frozen Plasma Transfusion 6,550 (0.9%) 11,825 (1.6%) 1.43 1.33, 1.55 < 0.001 Racial and gender disparities in care for AAH population Among patients hospitalized with AAC, female sex was independently associated with high in-hospital mortality after multivariable adjustment (aOR 1.08, 95% CI 1.04–1.12). Compared with White patients, Black (aOr 1.08, 95% CI 1.01–1.15) and Native American patients (aOR 1.17, 95% CI 1.03–1.32) had higher adjusted odds of in-hospital mortality, while Hispanic patients had lower adjusted odds (aOR 0.91, 95% CI 0.86–0.95). Significant disparities in access to advanced inpatient procedures were also observed in the AAC cohort. Female patients had lower adjusted odds of TIPS (aOR 0.76, 95% CI 0.69–0.84) and liver transplantation (aOR 0.72, 95% CI 0.64–0.80). Black patients experienced markedly reduced odds of TIPS (aOR 0.54, 95% CI 0.44–0.67) and transplantation (aOR 0.57, 95% CI 0.44–0.75) compared with White patients. In contrast, racial and ethnic minority patients had substantially higher adjusted odds of hemodialysis, most pronounced among Black patients (aOR 2.02, 95% CI 1.88–2.17). Discussion Liver cirrhosis is a major public health concern worldwide, with a rising global incidence of mortality compared to the past, and poses a burden to the healthcare system. AAC is a serious and potentially fatal condition resulting from long-term, excessive alcohol consumption. Among the reasons for cirrhosis, AAC is a dominant etiology that leads to major morbidity and mortality [ 9 ]. Our study shows that AAC is the most common cause of cirrhosis-related hospital admissions, a leading cause of in-hospital death when compared to other cirrhosis etiologies, and it significantly increases the need for resuscitation and procedure utilization. In addition, the study demonstrates a substantial discrepancy in outcomes of patients from different genders and ethnicities. Our study, which included a large sample size of 1,428,425 cirrhosis-related hospitalizations, demonstrated a statistically significant increase in in-hospital mortality among patients admitted with AAC compared to patients with OC (9.0% vs 8.4% OR 1.13, p < 0.001). Similar findings were reported in a cohort study of patients with a confirmed diagnosis of cirrhosis in 2609 patients at the Karolinska University Hospital in Sweden between 2004 and 2017. The study demonstrated that patients with AAC had the highest overall mortality rate [ 10 ]. In contrast to this, a 2022 ICU study found no significant difference in ICU mortality rates between AAC and OC cohorts (10.2% vs 11.7%, p = 0.40) although post-ICU in-hospital mortality was significantly higher in the alcohol-associated group (10.0% vs 6.5%, p = 0.04) [ 5 ]. Moreover, a population-based research in Taiwan of 472 alcoholic and 4,313 non-alcoholic cirrhosis patients revealed that there was no difference in the two groups' six-year survival rates [ 11 ]. Our large cohort study provides a more precise characterization of the differences between alcohol-associated cirrhosis compared with other etiologies. These findings may reflect a more severe and unstable clinical presentation at admission, superimposed on a chronic illness that is often left untreated because of non-compliance and a lack of resources [ 12 , 13 ]. Compared with other etiologies, patients with AAC were significantly more likely to undergo upper gastrointestinal endoscopy (EGD) (16% vs 11% OR 1.5 p < 0.001), receive endoscopic interventions (11% vs 8% OR 1.3 p < 0.01), require TIPS placement (adjusted OR 1.19, 95% CI 1.10–1.28, p < 0.001), and undergo resuscitation with blood products, whereas they were less likely to receive liver transplantation (adjusted OR 0.57, 95% CI 0.53–0.62, p < 0.001). A study that analyzed 34,494 Veterans Affairs patients with end-stage liver disease, demonstrated a 70% reduction in the likelihood of receiving a transplant (HR 0.30) for patients with alcohol-related cirrhosis compared to those with HCV-related cirrhosis [ 14 ] These findings highlight a concerning disparity whereby, despite AAC being a predominant etiology and being associated with substantial in-hospital mortality, affected patients are significantly less likely to undergo liver transplantation. It raises important concerns regarding potential barriers to transplant access and is suggested to be due to multifactorial reasons. Potential contributing factors include the traditional 6-month abstinence requirement, limited social and socioeconomic support, and a higher burden of medical and psychiatric comorbidities, all of which may adversely affect transplant eligibility and access in patients with AAC. A 2023 New England Journal of Medicine review noted that only a small percentage of possible ALD candidates are chosen to be placed on the waiting list using the present psychosocial evaluation-based selection criteria [ 15 ]. Furthermore, a review published in the World Journal of Gastroenterology in 2018 shows that although the survival rates following liver transplantation improve as with any other cause for transplant, AAC is stigmatized, which affects acceptance rates [ 16 ]. The study comprehensively analysed and showed significant ethnic and gender disparities in outcomes and procedure utilization in the specific subgroup of AAC patients. Hispanic patients had a lower mortality risk than White patients, but Black, Asian or Pacific Islander, Native American, and Other race patients had higher rates of in-hospital mortality. Black patients had approximately twofold greater likelihood of obtaining hemodialysis (adjusted OR 2.86, 95% CI 2.75–2.99, p < 0.001) compared to other minority racial groups and significantly decreased likelihood of receiving liver transplantation and TIPS (adjusted OR 0.42, 95% CI 0.35–0.49, p < 0.001). In addition, the study demonstrates gender discrepancies; female AAC patients were independently associated with increased in-hospital mortality (adjusted OR 1.08, 95% CI 1.04–1.12, p < 0.001) and a higher likelihood of undergoing upper gastrointestinal endoscopy (EGD). In contrast, female AAC patients had significantly lower odds of receiving transjugular intrahepatic portosystemic shunt (TIPS) placement (adjusted OR 0.76, 95% CI 0.69–0.84, p < 0.001), hemodialysis (adjusted OR 0.86, 95% CI 0.81–0.90, p < 0.001), and liver transplantation (adjusted OR 0.72, 95% CI 0.64–0.80, p < 0.001) (Table 4 ). A study by Nephew et al., which included all-cause cirrhosis, examined racial and ethnic disparities in the receipt of lifesaving procedures and mortality among hospitalized patients with decompensated cirrhosis, showed no significant racial or ethnic differences in the odds of receiving upper endoscopy for variceal hemorrhage. However, Black patients remained substantially less likely than White patients to undergo TIPS for variceal hemorrhage (OR 0.54, 95% CI 0.47–0.62) and ascites (OR 0.34, 95% CI 0.31–0.38). Black patients had lower odds of liver transplantation (OR 0.66, 95% CI 0.61–0.70), and Hispanic patients also had reduced odds (OR 0.74, 95% CI 0.70–0.78) compared to White patients [ 17 ]. Table 4 Results of multivariate regression models to evaluate for racial and gender bias for in-hospital mortality and procedures (for alcohol-associated cirrhosis population) Characteristic Adjusted OR * 95% CI p-value In-hospital mortality Female 1.08 1.04, 1.12 < 0.001 Race White Reference Reference Reference Black 1.08 1.01, 1.15 0.019 Hispanic 0.91 0.86, 0.95 < 0.001 Asian or Pacific Islander 1.1 0.94, 1.29 0.227 Native American 1.17 1.03, 1.32 0.018 Other 1.16 1.04, 1.29 0.008 Upper Gastrointestinal Endoscopy (EGD) Female 1.07 1.04, 1.11 < 0.001 Race White Reference Reference Reference Black 1.07 1.02, 1.13 0.007 Hispanic 1.02 0.98, 1.07 0.262 Asian or Pacific Islander 1.08 0.96, 1.23 0.214 Native American 1.02 0.93, 1.12 0.657 Other 0.95 0.87, 1.04 0.261 Transjugular Intrahepatic Portosystemic shunt Female 0.76 0.69, 0.84 < 0.001 Race White Reference Reference Reference Black 0.54 0.44, 0.67 < 0.001 Hispanic 0.93 0.82, 1.06 0.267 Asian or Pacific Islander 0.75 0.49, 1.14 0.178 Native American 0.76 0.55, 1.04 0.083 Other 1.03 0.78, 1.35 0.856 Hemodialysis Female 0.86 0.81, 0.90 < 0.001 Race White Reference Reference Reference Black 2.02 1.88, 2.17 < 0.001 Hispanic 1.73 1.62, 1.86 < 0.001 Asian or Pacific Islander 1.87 1.56, 2.25 < 0.001 Native American 1.8 1.56, 2.07 < 0.001 Other 1.65 1.44, 1.88 < 0.001 Liver Transplant Female 0.72 0.64, 0.80 < 0.001 Race White Reference Reference Reference Black 0.57 0.44, 0.75 < 0.001 Hispanic 0.98 0.80, 1.21 0.876 Asian or Pacific Islander 0.87 0.57, 1.32 0.508 Native