Racial Disparities in Alcoholic Hepatitis Hospitalizations in the United States: Trends, Outcomes, and Future Projections

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Our study aims to analyze the morbidity and mortality of AH across racial groups and project hospitalization trends up to 2028, thereby informing public health initiatives. Methods: We conducted a cross-sectional study utilizing data from the Nationwide Inpatient Sample (NIS) spanning 2012 to 2021. The study population comprised hospitalizations identified using specific ICD-9-CM and ICD-10-CM codes for AH. We assessed hospitalizations, in-hospital mortality rates, length of stay (LOS), and morbidities related to alcoholic hepatitis adjusting for sociodemographic factors and hospital characteristics. Statistical analyses were performed using Stata and R software, employing logistic and linear regression analyses, and SARIMA models for forecasting. Results: Our results indicated a predominantly White cohort (68%), with a notable increase in AH hospitalizations among Hispanics (129.1% from 2012 to 2021). Racial disparities were observed in inpatient mortality, liver transplant accessibility, and the occurrence of in-hospital complications. The study forecasts a continued rise in hospitalizations across all racial groups, with Hispanics experiencing the sharpest increase. Conclusion: Our study reveals a disproportionate rise in the AH burden among Hispanics with projections indicating a persistent upward trend through 2028. These findings highlight the need for targeted public health strategies and improved healthcare access to mitigate the increasing AH burden and address disparities in care and outcomes. Alcoholic Hepatitis Racial Disparities HCUP-NIS Liver Disease Figures Figure 1 Figure 2 Figure 3 Introduction Alcoholic liver disease encompasses a spectrum of liver injuries due to alcohol use, ranging from steatosis and hepatitis to cirrhosis. This spectrum is marked by various pathophysiological changes in the liver, including fatty liver, inflammation, and fibrosis, and leading to cirrhosis (1). Alcoholic hepatitis (AH) is an acute, inflammation-driven condition that emerges as a complication of alcohol consumption and is associated with high morbidity and mortality globally. In severe cases, AH can have a 30-day mortality rate of 17 to 50% (2). In the United States, excessive alcohol consumption ranks as the third leading cause of preventable death. Surveys indicate that 68% of American adults consume alcohol monthly, with 10% classified as heavy drinkers (3,4). AH’s incidence is challenging to determine due to asymptomatic cases, but studies suggest a prevalence of 20–35% among alcohol consumers. With an estimated 8% of Americans suffering from alcoholism, this translates to approximately 26.6 million individuals at risk for AH, potentially resulting in 5.3–9.3 million AH cases (4). The management of AH remains a significant medical challenge, with steroids as the primary treatment. However, these treatments do not substantially reduce the long-term mortality rates (5–7). The risk of developing AH varies with the amount and duration of alcohol consumption, indicating the interplay of environmental, genetic, and sociodemographic factors in the disease development (7). Despite recent efforts to equalize healthcare access across racial and ethnic groups for chronic liver disease, the impact of these efforts on AH remains to be examined (8,9). Therefore, our study aims to analyze the mortality and morbidity of AH across racial groups and employ forecasting methods to project hospitalization trends up to 2028. This will aid in devising public health initiatives to address the escalating burden of AH. Methods Design This cross-sectional study analyzed data from the Nationwide Inpatient Sample (NIS) spanning from 2012 to 2021. The NIS, part of the Healthcare Cost and Utilization Project (HCUP), is a collaborative initiative between the Federal government and the healthcare industry, sponsored by the Agency for Healthcare Research and Quality (AHRQ). It provides discharge-level information on diagnoses, procedures, and demographics. Our primary unit of analysis was hospital discharge records. Study population The study sample comprised hospitalizations identified using specific ICD-9-CM and ICD-10-CM codes for AH, validated in previous studies (10,11). Using the NIS database, we assessed several outcomes: a) the number of hospitalizations from 2012 to 2021, b) in-hospital mortality rates, c) length of stay (LOS), and d) in-hospital complications related to AH. The main independent variable was race/ethnicity, categorized as non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic. Covariates included sociodemographic factors (age, gender, insurance status, income levels) and hospital characteristics (bed sizes, medical comorbidity). The ethical considerations were adhered to, with the study receiving a waiver from the John H. Stroger Hospital ethics committee due to the use of publicly available and de-identified data. Statistical analysis Stata statistical software package (version 17.0, Stata Corp LP, College Station, TX), and R studio software (version 2023.30, Vienna, Austria) were used for statistical analysis. All statistical tests account for the complex survey methodology and were 2-sided with a P value of < 0.05 chosen as the level of significance. Continuous variables were presented with mean and compared with the student t-test and categorical variables were presented with percentages and compared with the Chi-square test. Temporal trends in the number of hospitalizations for AH were assessed by calculating the annual percentage change (APC), and average annual percentage change (AAPC) using a generalized linear model. Jointpoint regression was employed to detect statical inflection points using the grid search method. For assessing the independent relationship between race/ ethnicity and mortality, we employed multivariable logistic regression analysis, presenting odds ratios and 95% confidence intervals. Additionally, we used multivariable linear analyses (to examine the relationship between race/ethnicity and LOS. We also displayed the regression coefficient and its corresponding 95% confidence interval. Hospitalization numbers were calculated as “Hospitalization Density”, using U.S Census Bureau data to standardize the population to the calculated years, and reported as per 100,000 persons-year. The change in hospitalization is also presented. Annual changes in hospitalization rates were calculated as percent changes in the number of hospitalizations using 2012 as the reference year of each race/ethnicity. The future projections for AH to the year 2028 were forecasted using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. This model encompasses both trend and seasonality in time series data. Monthly data between January 2012 and December 2021 were used as a training dataset to develop the forecasting model to predict the monthly count of AH hospitalizations from January 2022 to December 2028. Results The study cohort was predominantly White (68%), with the remainder of the cohort composed of Blacks (10%) and Hispanics (12%). The mean age of the participants was similar across the White (48.6 years) and Black cohorts (49.6 years), but slightly lower in the Hispanic cohort (44.8 years). (Table 1 ) Males constituted the majority in all racial groups, comprising 64.8% of the White cohort, 66.3% of the Black cohort, and 79.8% of the Hispanic cohort. Insurance coverage varied notably across the groups. Medicare was the primary insurer for 18.0% of White patients, 20.9% of Black patients, and 10.7% of Hispanic patients. Medicaid coverage was more prevalent among Blacks (45.9%) and Hispanics (51.3%) than Whites (35.7%). Private insurance was held by 31.3% of Whites, 18.1% of Blacks, and 16.8% of Hispanics. A significant proportion of each group was non-insured, with 15.0% in Whites, 15.2% in Blacks, and a higher rate of 21.2% in Hispanics. Income distribution showed that the lowest median household income bracket contained 22.2% of Whites, a striking contrast to 52.8% of Blacks and 34.4% of Hispanics. Conversely, the highest income bracket included 24.4% of Whites, 10.4% of Blacks, and 15.9% of Hispanics, findings included in Table 1 . Regarding hospital characteristics, the cohort was distributed across various bed sizes, with 49.1% of NHW, 50.2% of NHB, and 51.5% of Hispanics treated in large hospitals. The hospital region also varied, with 43.3% of Blacks treated in the South region, significantly higher than Whites (31.4%) and Hispanics (23.7%). The hospital location and teaching status indicated that a large majority of NHB (77.3%) and Hispanics (74.8%) were treated in urban teaching hospitals, compared to 64.2% of NHW. Comorbidities were prevalent across the cohort with hypertension being the most common, particularly among Blacks (49.7%) compared to Whites (39.8%) and Hispanics (30.9%). Chronic kidney disease (CKD) and congestive heart failure (CHF) were also more prevalent in the Black cohort (8.5% and 9.1%, respectively) than in Whites (4.4% and 5.3%, respectively) and Hispanics (4.9% and 3.7%, respectively). Temporal Trend and Projection: During the study period, the hospitalization density of alcoholic hepatitis increased at varied rates between racial groups (Fig. 1 ). The AH hospitalization density in non-Hispanic whites increased from 25 per 100,000 person-years in 2012 to 42 per 100,000 person-years in 2021, presenting an AAPC of 6.83%, in non-Hispanic blacks increased from 23 per 100,000 person-years in 2012 to 38 per 100,000 person-years in 2021, with an AAPC of 7.22%, and in Hispanics, it increased from 18 per 100,000 person-years in 2012 to 35 per 100,000 person-years in 2021, with an overall AAPC of 9.30%. On the evaluation of the trend segment, in Hispanics, we noted two jointpoint changes, with a much steeper rise between 2014–2021 of APC 10.76% (95CI: 9.59 to 14.33). Trend segment analysis also revealed a significant rise in the NHB population with a steeper rise in hospitalization density during 2019–2021 with an APC of 13.63% (95CI: 6.55 to 18.34) ( Table S1 ). When evaluating the annual number of hospitalizations using the starting study year 2012 as a reference, the cumulative percentage change in the number of hospitalizations increased the most in Hispanics (129.1%), followed by non-Hispanic Black (78.2%), and then non-Hispanics White (70.5%) (Fig. 2 ). In our forecast model, the number of hospitalizations is expected to continue to rise in all racial groups (Fig. 3 ), in non-Hispanic whites it is expected to increase from 104,895 in 2021, to a forecasted 116,840, with an AAPC of 1.40%. Contrastingly, Hispanic groups are expected to have a more rapid rise in the number of alcoholic hepatitis hospitalizations from 21,790 in 2021 to 36,124 cases in 2028, with an average of 7.44% increase annually (Fig. 3 and Table S2 ). Primary Outcome: Mortality There were 28,240 (4.2%) deaths among NHW and 4,840 (4.2%) deaths among Hispanics, followed by 3,720 deaths (3.6%) among NHB (Table 2 ). The adjusted model showed significantly lower in-patient mortality for NHB (adjusted odds ratio (aOR] 0.73; 95% CI: 0.68–0.79) compared to NHW (Table 3 ) . No significant difference in in-patient mortality was observed for Hispanics compared to NHW. Other predictors for inpatient mortality included increasing age (aOR: 1.03; 95%CI:1.03–1.04, P < 0.05) and comorbidities including chronic kidney disease (aOR: 1.82, 95%CI:1.68–1.98, P < 0.05) and congestive heart failure (aOR: 1.35; 95%CI: 1.24–1.48; P < 0.05). Secondary Outcome: During the study period, there were 1,535 liver transplants performed. The proportion of liver transplant recipients among AH hospitalization was highest among non-Hispanic Whites (NHW) at 0.2%, followed by Hispanics at 0.13%, and non-Hispanic Blacks (NHB) at 0.1%. On adjusted analysis, NHB had lower odds of receiving a liver transplant (aOR: 0.50; 95%CI: 0.30–0.83; P < 0.05) compared to NHW ( Table 2 ) . No significant differences were observed between Hispanics and NHW. The LOS was similar for NHW (6.2) and Hispanic patients (6.1), which was longer than for NHB patients (6.0), and an additional multivariate analysis of factor-affected LOS is listed in Table S3 . Hispanic patients exhibited the highest in-hospital rates of sepsis (10.8%), ascites (6.3%), and variceal bleeding (25.8%). In the adjusted model, they were significantly more likely to experience sepsis (aOR: 1.24; 95%CI: 1.18–1.30; P < 0.001), ascites (aOR: 1.10; 95%CI: 1.10–1.14; P < 0.05), and variceal hemorrhage (aOR: 1.61; 95%CI: 1.51–1.72; P < 0.001) compared to NHW. NHB patients had the highest in-hospital rate of acute kidney injury (AKI) at 25.1%, followed by NHW (20.9%), and then Hispanics (20.4%). NHB had higher odds of AKI (aOR 1.1; 95%CI: 1.10–1.10, P < 0.01) compared to NHW. However, NHB patients had lower odds for ascites (aOR: 0.60; 95CI: 0.58–0.62; P < 0.05), variceal hemorrhage (aOR 0.72; 95%CI: 0.65–0.79; P < 0.05), and hepatic encephalopathy (aOR: 0.81; 95%CI: 0.77–0.85; P < 0.05) (Table 3 ) . Discussion This comprehensive analysis of a nationally representative cohort elucidates racial disparities in the burden of AH and projects an escalating future burden. Our observations indicate a marked escalation in AH hospitalizations, notably among Hispanics who experienced a 129.1% increase from 2012 to 2021. This increment substantially surpasses that of NHW at 70.5% and NHB at 78.2%, signaling a burgeoning future burden of AH, especially in this demographic group. In addition, we also observed a significant change in time-period trend in the NHBs population with rapidly rising APC during the period of the COVID-19 pandemic. Our study further delineates disparities in mortality rates and rate of liver transplants with NHBs exhibiting lower inpatient mortality yet facing reducing likelihood of liver transplants compared to NHWs. Insurance coverage disparities and comorbidity prevalence were also notable, with Hispanics facing the highest rates of in-hospital complications, such as sepsis and variceal hemorrhage, and NHBs presenting the highest incidence of acute kidney injury. Although prior research has shown a general rise in AH (10,12,13), our study uniquely highlights variations in the current racial burden and projects the future burden of AH for each race/ethnicity up to 2028. The disproportionately rising trend among Hispanics has been largely attributed to changing alcohol consumption habits, especially with a shift toward young adults between 15–39 years old (14). This underscores the need for focused public intervention, particularly among Hispanic communities, to mitigate the impending burden of AH. The COVID-19 pandemic has further exacerbated the problem (15) and has since widened this racial gap. Using 2019 as a pre-pandemic reference year compared to 2021, we observed that the relative percentage change in AH hospitalization increased most significantly among Hispanics (33.0%), followed by NHBs (28.3%) and then NHWs (13.9%). This short-term rise in AH burden among racial groups could result in increasing mortality, and disability-adjusted life-year loss, as modeled by Julien et el (16). Moreover, this increasing burden is augmented by the higher rates of morbidity they face while hospitalized. These findings align with previous research indicating greater in-hospital complications and healthcare service utilization for AH among Hispanics (17). Factors contributing to these disparities include inadequate insurance coverage and delays in seeking preventative services, leading to advanced-stage presentations and higher hospitalization and resource utilization rates (18). Our findings highlight two concerning trends among Hispanics: younger age at admission and the higher prevalence of in-hospital complications of manifestation of portal hypertension. National survey data from the United States have documented an alarming increase in per capita alcohol consumption, particularly among younger NHWs and Hispanics (19). Another factor contributing to this early onset could be genetic predispositions. Previously PNPLA3 gene has been demonstrated to increase the risk for alcohol-related liver disease (20,21), and heterogeneity in the expression of alcohol metabolizing enzyme allele among Hispanics could also play a role. The elevated rate of in-hospital complications from portal hypertension may also indicate poor outpatient management of chronic liver disease and insufficient environmental and medical support for this ethnic minority group. Preventative measures like regular endoscopic screenings and access to medications for varices prophylaxis and hepatic encephalopathy are crucial (22–24). These practices are particularly underutilized by those from lower socioeconomic backgrounds as well as individuals with co-existing psychiatric illnesses or substance abuse disorders (25). The mortality disparity in NHB observed in our study expands the body of knowledge on racial disparities in AH mortality. This aligns with the findings of May et el, suggesting that NHBs are more likely to present with milder forms of AH, as indicated by lower discriminant function scores (26). This could partially explain the observed difference in mortality rates. Moreover, variations in care patterns across racial groups could lead to inadequate treatment and premature discharges for NHB patients, potentially increasing mortality rates outside the hospital setting (27,28). Interestingly, our data also suggests lower rates of hepatorenal syndrome and variceal hemorrhage among NHBs, which may lessen contraindications for steroid use and offer a mortality benefit. However, Lei et el suggest increased mortality observed in moderate-drinking behavior secondary to liver diseases among NHBs, a pattern not observed in NHWs (29). The difference may stem from a complex interplay of genetic variations in alcohol metabolizing enzymes, and environmental factors, including metabolic syndrome and obesity, influenced by lifestyle and dietary patterns. Although our data does not clarify the severity of AH presentation among racial groups, it underscores the need for future research to understand the intricate relationships between metabolic syndrome, alcohol consumption levels, and social determinants such as BMI, diet, and insurance coverage, to better comprehend the racial disparities in AH mortality. Despite NHB patients showing lower inpatient mortality rates for AH, we noted a lower rate of liver transplants within this demographic. Our study supports previous findings from various transplant databases (30–32) and underscores disparities rooted in multifaceted factors. Firstly, there is a noted variation in the severity of alcohol-related liver injury and recovery among racial groups, with NHB individuals potentially experiencing milder AH compared to NHW (26). Patient-related barriers, such as limited healthcare access and financial limitations, contribute to lower rates of transplant referral rates (33,34). Furthermore, studies have indicated neighborhood income level independently affects the likelihood of being waitlisted for a transplant (35). Our study revealed that NHB patients predominantly reside in the lowest income quintile, therefore likely influencing their reduced rate of liver transplant. Provider-related barriers also play a role, with NHBs less likely to be referred for transplant listing and facing higher post-transplant mortality and morbidity (36–38). Systemic barriers, including insurance-related challenges, exacerbate these disparities (39). Although our analysis does not allow for a detailed analysis of these factors, we aim to shed light on the current inpatient disease landscape. Our goal is to encourage future efforts to explore the causes of these disparities and focus on addressing the inequities by improving healthcare access and tackling implicit bias among healthcare providers. Our study, which utilizes retrospective analysis of administrative data from the NIS, acknowledges several inherent limitations. One significant constraint is our reliance on ICD-9-CM and ICD-10-CM codes, which are susceptible to coding inaccuracies. This issue is particularly relevant as our study spans the year 2015, a transitional period from ICD-9-CM to ICD-10-CM, potentially impacting the precision of diagnostic codes. To mitigate this, we employed established codes from prior literature (10,11,17). Another limitation is the absence of laboratory data in the NIS, hindering our ability to assess disease severity. This is especially critical for AH where measures like the discriminant function score are vital. Furthermore, the NIS lacks detailed individual patient information, limiting our understanding of the temporality of events and precluding access to longitudinal data post-discharge. This could lead to an underestimation of the overall mortality rate observed in our study. Finally, the lack of granular patient details prevented an evaluation of factors such as social support and past substance use history, which are influential in the context of liver transplant reception. Despite these limitations, our study has significant merits that are worth noting. To our knowledge, this study provides the most current analysis of the racial and ethnic burden of AH in the United States, including future projections. The use of the NIS, a nationally representative database, is a key strength. It encompasses a diverse range of patients, hospital types, and geographic areas across the United States, offering a comprehensive view of the current inpatient epidemiological state of AH. This broad scope enhances the generalizability of our findings and underscores the study's substantial contribution to understanding AH's impact on a diverse population. In conclusion, this comprehensive analysis sheds light on the pronounced racial disparities in the burden of AH within the United States, notably escalating among Hispanics. This trend, significantly tied to increased alcohol consumption and subsequent healthcare expenditures, calls for urgent and targeted public health interventions. Our findings particularly highlight the younger average age at which Hispanics are admitted to the hospital and their higher incidence of in-hospital complications, including portal hypertension, pointing to the need for improved management strategies for chronic liver disease. Moving forward, it is needed to understand the influence of social determinants affect health outcomes. Future research should include diverse hospital settings and collection of disease severity details to provide a more thorough understanding of the issues, thereby adding to the reduction of health disparities highlighted by our study. Abbreviations AH Alcoholic Hepatitis NHW Non-Hispanic White NHB Non-Hispanic Black LOS Length of Stay ICD-9-CM International Classification of Diseases, Ninth Revision, Clinical Modification ICD-10-CM International Classification of Diseases, Tenth Revision, Clinical Modification APC Annual Percentage Change AAPC Average Annual Percentage Change SARIMA Seasonal Autoregressive Integrated Moving Average CKD Chronic Kidney Disease COPD Chronic Obstructive Pulmonary Disease CHF Congestive Heart Failure HLD Hyperlipidemia HTN Hypertension AKI Acute Kidney Injury Declarations Disclosures : None to declare. Data Availability Statement : The data used in this study are publicly available from Healthcare Cost and Utilization Project (HCUP Financial support : No funding support to disclose Patient Consent Statement : Not applicable. This study did not involve patients or require patient consent Specific author contributions: Study Concept and Design: C.P Acquisition, analysis, or interpretation of data for the work: C.P, D.G, V.K Drafting the work: C.P, V.K Supervise the work: V.K Revision of the work critically for important intellectual content: All authors Final approval of the version to be published: All authors References Hosseini N, Shor J, Szabo G. Alcoholic Hepatitis: A Review. Alcohol Alcohol Oxf Oxfs. 2019 Jul;54(4):408–16. Sehrawat TS, Liu M, Shah VH. The Knowns and Unknowns of Treatment for Alcoholic Hepatitis. Lancet Gastroenterol Hepatol. 