American 0.63 0.36, 1.09 0.097 Other 1.27 0.97, 1.66 0.088 Strengths This study leverages a large, nationally representative cohort of more than 1.4 million cirrhosis-related hospitalizations, providing substantial statistical power to detect clinically meaningful differences between alcohol-associated and other etiologies while enabling comprehensive multivariable analyses. By directly comparing alcohol-associated cirrhosis with other causes within a unified analytic framework, we provide robust etiology-specific evaluation of mortality, procedural utilization, and resource use. Adjustment for demographic factors, comorbidity burden, and hospital characteristics strengthens the validity of the findings. The stratified analysis by sex and race highlights significant disparities in mortality and access to advanced procedures, including EGD, TIPS, hemodialysis, and liver transplantation, offering granular insight into inequities that remain underexplored in national-level studies (Fig. 2 ). Limitations The study has several limitations. First, the study does not measure confounding variables that can affect the outcomes, such as socioeconomic status and access to liver transplant centers. In addition, adherence to follow-ups and participation in alcohol cessation programs data could add another layer to the stratification of AAC patients compared to the OC patients. Furthermore, it focused only on in-hospital outcomes, and data on readmissions, long-term survival, or post-discharge complications and outcomes was not evaluated. Those additional findings would provide a more comprehensive understanding of the clinical course and assist in creating further stratification and overall prognosis. Conclusion Our study demonstrates that, in comparison to other cirrhosis etiologies, AAC is the most frequent cause of in-hospital mortality, and it dramatically raises the need for resuscitation and procedure utilization. Although AAC has been one of the most dominant causes of healthcare resource burden, this population less frequently receives liver transplantation compared with other etiologies. There are discrepancies in patient outcomes based on gender and ethnicity. Further studies are required to expand the comparison between the AAC and OC patients and to address more factors that lead to the discrepancy, to provide better and equitable care in this population. Abbreviations AAC Alcohol-Associated Cirrhosis OC Other Causes of Cirrhosis NIS National Inpatient Sample HCUP Healthcare Cost and Utilization Project ICD-10-CM International Classification of Diseases, Tenth Revision, Clinical Modification ICD-10-PCS International Classification of Diseases, Tenth Revision, Procedure Coding System EGD Esophagogastroduodenoscopy TIPS Trans-jugular Intrahepatic Portosystemic Shunt LOS Length of Stay OR Odds Ratio aOR Adjusted Odds Ratio CI Confidence Interval RBC Red Blood Cell FFP Fresh Frozen Plasma ICU Intensive Care Unit HCV Hepatitis C Virus ALD Alcohol-Associated Liver Disease Declarations Ethics approval This study used the Nationwide Inpatient Sample (NIS), a publicly available, de-identified database. Institutional Review Board approval was not required in accordance with U.S. federal regulations (45 CFR 46). Consent for publication Informed consent was waived due to the use of anonymized data. Availability of data and materials All data generated or analyzed during this study are included in the manuscript and its supplementary file. Competing interests The authors declare no conflicts of interest. Funding No specific funding was received by authors for this work. Authors' contributions IG and HS conceptualized the review. HS performed the statistical review. IG, and HS contributed to data analysis and data collection. IG, KK, and KM wrote the original draft. HS, CT, AH, MAH, AF and KAK contributed to literature review, writing, and editing. KA and MAH provided critical revisions and clinical expertise. LP, KA, and MAH supervised the project and reviewed the final manuscript. All authors read and approved the final version. Acknowledgements Not applicable References Asrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. J Hepatol. 2019;70(1):151-171. doi:10.1016/j.jhep.2018.09.014. Ginès P, Krag A, Abraldes JG, Solà E, Fabrellas N, Kamath PS. Liver cirrhosis. Lancet. 2021;398(10308):1359-1376. doi:10.1016/S0140-6736(21)01374-X. Liu YB, Chen MK. Epidemiology of liver cirrhosis and associated complications: Current knowledge and future directions. World J Gastroenterol. 2022;28(41):5910-5930. doi:10.3748/wjg.v28.i41.5910. Smith A, Baumgartner K, Bositis C. Cirrhosis: Diagnosis and management. Am Fam Physician. 2019;100(12):759-770. Devarbhavi H, Asrani SK, Arab JP, Nartey YA, Pose E, Kamath PS. Global burden of liver disease: 2023 update. J Hepatol. 2023;79(2):516-537. doi:10.1016/j.jhep.2023.03.017. Choi C, Choi DH, Spears GM, Peeraphatdit TB, Serafim LP, Gajic O, et al. Relationship between etiology of cirrhosis and survival among patients hospitalized in intensive care units. Mayo Clin Proc. 2022;97(2):274-284. doi:10.1016/j.mayocp.2021.08.025. Lone NI, Lee R, Walsh TS. Long-term mortality and hospital resource use in ICU patients with alcohol-related liver disease. Crit Care Med. 2019;47(1):23-32. doi:10.1097/CCM.0000000000003421. Huang YF, Lin CS, Cherng YG, Yeh CC, Chen RJ, Chen TL, et al. A population-based cohort study of mortality of intensive care unit patients with liver cirrhosis. BMC Gastroenterol. 2020;20(1):15. doi:10.1186/s12876-020-1163-1. Huang DQ, Mathurin P, Cortez-Pinto H, Loomba R. Global epidemiology of alcohol-associated cirrhosis and HCC: trends, projections and risk factors. Nat Rev Gastroenterol Hepatol. 2023;20(1):37-49. doi:10.1038/s41575-022-00688-6. Hagström H, Lindfors A, Holmer M, Bengtsson B, Björkström K, Hegmar H, et al. Etiologies and outcomes of cirrhosis in a large contemporary cohort. Scand J Gastroenterol. 2021;56(6):727-732. doi:10.1080/00365521.2021.1912167. Yang TW, Wang CC, Tsai MC, Wang YT, Tseng MH, Lin CC. Comorbidities and outcome of alcoholic and non-alcoholic liver cirrhosis in Taiwan: A population-based study. Int J Environ Res Public Health. 2020;17(8):2825. doi:10.3390/ijerph17082825. Jophlin LL, Singal AK, Bataller R, Wong RJ, Sauer BG, Terrault NA, et al. ACG clinical guideline: Alcohol-associated liver disease. Am J Gastroenterol. 2024;119(1):30-54. doi:10.14309/ajg.0000000000002572. Marot A, Henrion J, Knebel JF, Moreno C, Deltenre P. Alcoholic liver disease confers a worse prognosis than HCV infection and non-alcoholic fatty liver disease among patients with cirrhosis: An observational study. PLoS One. 2017;12(10):e0186715. doi:10.1371/journal.pone.0186715. Kanwal F, Hernaez R, Liu Y, Taylor TJ, Rana A, Kramer JR, et al. Factors associated with access to and receipt of liver transplantation in veterans with end-stage liver disease. JAMA Intern Med. 2021;181(7):949-959. doi:10.1001/jamainternmed.2021.2051. Lucey MR, Furuya KN, Foley DP. Liver transplantation. N Engl J Med. 2023;389(20):1888-1900. doi:10.1056/NEJMra2200923. Marroni CA, Fleck AM Jr, Fernandes SA, Galant LH, Mucenic M, de Mattos Meine MH, et al. Liver transplantation and alcoholic liver disease: History, controversies, and considerations. World J Gastroenterol. 2018;24(26):2785-2805. doi:10.3748/wjg.v24.i26.2785. Nephew LD, Knapp SM, Mohamed KA, Ghabril M, Orman E, Patidar KR, et al. Trends in racial and ethnic disparities in the receipt of lifesaving procedures for hospitalized patients with decompensated cirrhosis in the US, 2009-2018. JAMA Netw Open. 2023;6(7):e2324539. doi:10.1001/jamanetworkopen.2023.24539. Additional Declarations No competing interests reported. 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Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Idan\",\"middleName\":\"\",\"lastName\":\"Grossmann\",\"suffix\":\"\"},{\"id\":618018686,\"identity\":\"10e7903c-6f02-4cf0-8172-407ddb7ba6f5\",\"order_by\":1,\"name\":\"Karolina Kaczmarczyk\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Karolina\",\"middleName\":\"\",\"lastName\":\"Kaczmarczyk\",\"suffix\":\"\"},{\"id\":618018693,\"identity\":\"2ac8963d-c42d-41b3-b00d-78bf4cfce111\",\"order_by\":2,\"name\":\"Katherine Margolin\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian School of Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Katherine\",\"middleName\":\"\",\"lastName\":\"Margolin\",\"suffix\":\"\"},{\"id\":618018700,\"identity\":\"710b3c5a-2ac5-4c15-b406-98dd095dba40\",\"order_by\":3,\"name\":\"Harshavardhan Sanekommu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Harshavardhan\",\"middleName\":\"\",\"lastName\":\"Sanekommu\",\"suffix\":\"\"},{\"id\":618018703,\"identity\":\"633b6c58-2e4f-4db0-a6d9-9ca71b10d34b\",\"order_by\":4,\"name\":\"Chinmay Trivedi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Chinmay\",\"middleName\":\"\",\"lastName\":\"Trivedi\",\"suffix\":\"\"},{\"id\":618018719,\"identity\":\"cae2cb86-3b31-4518-baa9-027f1f4b9bdb\",\"order_by\":5,\"name\":\"Anid Hassan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Anid\",\"middleName\":\"\",\"lastName\":\"Hassan\",\"suffix\":\"\"},{\"id\":618018730,\"identity\":\"0478f9e1-1efa-47ce-a3c4-217a46ac129b\",\"order_by\":6,\"name\":\"Aroob Farooqi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Postgraduate Medical Institute, Ameer-ud-Din medical college\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Aroob\",\"middleName\":\"\",\"lastName\":\"Farooqi\",\"suffix\":\"\"},{\"id\":618018733,\"identity\":\"1151e54a-59dc-4069-b651-57ae1a7814c2\",\"order_by\":7,\"name\":\"Kamil Ahmad Kamil\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDCCA2xAwsCCwQBISSRUAElm5gZitEhAtDw4A9LCSIwWBogWyYdtIA4BLXy3jyV+ulEgIW8udvjhjcR5tdH87UAtPyq24dQieS7tsHSOgYThztlpxhaJ247nzjjM2MDYc+Y2Ti0GZ9gbQFoYN9xOMJNI3HYstwGohZmxDa+W5t9ALfYbbqd/k0iccyx3PmEtbMdAtiRuuJ0DtKWhJncDIS2SZ9jSrIFakoFaii0Sjh3I3QjUchCfX/jOsBnfzvljYwt02MabP2rqcuedP3zwwY8K3FrQwWEweYBo9UBQR4riUTAKRsEoGCEAAPfEX+tks3SwAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Mirwais Regional Hospital\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Kamil\",\"middleName\":\"Ahmad\",\"lastName\":\"Kamil\",\"suffix\":\"\"},{\"id\":618018735,\"identity\":\"ef230fc9-ed73-4037-9b3d-4992dc62a0e1\",\"order_by\":8,\"name\":\"Mohammad Hossain\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammad\",\"middleName\":\"\",\"lastName\":\"Hossain\",\"suffix\":\"\"},{\"id\":618018738,\"identity\":\"c802cb24-e2a8-45e4-8644-88fe9a25b669\",\"order_by\":9,\"name\":\"Kamal Amer\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kamal\",\"middleName\":\"\",\"lastName\":\"Amer\",\"suffix\":\"\"},{\"id\":618018741,\"identity\":\"7f1dcd69-9b18-44bf-b66d-a270dd0951c7\",\"order_by\":10,\"name\":\"Lee Peng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hackensack Meridian Health Jersey Shore University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Lee\",\"middleName\":\"\",\"lastName\":\"Peng\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-03-02 17:53:45\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9012817/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9012817/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":106724985,\"identity\":\"2d39114a-1768-44eb-8615-550afd27134f\",\"added_by\":\"auto\",\"created_at\":\"2026-04-12 18:30:52\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":102272,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eStudy Flow Diagram of Cohort Selection from the National Inpatient Sample (2016–2019)\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9012817/v1/5d6417367a2af4b49f2e6059.png\"},{\"id\":106534111,\"identity\":\"179402bd-df45-45fd-93e7-7602cbb19e38\",\"added_by\":\"auto\",\"created_at\":\"2026-04-09 15:01:55\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":197063,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMultivariable-Adjusted Odds of In-Hospital Mortality and Procedural Utilization by Sex and Race\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9012817/v1/c78d0729f4b9be9c7801e87e.png\"},{\"id\":108805282,\"identity\":\"d81259c6-e470-4b9b-9f82-3b15708ad81a\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:25:27\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":648315,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9012817/v1/4c25038b-dbbb-4f8c-b30b-24e60bacbf82.pdf\"},{\"id\":106534113,\"identity\":\"bfe152ea-b630-4d8c-9adc-874c6f06329d\",\"added_by\":\"auto\",\"created_at\":\"2026-04-09 15:01:56\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":17209,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryTables.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9012817/v1/d042ac3dfc3e1f6c51935ce4.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Disparities in Outcomes of Alcohol-Associated Cirrhosis: Increased Mortality and Procedural Burden in a Nationwide Study\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eLiver cirrhosis accounts for approximately 1.16\\u0026nbsp;million deaths annually [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Between 2008 and 2014, the financial burden of liver cirrhosis-related hospitalizations in the United States increased by 30.2% to \\u003cspan\\u003e$\\u003c/span\\u003e7.37\\u0026nbsp;billion. Patients with cirrhosis also experience longer hospital stays, reflecting the complexity of the disease and the management required [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. There is a serious stigma issue and awareness gap surrounding cirrhosis, which results in underdiagnosis and diminished opportunities for early management. Public knowledge of cirrhosis is still poor, and only one in three individuals with the condition are aware of their diagnosis [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAmong the various etiologies for liver cirrhosis, alcohol associated cirrhosis (AAC) is responsible for almost 60% of all cirrhosis patients in Europe, North America, and Latin America [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Patients with AAC experience worse clinical outcomes than those with cirrhosis from other causes, including having higher short-term mortality and a greater likelihood of readmission [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. Admissions related to AAC had significantly increased rates of intensive care utilization and advanced procedures, such as endoscopic interventions for variceal bleeding and transjugular intrahepatic portosystemic shunt (TIPS) placement, compared to the cirrhosis of other causes [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eDespite the rapidly increasing burden of AAC, there is a paucity of national data comparing inpatient outcomes, resource utilizations, and disparities between AAC and other causes of cirrhosis (OC). While prior studies have described outcomes and disparities among patients with cirrhosis, few have directly compared AAC with OC, and etiology-specific differences in care delivery remain poorly characterized. We use the National Inpatient Sample (NIS) from 2016 to 2019 to compare in-hospital outcomes and resource utilization between patients admitted with AAC and OC. Improved characterization of etiology-specific outcomes may help inform targeted clinical strategies and health system planning for this growing population.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData Availability and Data Source\\u003c/h2\\u003e \\u003cp\\u003eWe conducted a retrospective cohort study utilizing data from the National Inpatient Sample (NIS), a component of the Healthcare Cost and Utilization Project (HCUP), for the years 2016 to 2019. The NIS is the largest publicly available all-payer inpatient healthcare database in the United States, encompassing approximately 20% of all discharges from U.S. community hospitals. The database includes de-identified patient information such as demographics, hospital characteristics, primary and secondary diagnoses and procedures, discharge status, length of stay, and total hospital charges. Sampling weights were applied to produce national estimates in accordance with HCUP methodology.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eStudy Population\\u003c/h3\\u003e\\n\\u003cp\\u003eAdult patients (aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;18 years) hospitalized with complications of cirrhosis were identified using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes. Patients were stratified based on the etiology of cirrhosis into two groups: alcohol-associated cirrhosis and cirrhosis due to other causes. Patients with missing demographic information or transferred to other facilities were excluded from the analysis. The full list of diagnostic codes used is provided in \\u003cb\\u003eSupplementary Tables\\u0026nbsp;1 and 2\\u003c/b\\u003e.\\u003c/p\\u003e\\n\\u003ch3\\u003eHospital and Patient Characteristics\\u003c/h3\\u003e\\n\\u003cp\\u003eBaseline patient characteristics included demographic, clinical, and hospital-level variables available within the National Inpatient Sample (NIS). Patient-level variables included age (analyzed as a continuous variable), sex (male or female), race/ethnicity (Non-Hispanic White, Black, Hispanic, Asian or Pacific Islander, Native American, and Other), and primary payer (Medicare, Medicaid, private/commercial insurance, and others, including self-pay). Comorbidity burden was assessed using the Elixhauser Comorbidity Index and modeled as a continuous variable in multivariable analyses.