2020 May;5(5):494–506. Shah NJ, Royer A, John S. Alcoholic Hepatitis. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 [cited 2024 Feb 21]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK470217/ Mathurin P, Duchatelle V, Ramond MJ, Degott C, Bedossa P, Erlinger S, et al. Survival and prognostic factors in patients with severe alcoholic hepatitis treated with prednisolone. Gastroenterology. 1996 Jun;110(6):1847–53. Thursz MR, Richardson P, Allison M, Austin A, Bowers M, Day CP, et al. Prednisolone or pentoxifylline for alcoholic hepatitis. N Engl J Med. 2015 Apr 23;372(17):1619–28. Penninti P, Adekunle AD, Singal AK. Alcoholic Hepatitis: The Rising Epidemic. Med Clin North Am. 2023 May;107(3):533–54. Lourens S, Sunjaya DB, Singal A, Liangpunsakul S, Puri P, Sanyal A, et al. Acute Alcoholic Hepatitis: Natural History and Predictors of Mortality Using a Multicenter Prospective Study. Mayo Clin Proc Innov Qual Outcomes. 2017 Jul;1(1):37–48. El-Serag HB, Kramer J, Duan Z, Kanwal F. Racial differences in the progression to cirrhosis and hepatocellular carcinoma in HCV-infected veterans. Am J Gastroenterol. 2014 Sep;109(9):1427–35. Nephew LD, Aitcheson G, Iyengar M. The Impact of Racial Disparities on Liver Disease Access and Outcomes. Curr Treat Options Gastroenterol. 2022 Sep 1;20(3):279–94. Shirazi F, Singal AK, Wong RJ. Alcohol-associated Cirrhosis and Alcoholic Hepatitis Hospitalization Trends in the United States. J Clin Gastroenterol. 2021 Feb;55(2):174–9. Ali H, Pamarthy R, Bolick NL, Farooq MF. Ten-year trends and prediction model of 30-day inpatient mortality for alcoholic hepatitis in the United States. Ann Gastroenterol. 2022;35(4):427–33. Anouti A, Mellinger JL. The Changing Epidemiology of Alcohol-Associated Liver Disease: Gender, Race, and Risk Factors. Semin Liver Dis. 2023 Feb;43(01):050–9. Doshi SD, Stotts MJ, Hubbard RA, Goldberg DS. The Changing Burden of Alcoholic Hepatitis: Rising Incidence and Associations with Age, Gender, Race, and Geography. Dig Dis Sci. 2021 May;66(5):1707–14. Doycheva I, Watt KD, Rifai G, Abou Mrad R, Lopez R, Zein NN, et al. Increasing Burden of Chronic Liver Disease Among Adolescents and Young Adults in the USA: A Silent Epidemic. Dig Dis Sci. 2017 May;62(5):1373–80. Barbosa C, Cowell AJ, Dowd WN. Alcohol Consumption in Response to the COVID-19 Pandemic in the United States. J Addict Med. 2021;15(4):341–4. Julien J, Ayer T, Tapper EB, Barbosa C, Dowd WN, Chhatwal J. Effect of increased alcohol consumption during COVID‐19 pandemic on alcohol‐associated liver disease: A modeling study. Hepatology. 2022 Jun;75(6):1480–90. May FP, Rolston VS, Tapper EB, Lakshmanan A, Saab S, Sundaram V. The impact of race and ethnicity on mortality and healthcare utilization in alcoholic hepatitis: a cross-sectional study. BMC Gastroenterol. 2016 Dec;16(1):129. phelan-et-al-2010-social-conditions-as-fundamental-causes-of-health-inequalities-theory-evidence-and-policy-implications.pdf. Grant BF, Chou SP, Saha TD, Pickering RP, Kerridge BT, Ruan WJ, et al. Prevalence of 12-Month Alcohol Use, High-Risk Drinking, and DSM-IV Alcohol Use Disorder in the United States, 2001-2002 to 2012-2013: Results From the National Epidemiologic Survey on Alcohol and Related Conditions. JAMA Psychiatry. 2017 Sep 1;74(9):911. Martínez LA, Larrieta E, Calva JJ, Kershenobich D, Torre A. The Expression of PNPLA3 Polymorphism could be the Key for Severe Liver Disease in NAFLD in Hispanic Population. Ann Hepatol. 2017 Nov 1;16(6):909–15. Tian C, Stokowski RP, Kershenobich D, Ballinger DG, Hinds DA. Variant in PNPLA3 is associated with alcoholic liver disease. Nat Genet. 2010 Jan;42(1):21–3. Robinson A, Tavakoli H, Liu B, Bhuket T, Cheung R, Wong RJ. African-Americans with Cirrhosis Are Less Likely to Receive Endoscopic Variceal Screening Within One Year of Cirrhosis Diagnosis. J Racial Ethn Health Disparities. 2018 Aug 1;5(4):860–6. Pinon-Gutierrez R, Durbin-Johnson B, Halsted CH, Medici V. Clinical features of alcoholic hepatitis in latinos and caucasians: A single center experience. World J Gastroenterol. 2017 Oct 28;23(40):7274–82. Tapper EB, Essien UR, Zhao Z, Ufere NN, Parikh ND. Racial and ethnic disparities in rifaximin use and subspecialty referrals for patients with hepatic encephalopathy in the United States. J Hepatol. 2022 Aug 1;77(2):377–82. Rogal S, Youk A, Zhang H, Gellad WF, Fine MJ, Good CB, et al. Impact of Alcohol Use Disorder Treatment on Clinical Outcomes among Patients with Cirrhosis. Hepatol Baltim Md. 2020 Jun;71(6):2080–92. Levy R, Catana AM, Durbin-Johnson B, Halsted CH, Medici V. Ethnic Differences in Presentation and Severity of Alcoholic Liver Disease. Alcohol Clin Exp Res. 2015 Mar;39(3):566–74. Volpp KG, Stone R, Lave JR, Jha AK, Pauly M, Klusaritz H, et al. Is Thirty-Day Hospital Mortality Really Lower for Black Veterans Compared with White Veterans? Health Serv Res. 2007 Aug;42(4):1613–31. Landon BE, Onnela JP, Meneades L, O’Malley AJ, Keating NL. Assessment of Racial Disparities in Primary Care Physician Specialty Referrals. JAMA Netw Open. 2021 Jan 25;4(1):e2029238. Fan L, Zhu X, Shingina A, Kabagambe EK, Shrubsole MJ, Dai Q. Racial Disparities in Associations of Alcohol Consumption With Liver Disease Mortality in a Predominantly Low-Income Population: A Report From the Southern Community Cohort Study. Am J Gastroenterol. 2022 Sep;117(9):1523–9. Bodek DD, Everwine MM, Lunsford KE, Okoronkwo N, Patel PA, Pyrsopoulos N. Racial Disparities in Liver Transplantation for Hepatocellular Carcinoma: Analysis of the National Inpatient Sample From 2007 to 2014. J Clin Gastroenterol. 2023 Mar;57(3):311. Cotter TG, Mitchell MC, Patel MJ, Anouti A, Lieber SR, Rich NE, et al. Racial and Ethnic Disparities in Liver Transplantation for Alcohol-associated Liver Diseases in the United States. Transplantation. 2024 Jan;108(1):225–34. Deutsch-Link S, Bittermann T, Nephew L, Ross-Driscoll K, Weinberg EM, Weinrieb RM, et al. Racial and ethnic disparities in psychosocial evaluation and liver transplant waitlisting. Am J Transplant. 2023 Jun 1;23(6):776–85. Kemmer N. Ethnic Disparities in Liver Transplantation. Gastroenterol Hepatol. 2011 May;7(5):302–7. Warren C, Carpenter AM, Neal D, Andreoni K, Sarosi G, Zarrinpar A. Racial Disparity in Liver Transplantation Listing. J Am Coll Surg. 2021 Apr;232(4):526–34. Mohamed KA, Ghabril M, Desai A, Orman E, Patidar KR, Holden J, et al. Neighborhood poverty is associated with failure to be waitlisted and death during liver transplantation evaluation. Liver Transpl. 2022 Sep;28(9):1441–53. Julapalli VR, Kramer JR, El-Serag HB. Evaluation for liver transplantation: Adherence to AASLD referral guidelines in a large veterans affairs center. Liver Transpl. 2005;11(11):1370–8. Eckhoff DE, McGuire BM, Young CJ, Sellers MT, Frenette LR, Hudson SL, et al. Race: a critical factor in organ donation, patient referral and selection, and orthotopic liver transplantation? Liver Transplant Surg Off Publ Am Assoc Study Liver Dis Int Liver Transplant Soc. 1998 Nov;4(6):499–505. Kamal SAF, Vikash S, Sohail H, Kilani Y, Vikash F. Racial disparities in the outcomes of liver transplantation in the treatment of hepatocellular carcinoma. J Clin Oncol. 2023 Jun;41(16_suppl):4131–4131. Wahid NA, Rosenblatt R, Brown RS. A Review of the Current State of Liver Transplantation Disparities. Liver Transpl. 2021 Mar;27(3):434–43. Tables Table 1. Demographics and characteristic of patient hospitalized with Alcoholic Hepatitis from 2012-2020 Parameter White 698,009 68% Black 104,695 10% Hispanics 120,115 12% Number (%) Number (%) Number (%) Mean age 48.6 (48.5-48.6) 49.6 (49.4-49.7) 44.8 (44.7-45) Male 519,990 64.8% 80,555 66.3% 113,295 79.8% Female 282,875 35.2% 40,990 33.7% 28,660 20.2% Insurance Medicare 125,140 18.0% 21,935 20.9% 13,195 10.7% Medicaid 248,615 35.7% 48,235 45.9% 63,265 51.3% Private 217,370 31.3% 19,020 18.1% 20,680 16.8% Non-insured 104,520 15.0% 15,930 15.2% 26,190 21.2% Median household income 0-25th 173,210 22.1% 62,640 52.8% 46,095 34.4% 26 th -50th 203,040 26.0% 25,030 21.1% 33,830 25.2% 51 st -75th 215,010 27.5% 18,510 15.6% 32,860 24.5% 75 th -100th 190,955 24.4% 12,370 10.4% 21,285 15.9% Hospital Bedsize Small 168,555 21.0% 24,705 20.3% 26,895 19.0% Medium 240,100 29.9% 35,840 29.5% 41,985 29.6% Large 394,305 49.1% 61,030 50.2% 73,080 51.5% Hospital Region Northeast 163,510 20.4% 24,555 20.2% 30,450 21.5% Midwest 198,975 24.8% 29,895 24.6% 13,345 9.4% South 252,140 31.4% 52,640 43.3% 33,660 23.7% West 188,335 23.5% 14,485 11.9% 64,505 45.4% Hospital location/teaching status Rural 63,495 7.9% 5,290 4.4% 3,620 2.6% Urban Non-teaching 223,795 27.9% 22,365 18.4% 32,220 22.7% Teaching 515,670 64.2% 93,920 77.3% 106,120 74.8% Comorbidities CKD 33,950 4.2% 9,845 8.1% 6,720 4.7% COPD 87,925 11.0% 10,870 8.9% 4,110 2.9% CHF 43,605 5.4% 11,195 9.2% 5,270 3.7% HLD 88,020 11.0% 14,320 11.8% 12,915 9.1% HTN 318,255 39.6% 59,730 49.1% 44,050 31.0% In-hospital Complication Sepsis 75,045 9.4% 11,985 9.9% 15,270 10.8% AKI 167,540 20.9% 30,565 25.1% 28,940 20.4% Ascites 34,100 4.3% 4,760 3.9% 8,945 6.3% Variceal hemorrhage 23,990 3.0% 2,685 2.1% 7,275 5.1% Hepatorenal syndrome 35,410 4.4% 3,550 2.9% 6,620 4.7% Hepatic encephalopathy 97,210 12.1% 13,110 10.8% 15,740 11.1% Red blood cell transfusion 61,645 7.7% 12,590 10.4% 15,625 11.0% Platelet transfusion 20,975 2.6% 3,185 2.6% 6,250 4.4% Number of procedures 0 45,305 13.1% 7,890 15.8% 9,085 13.8% 1 138,795 40.3% 18,685 37.4% 24,135 36.6% 2 60,455 17.5% 8,445 16.9% 12,325 18.7% >3 100,315 29.1% 14,920 29.9% 20,335 30.9% Table 2. Clinical Outcomes of Hospitalized Patients with Alcoholic Hepatitis Stratified by Race and Ethnicity Primary outcomes N/% Non-Hispanic White Non-Hispanic Black Hispanics P value Mortality 33,255 (4.2%) 4,330 (3.6%) 5,935 (4.2%) P <0.05 Liver transplant 1,255 (0.2%) 95 (0.1%) 185 (0.13%) P 0.014 Length of Stay (Days) 6.2 (6.1 to 6.2) 6 (5.9 to 6.1) 6.1 (6 to 6.2) P <0.05 Table 3. Multivariate analysis of Alcoholic Hepatitis hospitalization In-hospital Complication between Racial/Ethnic groups between 2012 to 2020, reference group to Non-Hispanic White Non-Hispanic Black Hispanic Primary Outcome Crude OR aOR Crude OR aOR Mortality 0.85 (0.79 to 0.92) 0.73 (0.68 to 0.79) 1.01 (0.95 to 1.08) 1.06 (0.99 to 1.14) Secondary Outcomes: Liver transplant 0.5 (0.31 to 0.8) 0.5 (0.3 to 0.83) 0.83 (0.57 to 1.21) 0.77 (0.52 to 1.12) Acute kidney injury 1.27 (1.23 to 1.32) 1.1 (1.1 to 1.1) 0.97 (0.94 to 1) 0.98 (0.95 to 1.02) Hepatorenal syndrome 0.65 (0.6 to 0.71) 0.53 (0.49 to 0.58) 1.06 (1 to 1.13) 1.03 (0.96 to 1.1) Ascites 0.65 (0.62 to 0.67) 0.6 (0.58 to 0.62) 1.06 (1.03 to 1.1) 1.1 (1.06 to 1.14) Hepatic Encephalopathy 0.88 (0.84 to 0.92) 0.81 (0.77 to 0.85) 0.91 (0.87 to 0.95) 0.96 (0.91 to 1) Sepsis 1.06 (1.01 to 1.11) 0.99 (0.94 to 1.04) 1.17 (1.12 to 1.22) 1.24 (1.18 to 1.3) Variceal Hemorrhage 0.73 (0.67 to 0.8) 0.72 (0.65 to 0.79) 1.75 (1.65 to 1.87) 1.61 (1.51 to 1.72) *Odd Ratio are calculated compared to Non-Hispanic White as reference group, Multivariate model are adjusted to gender, age, hospital characteristics. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable.docx Cite Share Download PDF Status: Published Journal Publication published 28 May, 2024 Read the published version in Digestive Diseases and Sciences → Version 1 posted Editorial decision: Revision requested 12 Apr, 2024 Reviews received at journal 08 Apr, 2024 Reviewers agreed at journal 25 Mar, 2024 Reviewers invited by journal 23 Mar, 2024 Editor assigned by journal 22 Mar, 2024 Submission checks completed at journal 22 Mar, 2024 First submitted to journal 20 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4138145","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283736458,"identity":"d430d4ab-2a87-4139-8119-e57e802fe08f","order_by":0,"name":"Chun-Wei Pan","email":"data:image/png;base64,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","orcid":"","institution":"John H. Stroger, Jr. Hospital of Cook County","correspondingAuthor":true,"prefix":"","firstName":"Chun-Wei","middleName":"","lastName":"Pan","suffix":""},{"id":283736459,"identity":"ddcc9d0b-df26-4506-923f-52537e1af316","order_by":1,"name":"Daniel Guifarro","email":"","orcid":"","institution":"John H. Stroger, Jr. Hospital of Cook County","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Guifarro","suffix":""},{"id":283736460,"identity":"9db6b9b7-b50c-4776-b57f-df5bf4c0d11e","order_by":2,"name":"Ayusha Poudel","email":"","orcid":"","institution":"John H. Stroger, Jr. Hospital of Cook County","correspondingAuthor":false,"prefix":"","firstName":"Ayusha","middleName":"","lastName":"Poudel","suffix":""},{"id":283736461,"identity":"f175d01c-b1cb-45f5-a62e-487dadca6618","order_by":3,"name":"Yazan Abboud","email":"","orcid":"","institution":"Rutgers New Jersey Medical School, Newark, NJ, USA","correspondingAuthor":false,"prefix":"","firstName":"Yazan","middleName":"","lastName":"Abboud","suffix":""},{"id":283736462,"identity":"7309e731-2350-487e-8cad-aa2a5b1ae13c","order_by":4,"name":"Vikram Kotwal","email":"","orcid":"","institution":"John H. Stroger, Jr. Hospital of Cook County","correspondingAuthor":false,"prefix":"","firstName":"Vikram","middleName":"","lastName":"Kotwal","suffix":""}],"badges":[],"createdAt":"2024-03-20 15:12:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4138145/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4138145/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10620-024-08462-1","type":"published","date":"2024-05-29T00:54:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53461760,"identity":"98cc120a-5e40-47f7-bff0-df598536e3d1","added_by":"auto","created_at":"2024-03-26 09:20:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":223948,"visible":true,"origin":"","legend":"\u003cp\u003eTotal Hospitalization with Alcoholic Hepatitis between 2012 and 2021, Stratified by Race and Ethnicity\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4138145/v1/78d878d5d530d773d8f38da9.jpeg"},{"id":53461762,"identity":"6463e5f8-277d-43a8-963a-ed70e88c6f65","added_by":"auto","created_at":"2024-03-26 09:20:43","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":191113,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative Changes (%) in Alcoholic Hepatitis hospitalization stratified by Race and Ethnicity. All calculation is based on using year 2012 as reference year.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4138145/v1/2a143b3da8535b37a8701596.jpeg"},{"id":53462256,"identity":"fa83d3d1-e33d-409b-833a-6991b9a8d26f","added_by":"auto","created_at":"2024-03-26 09:28:43","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":535150,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of Monthly Hospitalization of Alcoholic Hepatitis stratified by Race and Ethnicity between 2012-2021, with projection until 2028 December, (A) \u003cstrong\u003eNon-Hispanic White\u003c/strong\u003e, (B\u003cstrong\u003e) Non-Hispanic Black\u003c/strong\u003e, (C) \u003cstrong\u003eHispanic\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4138145/v1/88a0bec178c4ede6b1b5d7d9.jpeg"},{"id":57378987,"identity":"54493f08-894b-441a-bdeb-caa38e4f1d2d","added_by":"auto","created_at":"2024-05-30 00:54:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1725172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4138145/v1/26885389-bb36-448e-a64a-c22910cc02e7.pdf"},{"id":53462255,"identity":"d67d9857-ee25-4128-a69c-fb0384132ecb","added_by":"auto","created_at":"2024-03-26 09:28:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20608,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-4138145/v1/b54aee59f95fa7bd838f5771.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Racial Disparities in Alcoholic Hepatitis Hospitalizations in the United States: Trends, Outcomes, and Future Projections","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlcoholic liver disease encompasses a spectrum of liver injuries due to alcohol use, ranging from steatosis and hepatitis to cirrhosis. This spectrum is marked by various pathophysiological changes in the liver, including fatty liver, inflammation, and fibrosis, and leading to cirrhosis (1). Alcoholic hepatitis (AH) is an acute, inflammation-driven condition that emerges as a complication of alcohol consumption and is associated with high morbidity and mortality globally. In severe cases, AH can have a 30-day mortality rate of 17 to 50% (2).\u003c/p\u003e \u003cp\u003eIn the United States, excessive alcohol consumption ranks as the third leading cause of preventable death. Surveys indicate that 68% of American adults consume alcohol monthly, with 10% classified as heavy drinkers (3,4). AH\u0026rsquo;s incidence is challenging to determine due to asymptomatic cases, but studies suggest a prevalence of 20\u0026ndash;35% among alcohol consumers. With an estimated 8% of Americans suffering from alcoholism, this translates to approximately 26.6\u0026nbsp;million individuals at risk for AH, potentially resulting in 5.3\u0026ndash;9.3\u0026nbsp;million AH cases (4).\u003c/p\u003e \u003cp\u003eThe management of AH remains a significant medical challenge, with steroids as the primary treatment. However, these treatments do not substantially reduce the long-term mortality rates (5\u0026ndash;7). The risk of developing AH varies with the amount and duration of alcohol consumption, indicating the interplay of environmental, genetic, and sociodemographic factors in the disease development (7). Despite recent efforts to equalize healthcare access across racial and ethnic groups for chronic liver disease, the impact of these efforts on AH remains to be examined (8,9). Therefore, our study aims to analyze the mortality and morbidity of AH across racial groups and employ forecasting methods to project hospitalization trends up to 2028. This will aid in devising public health initiatives to address the escalating burden of AH.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eDesign\u003c/p\u003e \u003cp\u003eThis cross-sectional study analyzed data from the Nationwide Inpatient Sample (NIS) spanning from 2012 to 2021. The NIS, part of the Healthcare Cost and Utilization Project (HCUP), is a collaborative initiative between the Federal government and the healthcare industry, sponsored by the Agency for Healthcare Research and Quality (AHRQ). It provides discharge-level information on diagnoses, procedures, and demographics. Our primary unit of analysis was hospital discharge records.\u003c/p\u003e \u003cp\u003eStudy population\u003c/p\u003e \u003cp\u003eThe study sample comprised hospitalizations identified using specific ICD-9-CM and ICD-10-CM codes for AH, validated in previous studies (10,11). Using the NIS database, we assessed several outcomes: a) the number of hospitalizations from 2012 to 2021, b) in-hospital mortality rates, c) length of stay (LOS), and d) in-hospital complications related to AH. The main independent variable was race/ethnicity, categorized as non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic. Covariates included sociodemographic factors (age, gender, insurance status, income levels) and hospital characteristics (bed sizes, medical comorbidity). The ethical considerations were adhered to, with the study receiving a waiver from the John H. Stroger Hospital ethics committee due to the use of publicly available and de-identified data.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStata statistical software package (version 17.0, Stata Corp LP, College Station, TX), and R studio software (version 2023.30, Vienna, Austria) were used for statistical analysis. All statistical tests account for the complex survey methodology and were 2-sided with a P value of \u0026lt;\u0026thinsp;0.05 chosen as the level of significance. Continuous variables were presented with mean and compared with the student t-test and categorical variables were presented with percentages and compared with the Chi-square test. Temporal trends in the number of hospitalizations for AH were assessed by calculating the annual percentage change (APC), and average annual percentage change (AAPC) using a generalized linear model. Jointpoint regression was employed to detect statical inflection points using the grid search method. For assessing the independent relationship between race/ ethnicity and mortality, we employed multivariable logistic regression analysis, presenting odds ratios and 95% confidence intervals. Additionally, we used multivariable linear analyses (to examine the relationship between race/ethnicity and LOS. We also displayed the regression coefficient and its corresponding 95% confidence interval. Hospitalization numbers were calculated as \u0026ldquo;Hospitalization Density\u0026rdquo;, using U.S Census Bureau data to standardize the population to the calculated years, and reported as per 100,000 persons-year. The change in hospitalization is also presented. Annual changes in hospitalization rates were calculated as percent changes in the number of hospitalizations using 2012 as the reference year of each race/ethnicity. The future projections for AH to the year 2028 were forecasted using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. This model encompasses both trend and seasonality in time series data. Monthly data between January 2012 and December 2021 were used as a training dataset to develop the forecasting model to predict the monthly count of AH hospitalizations from January 2022 to December 2028.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe study cohort was predominantly White (68%), with the remainder of the cohort composed of Blacks (10%) and Hispanics (12%). The mean age of the participants was similar across the White (48.6 years) and Black cohorts (49.6 years), but slightly lower in the Hispanic cohort (44.8 years). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Males constituted the majority in all racial groups, comprising 64.8% of the White cohort, 66.3% of the Black cohort, and 79.8% of the Hispanic cohort. Insurance coverage varied notably across the groups. Medicare was the primary insurer for 18.0% of White patients, 20.9% of Black patients, and 10.7% of Hispanic patients. Medicaid coverage was more prevalent among Blacks (45.9%) and Hispanics (51.3%) than Whites (35.7%). Private insurance was held by 31.3% of Whites, 18.1% of Blacks, and 16.8% of Hispanics. A significant proportion of each group was non-insured, with 15.0% in Whites, 15.2% in Blacks, and a higher rate of 21.2% in Hispanics. Income distribution showed that the lowest median household income bracket contained 22.2% of Whites, a striking contrast to 52.8% of Blacks and 34.4% of Hispanics. Conversely, the highest income bracket included 24.4% of Whites, 10.4% of Blacks, and 15.9% of Hispanics, findings included in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRegarding hospital characteristics, the cohort was distributed across various bed sizes, with 49.1% of NHW, 50.2% of NHB, and 51.5% of Hispanics treated in large hospitals. The hospital region also varied, with 43.3% of Blacks treated in the South region, significantly higher than Whites (31.4%) and Hispanics (23.7%). The hospital location and teaching status indicated that a large majority of NHB (77.3%) and Hispanics (74.8%) were treated in urban teaching hospitals, compared to 64.2% of NHW.\u003c/p\u003e \u003cp\u003eComorbidities were prevalent across the cohort with hypertension being the most common, particularly among Blacks (49.7%) compared to Whites (39.8%) and Hispanics (30.9%). Chronic kidney disease (CKD) and congestive heart failure (CHF) were also more prevalent in the Black cohort (8.5% and 9.1%, respectively) than in Whites (4.4% and 5.3%, respectively) and Hispanics (4.9% and 3.7%, respectively).\u003c/p\u003e \u003cp\u003eTemporal Trend and Projection:\u003c/p\u003e \u003cp\u003eDuring the study period, the hospitalization density of alcoholic hepatitis increased at varied rates between racial groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The AH hospitalization density in non-Hispanic whites increased from 25 per 100,000 person-years in 2012 to 42 per 100,000 person-years in 2021, presenting an AAPC of 6.83%, in non-Hispanic blacks increased from 23 per 100,000 person-years in 2012 to 38 per 100,000 person-years in 2021, with an AAPC of 7.22%, and in Hispanics, it increased from 18 per 100,000 person-years in 2012 to 35 per 100,000 person-years in 2021, with an overall AAPC of 9.30%. On the evaluation of the trend segment, in Hispanics, we noted two jointpoint changes, with a much steeper rise between 2014\u0026ndash;2021 of APC 10.76% (95CI: 9.59 to 14.33). Trend segment analysis also revealed a significant rise in the NHB population with a steeper rise in hospitalization density during 2019\u0026ndash;2021 with an APC of 13.63% (95CI: 6.55 to 18.34) (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). When evaluating the annual number of hospitalizations using the starting study year 2012 as a reference, the cumulative percentage change in the number of hospitalizations increased the most in Hispanics (129.1%), followed by non-Hispanic Black (78.2%), and then non-Hispanics White (70.5%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In our forecast model, the number of hospitalizations is expected to continue to rise in all racial groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), in non-Hispanic whites it is expected to increase from 104,895 in 2021, to a forecasted 116,840, with an AAPC of 1.40%. Contrastingly, Hispanic groups are expected to have a more rapid rise in the number of alcoholic hepatitis hospitalizations from 21,790 in 2021 to 36,124 cases in 2028, with an average of 7.44% increase annually (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eand Table S2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003ePrimary Outcome: Mortality\u003c/p\u003e \u003cp\u003eThere were 28,240 (4.2%) deaths among NHW and 4,840 (4.2%) deaths among Hispanics, followed by 3,720 deaths (3.6%) among NHB (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The adjusted model showed significantly lower in-patient mortality for NHB (adjusted odds ratio (aOR] 0.73; 95% CI: 0.68\u0026ndash;0.79) compared to NHW (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. No significant difference in in-patient mortality was observed for Hispanics compared to NHW. Other predictors for inpatient mortality included increasing age (aOR: 1.03; 95%CI:1.03\u0026ndash;1.04, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and comorbidities including chronic kidney disease (aOR: 1.82, 95%CI:1.68\u0026ndash;1.98, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and congestive heart failure (aOR: 1.35; 95%CI: 1.24\u0026ndash;1.48; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eSecondary Outcome:\u003c/p\u003e \u003cp\u003eDuring the study period, there were 1,535 liver transplants performed. The proportion of liver transplant recipients among AH hospitalization was highest among non-Hispanic Whites (NHW) at 0.2%, followed by Hispanics at 0.13%, and non-Hispanic Blacks (NHB) at 0.1%. On adjusted analysis, NHB had lower odds of receiving a liver transplant (aOR: 0.50; 95%CI: 0.30\u0026ndash;0.83; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to NHW \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. No significant differences were observed between Hispanics and NHW. The LOS was similar for NHW (6.2) and Hispanic patients (6.1), which was longer than for NHB patients (6.0), and an additional multivariate analysis of factor-affected LOS is listed in \u003cb\u003eTable S3\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eHispanic patients exhibited the highest in-hospital rates of sepsis (10.8%), ascites (6.3%), and variceal bleeding (25.8%). In the adjusted model, they were significantly more likely to experience sepsis (aOR: 1.24; 95%CI: 1.18\u0026ndash;1.30; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ascites (aOR: 1.10; 95%CI: 1.10\u0026ndash;1.14; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and variceal hemorrhage (aOR: 1.61; 95%CI: 1.51\u0026ndash;1.72; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to NHW. NHB patients had the highest in-hospital rate of acute kidney injury (AKI) at 25.1%, followed by NHW (20.9%), and then Hispanics (20.4%). NHB had higher odds of AKI (aOR 1.1; 95%CI: 1.10\u0026ndash;1.10, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to NHW. However, NHB patients had lower odds for ascites (aOR: 0.60; 95CI: 0.58\u0026ndash;0.62; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), variceal hemorrhage (aOR 0.72; 95%CI: 0.65\u0026ndash;0.79; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and hepatic encephalopathy (aOR: 0.81; 95%CI: 0.77\u0026ndash;0.85; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis comprehensive analysis of a nationally representative cohort elucidates racial disparities in the burden of AH and projects an escalating future burden. Our observations indicate a marked escalation in AH hospitalizations, notably among Hispanics who experienced a 129.1% increase from 2012 to 2021. This increment substantially surpasses that of NHW at 70.5% and NHB at 78.2%, signaling a burgeoning future burden of AH, especially in this demographic group. In addition, we also observed a significant change in time-period trend in the NHBs population with rapidly rising APC during the period of the COVID-19 pandemic. Our study further delineates disparities in mortality rates and rate of liver transplants with NHBs exhibiting lower inpatient mortality yet facing reducing likelihood of liver transplants compared to NHWs. Insurance coverage disparities and comorbidity prevalence were also notable, with Hispanics facing the highest rates of in-hospital complications, such as sepsis and variceal hemorrhage, and NHBs presenting the highest incidence of acute kidney injury.\u003c/p\u003e \u003cp\u003eAlthough prior research has shown a general rise in AH (10,12,13), our study uniquely highlights variations in the current racial burden and projects the future burden of AH for each race/ethnicity up to 2028. The disproportionately rising trend among Hispanics has been largely attributed to changing alcohol consumption habits, especially with a shift toward young adults between 15\u0026ndash;39 years old (14). This underscores the need for focused public intervention, particularly among Hispanic communities, to mitigate the impending burden of AH. The COVID-19 pandemic has further exacerbated the problem (15) and has since widened this racial gap. Using 2019 as a pre-pandemic reference year compared to 2021, we observed that the relative percentage change in AH hospitalization increased most significantly among Hispanics (33.0%), followed by NHBs (28.3%) and then NHWs (13.9%). This short-term rise in AH burden among racial groups could result in increasing mortality, and disability-adjusted life-year loss, as modeled by Julien et el (16). Moreover, this increasing burden is augmented by the higher rates of morbidity they face while hospitalized. These findings align with previous research indicating greater in-hospital complications and healthcare service utilization for AH among Hispanics (17). Factors contributing to these disparities include inadequate insurance coverage and delays in seeking preventative services, leading to advanced-stage presentations and higher hospitalization and resource utilization rates (18).\u003c/p\u003e \u003cp\u003eOur findings highlight two concerning trends among Hispanics: younger age at admission and the higher prevalence of in-hospital complications of manifestation of portal hypertension. National survey data from the United States have documented an alarming increase in per capita alcohol consumption, particularly among younger NHWs and Hispanics (19). Another factor contributing to this early onset could be genetic predispositions. Previously PNPLA3 gene has been demonstrated to increase the risk for alcohol-related liver disease (20,21), and heterogeneity in the expression of alcohol metabolizing enzyme allele among Hispanics could also play a role. The elevated rate of in-hospital complications from portal hypertension may also indicate poor outpatient management of chronic liver disease and insufficient environmental and medical support for this ethnic minority group. Preventative measures like regular endoscopic screenings and access to medications for varices prophylaxis and hepatic encephalopathy are crucial (22\u0026ndash;24). These practices are particularly underutilized by those from lower socioeconomic backgrounds as well as individuals with co-existing psychiatric illnesses or substance abuse disorders (25).\u003c/p\u003e \u003cp\u003eThe mortality disparity in NHB observed in our study expands the body of knowledge on racial disparities in AH mortality. This aligns with the findings of May et el, suggesting that NHBs are more likely to present with milder forms of AH, as indicated by lower discriminant function scores (26). This could partially explain the observed difference in mortality rates. Moreover, variations in care patterns across racial groups could lead to inadequate treatment and premature discharges for NHB patients, potentially increasing mortality rates outside the hospital setting (27,28). Interestingly, our data also suggests lower rates of hepatorenal syndrome and variceal hemorrhage among NHBs, which may lessen contraindications for steroid use and offer a mortality benefit. However, Lei et el suggest increased mortality observed in moderate-drinking behavior secondary to liver diseases among NHBs, a pattern not observed in NHWs (29). The difference may stem from a complex interplay of genetic variations in alcohol metabolizing enzymes, and environmental factors, including metabolic syndrome and obesity, influenced by lifestyle and dietary patterns. Although our data does not clarify the severity of AH presentation among racial groups, it underscores the need for future research to understand the intricate relationships between metabolic syndrome, alcohol consumption levels, and social determinants such as BMI, diet, and insurance coverage, to better comprehend the racial disparities in AH mortality.