\\u003c/p\\u003e \\u003cp\\u003eHospital-level characteristics included hospital region (Northeast, Midwest, South, and West), hospital location (urban vs rural), teaching status (teaching vs non-teaching), and bed size (small, medium, large), as defined by HCUP. These variables were incorporated into adjusted models to account for potential confounding related to institutional characteristics. All baseline characteristics were compared between hospitalizations for alcohol-associated cirrhosis and cirrhosis due to other etiologies using survey-adjusted statistical methods.\\u003c/p\\u003e\\n\\u003ch3\\u003eOutcomes\\u003c/h3\\u003e\\n\\u003cp\\u003eThe primary outcomes were all-cause in-hospital mortality, length of stay (LOS), and total hospitalization costs. In-hospital mortality was defined as death during the index hospitalization. LOS was measured in days. Hospitalization costs were calculated using HCUP cost-to-charge ratios applied to total hospital charges. Secondary outcomes included inpatient procedural utilization, identified using ICD-10-PCS codes, including upper gastrointestinal endoscopy (EGD), endoscopic variceal interventions, transjugular intrahepatic portosystemic shunt (TIPS) placement, hemodialysis, liver transplantation, and blood product transfusions. Procedural outcomes were analyzed as binary variables. A secondary analysis evaluated racial and sex-based disparities in mortality and access to advanced procedures among patients with alcohol-associated cirrhosis.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical Analysis\\u003c/h2\\u003e \\u003cp\\u003eAll analyses incorporated survey design elements, including discharge weights, to yield nationally representative estimates and adjust for clustering at the hospital level. Descriptive statistics were presented as weighted means (with standard errors) for continuous variables and weighted frequencies (with percentages) for categorical variables. Univariate comparisons were made using survey-adjusted t-tests for continuous variables and Rao-Scott χ\\u0026sup2; tests for categorical variables.\\u003c/p\\u003e \\u003cp\\u003eWe employed multivariate logistic regression to assess the association between cirrhosis etiology and in-hospital mortality and procedural utilization. LOS was modeled using Poisson regression, and hospitalization costs were analyzed using generalized linear modeling with a gamma distribution and log-link function. All models were adjusted for patient demographics (age, sex, race/ethnicity, payer status) and the Elixhauser Comorbidity Index.\\u003c/p\\u003e \\u003cp\\u003eIn a secondary analysis, we evaluated the presence of potential racial and gender disparities in in-hospital mortality and procedural utilization (EGD, TIPS, dialysis, and liver transplant) across the entire cohort. Statistical significance was defined as a two-sided P value\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05. All statistical analyses were performed using Stata/SE version 16.1 (StataCorp LLC, College Station, TX, USA).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003ePatients\\u003c/h2\\u003e\\n \\u003cp\\u003eWe identified a total of 1,428,425 hospitalizations for complications related to cirrhosis. Of these, 733,495 (51.4%) hospitalizations were attributed to AAC, while 694,930 (48.6%) were related to other etiologies of cirrhosis (Fig. \\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cp\\u003ePatients with AAC were significantly younger (mean age 55.8) and were more likely to be male (70%). Both groups were predominantly White. Patients with AAC were more frequently insured by Medicaid (34%) and less commonly covered by Medicare (32%) (Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eGeneral characteristics of the study cohort (ETOH vs other cirrhosis)\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eTotal hospitalizations\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOther Cirrhosis\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eETOH Cirrhosis\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eP value *\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e694,930\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e733,495\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAge, years - mean (SE)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e64.0 (0.05)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e55.8 (0.04)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e326,265 (47%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e218,500 (30%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRace/ethnicity, n (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNon-Hispanic White\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e451,640 (65%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e491,810 (67%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eBlack\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e77,250 (11%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e65,310 (8.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e113,225 (16%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e128,565 (18%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAsian\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e23,105 (3.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e9,340 (1.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNative American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e7,010 (1.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e17,305 (2.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e22,700 (3.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e21,165 (2.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePrimary payer, n (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eMedicare\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e404,235 (58%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e237,190 (32%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eMedicaid\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e121,840 (18%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e246,500 (34%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePrivate/commercial\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e124,610 (18%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e161,420 (22%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther (including self-pay)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e43,360 (6.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e87,160 (12%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eElixhauser comorbidity score - mean (SE)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e5.3 (0.01)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.5 (0.01)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eIn-hospital outcomes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eMortality, n (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e58,140 (8.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e65,810 (9.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eLength of stay in days (mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SE)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e6.8 (0.03)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.0 (0.03)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003ch3\\u003ePrimary outcomes\\u003c/h3\\u003e\\n\\u003cp\\u003eIn-hospital mortality was higher in AAC compared to OC (9.0% vs 8.4%; p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), and AAC remained independently associated with increased odds of in-hospital mortality after adjustment (aOR 1.13; 95% CI 1.10\\u0026ndash;1.16). Although mean length of stay and median hospitalization costs were slightly higher in unadjusted comparisons for AAC, adjusted models showed modestly lower length of stay and costs for AAC relative to OC (adjusted ratio 0.98 [95% CI 0.97\\u0026ndash;0.99] and 0.93 [95% CI 0.92\\u0026ndash;0.95], respectively) (Table \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003ePrimary Outcomes\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOther Cirrhosis\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eETOH Cirrhosis\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eAdjusted OR/RR *\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e95% CI\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003eP-value\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003en\\u0026thinsp;=\\u0026thinsp;694,930\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003en\\u0026thinsp;=\\u0026thinsp;733,495\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eIn-hospital Mortality\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e58,140 (8.