\u003c/p\u003e \u003cp\u003eDespite NHB patients showing lower inpatient mortality rates for AH, we noted a lower rate of liver transplants within this demographic. Our study supports previous findings from various transplant databases (30\u0026ndash;32) and underscores disparities rooted in multifaceted factors. Firstly, there is a noted variation in the severity of alcohol-related liver injury and recovery among racial groups, with NHB individuals potentially experiencing milder AH compared to NHW (26). Patient-related barriers, such as limited healthcare access and financial limitations, contribute to lower rates of transplant referral rates (33,34). Furthermore, studies have indicated neighborhood income level independently affects the likelihood of being waitlisted for a transplant (35). Our study revealed that NHB patients predominantly reside in the lowest income quintile, therefore likely influencing their reduced rate of liver transplant. Provider-related barriers also play a role, with NHBs less likely to be referred for transplant listing and facing higher post-transplant mortality and morbidity (36\u0026ndash;38). Systemic barriers, including insurance-related challenges, exacerbate these disparities (39). Although our analysis does not allow for a detailed analysis of these factors, we aim to shed light on the current inpatient disease landscape. Our goal is to encourage future efforts to explore the causes of these disparities and focus on addressing the inequities by improving healthcare access and tackling implicit bias among healthcare providers.\u003c/p\u003e \u003cp\u003eOur study, which utilizes retrospective analysis of administrative data from the NIS, acknowledges several inherent limitations. One significant constraint is our reliance on ICD-9-CM and ICD-10-CM codes, which are susceptible to coding inaccuracies. This issue is particularly relevant as our study spans the year 2015, a transitional period from ICD-9-CM to ICD-10-CM, potentially impacting the precision of diagnostic codes. To mitigate this, we employed established codes from prior literature (10,11,17). Another limitation is the absence of laboratory data in the NIS, hindering our ability to assess disease severity. This is especially critical for AH where measures like the discriminant function score are vital. Furthermore, the NIS lacks detailed individual patient information, limiting our understanding of the temporality of events and precluding access to longitudinal data post-discharge. This could lead to an underestimation of the overall mortality rate observed in our study. Finally, the lack of granular patient details prevented an evaluation of factors such as social support and past substance use history, which are influential in the context of liver transplant reception.\u003c/p\u003e \u003cp\u003eDespite these limitations, our study has significant merits that are worth noting. To our knowledge, this study provides the most current analysis of the racial and ethnic burden of AH in the United States, including future projections. The use of the NIS, a nationally representative database, is a key strength. It encompasses a diverse range of patients, hospital types, and geographic areas across the United States, offering a comprehensive view of the current inpatient epidemiological state of AH. This broad scope enhances the generalizability of our findings and underscores the study's substantial contribution to understanding AH's impact on a diverse population.\u003c/p\u003e \u003cp\u003eIn conclusion, this comprehensive analysis sheds light on the pronounced racial disparities in the burden of AH within the United States, notably escalating among Hispanics. This trend, significantly tied to increased alcohol consumption and subsequent healthcare expenditures, calls for urgent and targeted public health interventions. Our findings particularly highlight the younger average age at which Hispanics are admitted to the hospital and their higher incidence of in-hospital complications, including portal hypertension, pointing to the need for improved management strategies for chronic liver disease. Moving forward, it is needed to understand the influence of social determinants affect health outcomes. Future research should include diverse hospital settings and collection of disease severity details to provide a more thorough understanding of the issues, thereby adding to the reduction of health disparities highlighted by our study.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eAH\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Alcoholic Hepatitis\u003c/p\u003e\n\u003cp\u003eNHW\u0026nbsp;\u0026nbsp;Non-Hispanic White\u003c/p\u003e\n\u003cp\u003eNHB\u0026nbsp; \u0026nbsp;Non-Hispanic Black\u003c/p\u003e\n\u003cp\u003eLOS\u0026nbsp; \u0026nbsp;\u0026nbsp;Length of Stay\u003c/p\u003e\n\u003cp\u003eICD-9-CM\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;International Classification of Diseases, Ninth Revision, Clinical Modification\u003c/p\u003e\n\u003cp\u003eICD-10-CM\u0026nbsp; \u0026nbsp;\u0026nbsp;International Classification of Diseases, Tenth Revision, Clinical Modification\u003c/p\u003e\n\u003cp\u003eAPC\u0026nbsp; \u0026nbsp;\u0026nbsp;Annual Percentage Change\u003c/p\u003e\n\u003cp\u003eAAPC\u0026nbsp;Average Annual Percentage Change\u003c/p\u003e\n\u003cp\u003eSARIMA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Seasonal Autoregressive Integrated Moving Average\u003c/p\u003e\n\u003cp\u003eCKD\u0026nbsp; \u0026nbsp;Chronic Kidney Disease\u003c/p\u003e\n\u003cp\u003eCOPD\u0026nbsp;Chronic Obstructive Pulmonary Disease\u003c/p\u003e\n\u003cp\u003eCHF\u0026nbsp; \u0026nbsp;\u0026nbsp;Congestive Heart Failure\u003c/p\u003e\n\u003cp\u003eHLD\u0026nbsp; \u0026nbsp;\u0026nbsp;Hyperlipidemia\u003c/p\u003e\n\u003cp\u003eHTN\u0026nbsp; \u0026nbsp;\u0026nbsp;Hypertension\u003c/p\u003e\n\u003cp\u003eAKI \u0026nbsp; \u0026nbsp; Acute Kidney Injury\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosures\u003c/strong\u003e: None to declare.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e: The data used in this study are publicly available from Healthcare Cost and Utilization Project (HCUP\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial support\u003c/strong\u003e: No funding support to disclose\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent Statement\u003c/strong\u003e: Not applicable. This study did not involve patients or require patient consent\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpecific author contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy Concept and Design: \u0026nbsp; C.P\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcquisition, analysis, or interpretation of data for the work: C.P, D.G, V.K\u003c/p\u003e\n\u003cp\u003eDrafting the work: C.P, V.K\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupervise the work: V.K\u003c/p\u003e\n\u003cp\u003eRevision of the work critically for important intellectual content: All authors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinal approval of the version to be published: All authors\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHosseini N, Shor J, Szabo G. Alcoholic Hepatitis: A Review. Alcohol Alcohol Oxf Oxfs. 2019 Jul;54(4):408\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eSehrawat TS, Liu M, Shah VH. The Knowns and Unknowns of Treatment for Alcoholic Hepatitis. Lancet Gastroenterol Hepatol. 2020 May;5(5):494\u0026ndash;506.\u003c/li\u003e\n\u003cli\u003eShah NJ, Royer A, John S. Alcoholic Hepatitis. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 [cited 2024 Feb 21]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK470217/\u003c/li\u003e\n\u003cli\u003eMathurin P, Duchatelle V, Ramond MJ, Degott C, Bedossa P, Erlinger S, et al. Survival and prognostic factors in patients with severe alcoholic hepatitis treated with prednisolone. Gastroenterology. 1996 Jun;110(6):1847\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003eThursz MR, Richardson P, Allison M, Austin A, Bowers M, Day CP, et al. Prednisolone or pentoxifylline for alcoholic hepatitis. N Engl J Med. 2015 Apr 23;372(17):1619\u0026ndash;28.\u003c/li\u003e\n\u003cli\u003ePenninti P, Adekunle AD, Singal AK. Alcoholic Hepatitis: The Rising Epidemic. Med Clin North Am. 2023 May;107(3):533\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eLourens S, Sunjaya DB, Singal A, Liangpunsakul S, Puri P, Sanyal A, et al. Acute Alcoholic Hepatitis: Natural History and Predictors of Mortality Using a Multicenter Prospective Study. Mayo Clin Proc Innov Qual Outcomes. 2017 Jul;1(1):37\u0026ndash;48.\u003c/li\u003e\n\u003cli\u003eEl-Serag HB, Kramer J, Duan Z, Kanwal F. Racial differences in the progression to cirrhosis and hepatocellular carcinoma in HCV-infected veterans. Am J Gastroenterol. 2014 Sep;109(9):1427\u0026ndash;35.\u003c/li\u003e\n\u003cli\u003eNephew LD, Aitcheson G, Iyengar M. The Impact of Racial Disparities on Liver Disease Access and Outcomes. Curr Treat Options Gastroenterol. 2022 Sep 1;20(3):279\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eShirazi F, Singal AK, Wong RJ. Alcohol-associated Cirrhosis and Alcoholic Hepatitis Hospitalization Trends in the United States. J Clin Gastroenterol. 2021 Feb;55(2):174\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eAli H, Pamarthy R, Bolick NL, Farooq MF. Ten-year trends and prediction model of 30-day inpatient mortality for alcoholic hepatitis in the United States. Ann Gastroenterol. 2022;35(4):427\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eAnouti A, Mellinger JL. The Changing Epidemiology of Alcohol-Associated Liver Disease: Gender, Race, and Risk Factors. Semin Liver Dis. 2023 Feb;43(01):050\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eDoshi SD, Stotts MJ, Hubbard RA, Goldberg DS. The Changing Burden of Alcoholic Hepatitis: Rising Incidence and Associations with Age, Gender, Race, and Geography. Dig Dis Sci. 2021 May;66(5):1707\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eDoycheva I, Watt KD, Rifai G, Abou Mrad R, Lopez R, Zein NN, et al. Increasing Burden of Chronic Liver Disease Among Adolescents and Young Adults in the USA: A Silent Epidemic. Dig Dis Sci. 2017 May;62(5):1373\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eBarbosa C, Cowell AJ, Dowd WN. Alcohol Consumption in Response to the COVID-19 Pandemic in the United States. J Addict Med. 2021;15(4):341\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eJulien J, Ayer T, Tapper EB, Barbosa C, Dowd WN, Chhatwal J. Effect of increased alcohol consumption during COVID‐19 pandemic on alcohol‐associated liver disease: A modeling study. Hepatology. 2022 Jun;75(6):1480\u0026ndash;90.\u003c/li\u003e\n\u003cli\u003eMay FP, Rolston VS, Tapper EB, Lakshmanan A, Saab S, Sundaram V. The impact of race and ethnicity on mortality and healthcare utilization in alcoholic hepatitis: a cross-sectional study. BMC Gastroenterol. 