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e65,810 (9.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.10, 1.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eLength of Stay - mean (SE)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e6.8 (0.03)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.0 (0.03)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.97, 0.99\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHospitalization cost (US\\u003cspan\\u003e$\\u003c/span\\u003e, 2019 **) - median (IQR)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e11,430 (6,779\\u0026thinsp;\\u0026minus;\\u0026thinsp;20,937)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e11,697 (6,939\\u0026thinsp;\\u0026minus;\\u0026thinsp;21,680)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.92, 0.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eResource utilization\\u003c/h2\\u003e\\n \\u003cp\\u003eCompared with other cirrhosis etiologies, patients with AAC were significantly more likely to undergo EGD(16% vs. 11%; adjusted OR 1.50, 95% CI 1.46\\u0026ndash;1.53, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) and variceal ligation or other endoscopic control of bleeding (11% vs. 8.2%; adjusted OR 1.30, 95% CI 1.27\\u0026ndash;1.34). AAC was also associated with increased utilization of TIPS (adjusted OR 1.19, 95% CI 1.10\\u0026ndash;1.28, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), red blood cell transfusions (adjusted OR 1.27, 95% CI 1.24\\u0026ndash;1.31, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), platelet transfusions, and fresh frozen plasma transfusions. Conversely, patients with ETOH cirrhosis were less likely to undergo hemodialysis (adjusted OR 0.47, 95% CI 0.46\\u0026ndash;0.49) or liver transplantation during hospitalization (adjusted OR 0.57, 95% CI 0.53\\u0026ndash;0.62,) (Table \\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eUtilization of Procedures\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eUpper Gastrointestinal Endoscopy (EGD)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOther Cirrhosis\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eETOH Cirrhosis\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eAdjusted OR *\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e95% CI\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003eP-value\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e73,960 (11%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e116,315 (16%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.5\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.46, 1.53\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVariceal Ligation or Other Control of bleeding\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e56,995 (8.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e84,005 (11%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.27, 1.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eInsertion of Sengstaken tube /esophageal tamponade\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e145 (\\u0026lt;\\u0026thinsp;0.1%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e340 (\\u0026lt;\\u0026thinsp;0.1%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.28, 3.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e0.003\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eTransjugular Intrahepatic Portosystemic shunt\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e7,950 (1.1%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e10,515 (1.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.10, 1.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHemodialysis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e80,585 (12%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e46,580 (6.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.46, 0.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eLiver Transplant\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e10,670 (1.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e8,270 (1.1%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.57\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.53, 0.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRed Blood Cell Transfusion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e93,165 (13%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e123,935 (17%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.24, 1.31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePlatelets Transfusion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e24,445 (3.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e35,125 (4.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.14, 1.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFresh Frozen Plasma Transfusion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e6,550 (0.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e11,825 (1.6%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e1.33, 1.55\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eRacial and gender disparities in care for AAH population\\u003c/h2\\u003e\\n \\u003cp\\u003eAmong patients hospitalized with AAC, female sex was independently associated with high in-hospital mortality after multivariable adjustment (aOR 1.08, 95% CI 1.04\\u0026ndash;1.12). Compared with White patients, Black (aOr 1.08, 95% CI 1.01\\u0026ndash;1.15) and Native American patients (aOR 1.17, 95% CI 1.03\\u0026ndash;1.32) had higher adjusted odds of in-hospital mortality, while Hispanic patients had lower adjusted odds (aOR 0.91, 95% CI 0.86\\u0026ndash;0.95).\\u003c/p\\u003e\\n \\u003cp\\u003eSignificant disparities in access to advanced inpatient procedures were also observed in the AAC cohort. Female patients had lower adjusted odds of TIPS (aOR 0.76, 95% CI 0.69\\u0026ndash;0.84) and liver transplantation (aOR 0.72, 95% CI 0.64\\u0026ndash;0.80). Black patients experienced markedly reduced odds of TIPS (aOR 0.54, 95% CI 0.44\\u0026ndash;0.67) and transplantation (aOR 0.57, 95% CI 0.44\\u0026ndash;0.75) compared with White patients. In contrast, racial and ethnic minority patients had substantially higher adjusted odds of hemodialysis, most pronounced among Black patients (aOR 2.02, 95% CI 1.88\\u0026ndash;2.17).\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eLiver cirrhosis is a major public health concern worldwide, with a rising global incidence of mortality compared to the past, and poses a burden to the healthcare system. AAC is a serious and potentially fatal condition resulting from long-term, excessive alcohol consumption. Among the reasons for cirrhosis, AAC is a dominant etiology that leads to major morbidity and mortality [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Our study shows that AAC is the most common cause of cirrhosis-related hospital admissions, a leading cause of in-hospital death when compared to other cirrhosis etiologies, and it significantly increases the need for resuscitation and procedure utilization. In addition, the study demonstrates a substantial discrepancy in outcomes of patients from different genders and ethnicities.\\u003c/p\\u003e\\n\\u003cp\\u003eOur study, which included a large sample size of 1,428,425 cirrhosis-related hospitalizations, demonstrated a statistically significant increase in in-hospital mortality among patients admitted with AAC compared to patients with OC (9.0% vs 8.4% OR 1.13, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Similar findings were reported in a cohort study of patients with a confirmed diagnosis of cirrhosis in 2609 patients at the Karolinska University Hospital in Sweden between 2004 and 2017. The study demonstrated that patients with AAC had the highest overall mortality rate [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. In contrast to this, a 2022 ICU study found no significant difference in ICU mortality rates between AAC and OC cohorts (10.2% vs 11.7%, p\\u0026thinsp;=\\u0026thinsp;0.40) although post-ICU in-hospital mortality was significantly higher in the alcohol-associated group (10.0% vs 6.5%, p\\u0026thinsp;=\\u0026thinsp;0.04) [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Moreover, a population-based research in Taiwan of 472 alcoholic and 4,313 non-alcoholic cirrhosis patients revealed that there was no difference in the two groups\\u0026apos; six-year survival rates [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Our large cohort study provides a more precise characterization of the differences between alcohol-associated cirrhosis compared with other etiologies. These findings may reflect a more severe and unstable clinical presentation at admission, superimposed on a chronic illness that is often left untreated because of non-compliance and a lack of resources [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e\\n\\u003cp\\u003eCompared with other etiologies, patients with AAC were significantly more likely to undergo upper gastrointestinal endoscopy (EGD) (16% vs 11% OR 1.5 p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), receive endoscopic interventions (11% vs 8% OR 1.3 p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), require TIPS placement (adjusted OR 1.19, 95% CI 1.10\\u0026ndash;1.28, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), and undergo resuscitation with blood products, whereas they were less likely to receive liver transplantation (adjusted OR 0.57, 95% CI 0.53\\u0026ndash;0.62, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). A study that analyzed 34,494 Veterans Affairs patients with end-stage liver disease, demonstrated a 70% reduction in the likelihood of receiving a transplant (HR 0.30) for patients with alcohol-related cirrhosis compared to those with HCV-related cirrhosis [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e] These findings highlight a concerning disparity whereby, despite AAC being a predominant etiology and being associated with substantial in-hospital mortality, affected patients are significantly less likely to undergo liver transplantation. It raises important concerns regarding potential barriers to transplant access and is suggested to be due to multifactorial reasons. Potential contributing factors include the traditional 6-month abstinence requirement, limited social and socioeconomic support, and a higher burden of medical and psychiatric comorbidities, all of which may adversely affect transplant eligibility and access in patients with AAC. A 2023 New England Journal of Medicine review noted that only a small percentage of possible ALD candidates are chosen to be placed on the waiting list using the present psychosocial evaluation-based selection criteria [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Furthermore, a review published in the World Journal of Gastroenterology in 2018 shows that although the survival rates following liver transplantation improve as with any other cause for transplant, AAC is stigmatized, which affects acceptance rates [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e].\\u003c/p\\u003e\\n\\u003cp\\u003eThe study comprehensively analysed and showed significant ethnic and gender disparities in outcomes and procedure utilization in the specific subgroup of AAC patients. Hispanic patients had a lower mortality risk than White patients, but Black, Asian or Pacific Islander, Native American, and Other race patients had higher rates of in-hospital mortality. Black patients had approximately twofold greater likelihood of obtaining hemodialysis (adjusted OR 2.86, 95% CI 2.75\\u0026ndash;2.99, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) compared to other minority racial groups and significantly decreased likelihood of receiving liver transplantation and TIPS (adjusted OR 0.42, 95% CI 0.35\\u0026ndash;0.49, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). In addition, the study demonstrates gender discrepancies; female AAC patients were independently associated with increased in-hospital mortality (adjusted OR 1.08, 95% CI 1.04\\u0026ndash;1.12, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) and a higher likelihood of undergoing upper gastrointestinal endoscopy (EGD). In contrast, female AAC patients had significantly lower odds of receiving transjugular intrahepatic portosystemic shunt (TIPS) placement (adjusted OR 0.76, 95% CI 0.69\\u0026ndash;0.84, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), hemodialysis (adjusted OR 0.86, 95% CI 0.81\\u0026ndash;0.90, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), and liver transplantation (adjusted OR 0.72, 95% CI 0.64\\u0026ndash;0.80, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Table \\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). A study by Nephew et al., which included all-cause cirrhosis, examined racial and ethnic disparities in the receipt of lifesaving procedures and mortality among hospitalized patients with decompensated cirrhosis, showed no significant racial or ethnic differences in the odds of receiving upper endoscopy for variceal hemorrhage. However, Black patients remained substantially less likely than White patients to undergo TIPS for variceal hemorrhage (OR 0.54, 95% CI 0.47\\u0026ndash;0.62) and ascites (OR 0.34, 95% CI 0.31\\u0026ndash;0.38). Black patients had lower odds of liver transplantation (OR 0.66, 95% CI 0.61\\u0026ndash;0.70), and Hispanic patients also had reduced odds (OR 0.74, 95% CI 0.70\\u0026ndash;0.78) compared to White patients [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e].\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eResults of multivariate regression models to evaluate for racial and gender bias for in-hospital mortality and procedures (for alcohol-associated cirrhosis population)\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eCharacteristic\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eAdjusted OR *\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e95% CI\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003ep-value\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eIn-hospital mortality\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.04, 1.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRace\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eWhite\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eBlack\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.01, 1.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.86, 0.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAsian or Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.94, 1.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.227\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNative American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.03, 1.32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.04, 1.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.008\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eUpper Gastrointestinal Endoscopy (EGD)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.04, 1.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRace\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eWhite\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eBlack\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.02, 1.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.007\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.98, 1.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.262\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAsian or Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.96, 1.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.214\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNative American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.93, 1.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.657\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.87, 1.04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.261\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eTransjugular Intrahepatic Portosystemic shunt\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.76\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.69, 0.84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRace\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eWhite\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eBlack\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.44, 0.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.82, 1.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.267\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAsian or Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.49, 1.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.178\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNative American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.76\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.55, 1.04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.083\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.78, 1.