2016 Dec;16(1):129.\u003c/li\u003e\n\u003cli\u003ephelan-et-al-2010-social-conditions-as-fundamental-causes-of-health-inequalities-theory-evidence-and-policy-implications.pdf.\u003c/li\u003e\n\u003cli\u003eGrant BF, Chou SP, Saha TD, Pickering RP, Kerridge BT, Ruan WJ, et al. Prevalence of 12-Month Alcohol Use, High-Risk Drinking, and \u003cem\u003eDSM-IV\u003c/em\u003e Alcohol Use Disorder in the United States, 2001-2002 to 2012-2013: Results From the National Epidemiologic Survey on Alcohol and Related Conditions. JAMA Psychiatry. 2017 Sep 1;74(9):911.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez LA, Larrieta E, Calva JJ, Kershenobich D, Torre A. The Expression of PNPLA3 Polymorphism could be the Key for Severe Liver Disease in NAFLD in Hispanic Population. Ann Hepatol. 2017 Nov 1;16(6):909\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eTian C, Stokowski RP, Kershenobich D, Ballinger DG, Hinds DA. Variant in PNPLA3 is associated with alcoholic liver disease. Nat Genet. 2010 Jan;42(1):21\u0026ndash;3.\u003c/li\u003e\n\u003cli\u003eRobinson A, Tavakoli H, Liu B, Bhuket T, Cheung R, Wong RJ. African-Americans with Cirrhosis Are Less Likely to Receive Endoscopic Variceal Screening Within One Year of Cirrhosis Diagnosis. J Racial Ethn Health Disparities. 2018 Aug 1;5(4):860\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003ePinon-Gutierrez R, Durbin-Johnson B, Halsted CH, Medici V. Clinical features of alcoholic hepatitis in latinos and caucasians: A single center experience. World J Gastroenterol. 2017 Oct 28;23(40):7274\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003eTapper EB, Essien UR, Zhao Z, Ufere NN, Parikh ND. Racial and ethnic disparities in rifaximin use and subspecialty referrals for patients with hepatic encephalopathy in the United States. J Hepatol. 2022 Aug 1;77(2):377\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003eRogal S, Youk A, Zhang H, Gellad WF, Fine MJ, Good CB, et al. Impact of Alcohol Use Disorder Treatment on Clinical Outcomes among Patients with Cirrhosis. Hepatol Baltim Md. 2020 Jun;71(6):2080\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eLevy R, Catana AM, Durbin-Johnson B, Halsted CH, Medici V. Ethnic Differences in Presentation and Severity of Alcoholic Liver Disease. Alcohol Clin Exp Res. 2015 Mar;39(3):566\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eVolpp KG, Stone R, Lave JR, Jha AK, Pauly M, Klusaritz H, et al. Is Thirty-Day Hospital Mortality Really Lower for Black Veterans Compared with White Veterans? Health Serv Res. 2007 Aug;42(4):1613\u0026ndash;31.\u003c/li\u003e\n\u003cli\u003eLandon BE, Onnela JP, Meneades L, O\u0026rsquo;Malley AJ, Keating NL. Assessment of Racial Disparities in Primary Care Physician Specialty Referrals. JAMA Netw Open. 2021 Jan 25;4(1):e2029238.\u003c/li\u003e\n\u003cli\u003eFan L, Zhu X, Shingina A, Kabagambe EK, Shrubsole MJ, Dai Q. Racial Disparities in Associations of Alcohol Consumption With Liver Disease Mortality in a Predominantly Low-Income Population: A Report From the Southern Community Cohort Study. Am J Gastroenterol. 2022 Sep;117(9):1523\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eBodek DD, Everwine MM, Lunsford KE, Okoronkwo N, Patel PA, Pyrsopoulos N. Racial Disparities in Liver Transplantation for Hepatocellular Carcinoma: Analysis of the National Inpatient Sample From 2007 to 2014. J Clin Gastroenterol. 2023 Mar;57(3):311.\u003c/li\u003e\n\u003cli\u003eCotter TG, Mitchell MC, Patel MJ, Anouti A, Lieber SR, Rich NE, et al. Racial and Ethnic Disparities in Liver Transplantation for Alcohol-associated Liver Diseases in the United States. Transplantation. 2024 Jan;108(1):225\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eDeutsch-Link S, Bittermann T, Nephew L, Ross-Driscoll K, Weinberg EM, Weinrieb RM, et al. Racial and ethnic disparities in psychosocial evaluation and liver transplant waitlisting. Am J Transplant. 2023 Jun 1;23(6):776\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eKemmer N. Ethnic Disparities in Liver Transplantation. Gastroenterol Hepatol. 2011 May;7(5):302\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eWarren C, Carpenter AM, Neal D, Andreoni K, Sarosi G, Zarrinpar A. Racial Disparity in Liver Transplantation Listing. J Am Coll Surg. 2021 Apr;232(4):526\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eMohamed KA, Ghabril M, Desai A, Orman E, Patidar KR, Holden J, et al. Neighborhood poverty is associated with failure to be waitlisted and death during liver transplantation evaluation. Liver Transpl. 2022 Sep;28(9):1441\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003eJulapalli VR, Kramer JR, El-Serag HB. Evaluation for liver transplantation: Adherence to AASLD referral guidelines in a large veterans affairs center. Liver Transpl. 2005;11(11):1370\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eEckhoff DE, McGuire BM, Young CJ, Sellers MT, Frenette LR, Hudson SL, et al. Race: a critical factor in organ donation, patient referral and selection, and orthotopic liver transplantation? Liver Transplant Surg Off Publ Am Assoc Study Liver Dis Int Liver Transplant Soc. 1998 Nov;4(6):499\u0026ndash;505.\u003c/li\u003e\n\u003cli\u003eKamal SAF, Vikash S, Sohail H, Kilani Y, Vikash F. Racial disparities in the outcomes of liver transplantation in the treatment of hepatocellular carcinoma. J Clin Oncol. 2023 Jun;41(16_suppl):4131\u0026ndash;4131.\u003c/li\u003e\n\u003cli\u003eWahid NA, Rosenblatt R, Brown RS. A Review of the Current State of Liver Transplantation Disparities. Liver Transpl. 2021 Mar;27(3):434\u0026ndash;43.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographics and characteristic of patient hospitalized with Alcoholic Hepatitis from 2012-2020\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.578778135048232%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.344051446945338%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhite\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e698,009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.344051446945338%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e68%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.183279742765274%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlack\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e104,695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.183279742765274%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.183279742765274%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanics\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e120,115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.183279742765274%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e12%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.578778135048232%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.688102893890676%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e48.6\u003c/p\u003e\n \u003cp\u003e(48.5-48.6)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.366559485530548%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e49.6\u003c/p\u003e\n \u003cp\u003e(49.4-49.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.366559485530548%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003cp\u003e(44.7-45)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e519,990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e64.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e80,555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e66.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e113,295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e79.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e282,875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e35.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e40,990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e33.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e28,660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e20.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedicare\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e125,140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e18.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e21,935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e20.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e13,195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e10.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedicaid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e248,615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e35.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e48,235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e45.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e63,265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e51.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrivate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e217,370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e31.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e19,020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e18.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e20,680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e16.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-insured\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e104,520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e15.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e15,930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e15.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e26,190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e21.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian household income\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0-25th\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e173,210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e22.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e62,640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e52.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e46,095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e34.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e26\u003csup\u003eth\u003c/sup\u003e-50th\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e203,040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e26.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e25,030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e21.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e33,830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e25.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e51\u003csup\u003est\u003c/sup\u003e-75th\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e215,010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e27.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e18,510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e15.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e32,860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e24.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e75\u003csup\u003eth\u003c/sup\u003e-100th\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e190,955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e24.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e12,370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e10.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e21,285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e15.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Bedsize\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e168,555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e21.