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.856\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHemodialysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.81, 0.90\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRace\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eWhite\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eBlack\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e2.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.88, 2.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.62, 1.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAsian or Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.56, 2.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNative American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.56, 2.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.65\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.44, 1.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eLiver Transplant\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.64, 0.80\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRace\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eWhite\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003eReference\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eBlack\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.57\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.44, 0.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHispanic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.80, 1.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.876\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAsian or Pacific Islander\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.57, 1.32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.508\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNative American\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.63\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.36, 1.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.097\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOther\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.97, 1.66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.088\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eStrengths\\u003c/h2\\u003e\\n \\u003cp\\u003eThis study leverages a large, nationally representative cohort of more than 1.4\\u0026nbsp;million cirrhosis-related hospitalizations, providing substantial statistical power to detect clinically meaningful differences between alcohol-associated and other etiologies while enabling comprehensive multivariable analyses. By directly comparing alcohol-associated cirrhosis with other causes within a unified analytic framework, we provide robust etiology-specific evaluation of mortality, procedural utilization, and resource use. Adjustment for demographic factors, comorbidity burden, and hospital characteristics strengthens the validity of the findings.\\u003c/p\\u003e\\n \\u003cp\\u003eThe stratified analysis by sex and race highlights significant disparities in mortality and access to advanced procedures, including EGD, TIPS, hemodialysis, and liver transplantation, offering granular insight into inequities that remain underexplored in national-level studies (Fig. \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eLimitations\\u003c/h2\\u003e\\n \\u003cp\\u003eThe study has several limitations. First, the study does not measure confounding variables that can affect the outcomes, such as socioeconomic status and access to liver transplant centers. In addition, adherence to follow-ups and participation in alcohol cessation programs data could add another layer to the stratification of AAC patients compared to the OC patients. Furthermore, it focused only on in-hospital outcomes, and data on readmissions, long-term survival, or post-discharge complications and outcomes was not evaluated. Those additional findings would provide a more comprehensive understanding of the clinical course and assist in creating further stratification and overall prognosis.\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eOur study demonstrates that, in comparison to other cirrhosis etiologies, AAC is the most frequent cause of in-hospital mortality, and it dramatically raises the need for resuscitation and procedure utilization. Although AAC has been one of the most dominant causes of healthcare resource burden, this population less frequently receives liver transplantation compared with other etiologies. There are discrepancies in patient outcomes based on gender and ethnicity. Further studies are required to expand the comparison between the AAC and OC patients and to address more factors that lead to the discrepancy, to provide better and equitable care in this population.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"624\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAAC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAlcohol-Associated Cirrhosis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOther Causes of Cirrhosis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNational Inpatient Sample\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eHCUP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eHealthcare Cost and Utilization Project\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eICD-10-CM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eInternational Classification of Diseases, Tenth Revision, Clinical Modification\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eICD-10-PCS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eInternational Classification of Diseases, Tenth Revision, Procedure Coding System\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eEGD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eEsophagogastroduodenoscopy\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eTIPS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eTrans-jugular Intrahepatic Portosystemic Shunt\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLOS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLength of Stay\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOdds Ratio\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eaOR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAdjusted Odds Ratio\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eConfidence Interval\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eRBC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eRed Blood Cell\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eFFP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eFresh Frozen Plasma\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eICU\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eIntensive Care Unit\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eHCV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eHepatitis C Virus\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eALD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAlcohol-Associated Liver Disease\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eEthics approval\\u0026nbsp;\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eThis study used the Nationwide Inpatient Sample (NIS), a publicly available, de-identified database. Institutional Review Board approval was not required in accordance with U.S. federal regulations (45 CFR 46).\\u003c/p\\u003e\\n\\u003col start=\\\"2\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eInformed consent was waived due to the use of anonymized data.\\u003c/p\\u003e\\n\\u003col start=\\\"3\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eAll data generated or analyzed during this study are included in the manuscript and its supplementary file.\\u003c/p\\u003e\\n\\u003col start=\\\"4\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eThe authors declare no conflicts of interest.\\u003c/p\\u003e\\n\\u003col start=\\\"5\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eNo specific funding was received by authors for this work.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003col start=\\\"6\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eIG and HS conceptualized the review. HS performed the statistical review. IG, and HS contributed to data analysis and data collection. \\u0026nbsp;IG, KK, and KM wrote the original draft. HS, CT, AH, MAH, AF and KAK contributed to literature review, writing, and editing. KA and MAH provided critical revisions and clinical expertise. LP, KA, and MAH supervised the project and reviewed the final manuscript. All authors read and approved the final version.\\u003c/p\\u003e\\n\\u003col start=\\\"7\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eNot applicable\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eAsrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. J Hepatol. 2019;70(1):151-171. doi:10.1016/j.jhep.2018.09.014.\\u003c/li\\u003e\\n \\u003cli\\u003eGin\\u0026egrave;s P, Krag A, Abraldes JG, Sol\\u0026agrave; E, Fabrellas N, Kamath PS. Liver cirrhosis. Lancet. 2021;398(10308):1359-1376. doi:10.1016/S0140-6736(21)01374-X.\\u003c/li\\u003e\\n \\u003cli\\u003eLiu YB, Chen MK. Epidemiology of liver cirrhosis and associated complications: Current knowledge and future directions. World J Gastroenterol. 2022;28(41):5910-5930. doi:10.3748/wjg.v28.i41.5910.\\u003c/li\\u003e\\n \\u003cli\\u003eSmith A, Baumgartner K, Bositis C. Cirrhosis: Diagnosis and management. Am Fam Physician. 2019;100(12):759-770.\\u003c/li\\u003e\\n \\u003cli\\u003eDevarbhavi H, Asrani SK, Arab JP, Nartey YA, Pose E, Kamath PS. Global burden of liver disease: 2023 update. J Hepatol. 2023;79(2):516-537. doi:10.1016/j.jhep.2023.03.017.\\u003c/li\\u003e\\n \\u003cli\\u003eChoi C, Choi DH, Spears GM, Peeraphatdit TB, Serafim LP, Gajic O, et al. Relationship between etiology of cirrhosis and survival among patients hospitalized in intensive care units. Mayo Clin Proc. 2022;97(2):274-284. doi:10.1016/j.mayocp.2021.08.025.\\u003c/li\\u003e\\n \\u003cli\\u003eLone NI, Lee R, Walsh TS. Long-term mortality and hospital resource use in ICU patients with alcohol-related liver disease. Crit Care Med. 2019;47(1):23-32. doi:10.1097/CCM.0000000000003421.\\u003c/li\\u003e\\n \\u003cli\\u003eHuang YF, Lin CS, Cherng YG, Yeh CC, Chen RJ, Chen TL, et al. A population-based cohort study of mortality of intensive care unit patients with liver cirrhosis. BMC Gastroenterol. 2020;20(1):15. doi:10.1186/s12876-020-1163-1.\\u003c/li\\u003e\\n \\u003cli\\u003eHuang DQ, Mathurin P, Cortez-Pinto H, Loomba R. Global epidemiology of alcohol-associated cirrhosis and HCC: trends, projections and risk factors. Nat Rev Gastroenterol Hepatol. 2023;20(1):37-49. doi:10.1038/s41575-022-00688-6.\\u003c/li\\u003e\\n \\u003cli\\u003eHagstr\\u0026ouml;m H, Lindfors A, Holmer M, Bengtsson B, Bj\\u0026ouml;rkstr\\u0026ouml;m K, Hegmar H, et al. Etiologies and outcomes of cirrhosis in a large contemporary cohort. Scand J Gastroenterol. 2021;56(6):727-732. doi:10.1080/00365521.2021.1912167.\\u003c/li\\u003e\\n \\u003cli\\u003eYang TW, Wang CC, Tsai MC, Wang YT, Tseng MH, Lin CC. Comorbidities and outcome of alcoholic and non-alcoholic liver cirrhosis in Taiwan: A population-based study. Int J Environ Res Public Health. 2020;17(8):2825. doi:10.3390/ijerph17082825.\\u003c/li\\u003e\\n \\u003cli\\u003eJophlin LL, Singal AK, Bataller R, Wong RJ, Sauer BG, Terrault NA, et al. ACG clinical guideline: Alcohol-associated liver disease. Am J Gastroenterol. 2024;119(1):30-54. doi:10.14309/ajg.0000000000002572.\\u003c/li\\u003e\\n \\u003cli\\u003eMarot A, Henrion J, Knebel JF, Moreno C, Deltenre P. Alcoholic liver disease confers a worse prognosis than HCV infection and non-alcoholic fatty liver disease among patients with cirrhosis: An observational study. PLoS One. 2017;12(10):e0186715. doi:10.1371/journal.pone.0186715.\\u003c/li\\u003e\\n \\u003cli\\u003eKanwal F, Hernaez R, Liu Y, Taylor TJ, Rana A, Kramer JR, et al. Factors associated with access to and receipt of liver transplantation in veterans with end-stage liver disease. JAMA Intern Med. 2021;181(7):949-959. doi:10.1001/jamainternmed.2021.2051.\\u003c/li\\u003e\\n \\u003cli\\u003eLucey MR, Furuya KN, Foley DP. Liver transplantation. N Engl J Med. 2023;389(20):1888-1900. doi:10.1056/NEJMra2200923.\\u003c/li\\u003e\\n \\u003cli\\u003eMarroni CA, Fleck AM Jr, Fernandes SA, Galant LH, Mucenic M, de Mattos Meine MH, et al. Liver transplantation and alcoholic liver disease: History, controversies, and considerations. World J Gastroenterol. 2018;24(26):2785-2805. doi:10.3748/wjg.v24.i26.2785.\\u003c/li\\u003e\\n \\u003cli\\u003eNephew LD, Knapp SM, Mohamed KA, Ghabril M, Orman E, Patidar KR, et al. Trends in racial and ethnic disparities in the receipt of lifesaving procedures for hospitalized patients with decompensated cirrhosis in the US, 2009-2018. JAMA Netw Open. 2023;6(7):e2324539. doi:10.1001/jamanetworkopen.2023.24539.\\u003c/li\\u003e\\n\\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\":\"info@researchsquare.com\",\"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\":\"Alcohol-associated cirrhosis, National Inpatient Sample (NIS), Liver transplantation, outcomes.\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9012817/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9012817/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cb\\u003eBackground:\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003eAlcohol-associated cirrhosis is a leading cause of liver-related hospitalizations and mortality globally. Despite its prevalence, the determinants of clinical outcomes, procedural utilization, and disparities by race and gender remain incompletely characterized. This study aimed to compare in-hospital outcomes and resource utilization between patients with alcohol-associated cirrhosis and those with cirrhosis from other etiologies.\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eMethods:\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003eWe conducted a retrospective cohort study using the National Inpatient Sample (NIS) from 2016 to 2019. Adult hospitalizations with cirrhosis were stratified by etiology (alcohol-associated vs. other). Primary outcomes included in-hospital mortality, length of stay, and hospitalization costs. Secondary outcomes included utilization of upper gastrointestinal endoscopy (EGD), variceal interventions, transjugular intrahepatic portosystemic shunt (TIPS), hemodialysis, liver transplantation, and blood product transfusions. Multivariable logistic and Poisson regression models were used to assess associations, adjusting for demographics, comorbidities, and hospital characteristics.\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eResults:\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003eAmong 1,428,425 cirrhosis-related hospitalizations, 733,495 (51.4%) were alcohol-associated. Patients with alcohol-associated cirrhosis were younger (mean age 55.8 vs. 64.0 years), more likely to be male, and had higher Medicaid coverage. In-hospital mortality was higher in alcohol-associated cirrhosis (9.0% vs. 8.4%; adjusted OR 1.13, 95% CI 1.10\\u0026ndash;1.16, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). These patients underwent more EGD (16% vs. 11%; OR 1.50), variceal interventions (11% vs. 8.2%; OR 1.30), TIPS (1.4% vs. 1.1%; OR 1.19), and blood transfusions (17% vs. 13%; OR 1.27), but had lower odds of liver transplantation (1.1% vs. 1.5%; OR 0.57). Female sex and minority race were independently associated with disparities in mortality and procedural utilization, with pronounced effects among alcohol-associated cirrhosis patients.\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eConclusion:\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003eAlcohol-associated cirrhosis is the most common cause of cirrhosis-related hospitalizations and in-hospital mortality and is associated with a higher procedural burden. Notable racial and gender disparities exist in both outcomes and access to advanced procedures. These findings highlight the need for targeted strategies to improve equity and optimize care in patients with alcohol-related cirrhosis.\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eTrial Registration:\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003eNot applicable. This study is a retrospective analysis of a publicly available, de-identified administrative database and does not involve a prospective healthcare intervention.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Disparities in Outcomes of Alcohol-Associated Cirrhosis: Increased Mortality and Procedural Burden in a Nationwide Study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-04-09 15:01:51\",\"doi\":\"10.21203/rs.3.rs-9012817/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"31daf749-6ac1-4097-93a8-387f3e585ed1\",\"owner\":[],\"postedDate\":\"April 9th, 2026\",\"published\":true,\"recentEditorialEvents\":[{\"type\":\"decision\",\"content\":\"Withdrawn\",\"date\":\"2026-05-06T15:42:11+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-06T15:56:10+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-04-09 15:01:51\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9012817\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9012817\",\"identity\":\"rs-9012817\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}