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e24,705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e20.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e26,895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e19.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e240,100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e29.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e35,840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e29.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e41,985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e29.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLarge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e394,305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e49.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e61,030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e50.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e73,080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e51.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Region\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNortheast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e163,510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e20.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e24,555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e20.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e30,450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e21.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMidwest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e198,975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e24.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e29,895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e24.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e13,345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e9.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSouth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e252,140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e31.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e52,640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e43.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e33,660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e23.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e188,335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e23.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e14,485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e11.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e64,505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e45.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital location/teaching status\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRural\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e63,495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e7.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e5,290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e4.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e3,620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.578778135048232%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"79.42122186495178%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-teaching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e223,795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e27.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e22,365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e18.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e32,220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e22.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.545746388443018%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTeaching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" colspan=\"\" valign=\"top\"\u003e\n \u003cp\u003e515,670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e64.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e93,920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e77.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e106,120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" valign=\"top\"\u003e\n \u003cp\u003e74.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCKD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e33,950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e9,845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e8.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e6,720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e4.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e87,925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e11.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e10,870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e8.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e4,110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e2.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e43,605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e5.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e11,195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e9.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e5,270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e3.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e88,020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e11.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e14,320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e11.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e12,915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e9.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHTN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e318,255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e39.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e59,730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e49.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e44,050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e31.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn-hospital Complication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSepsis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e75,045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e9.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e11,985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e9.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e15,270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e10.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAKI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e167,540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e20.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e30,565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e25.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e28,940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e20.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAscites\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e34,100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e4.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e4,760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e3.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e8,945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e6.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariceal hemorrhage\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e23,990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e3.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e2,685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e2.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e7,275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e5.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHepatorenal syndrome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e35,410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e4.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e3,550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e2.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e6,620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e4.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHepatic encephalopathy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e97,210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e12.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e13,110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e10.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e15,740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e11.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRed blood cell transfusion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e61,645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e7.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e12,590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e10.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e15,625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e11.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlatelet transfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e20,975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e3,185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e6,250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e4.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of procedures\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e45,305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e13.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e7,890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e15.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e9,085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e13.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e138,795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e40.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e18,685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e37.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e24,135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e36.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e60,455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e17.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e8,445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e16.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e12,325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e18.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.582664526484752%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e100,315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e29.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e14,920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e29.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.48314606741573%\" valign=\"top\"\u003e\n \u003cp\u003e20,335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.32263242375602%\" valign=\"top\"\u003e\n \u003cp\u003e30.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Clinical Outcomes of Hospitalized Patients with Alcoholic Hepatitis Stratified by Race and Ethnicity \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.853932584269664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary outcomes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; N/%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.508828250401283%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Hispanic White\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Hispanic Black\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.669341894060995%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.853932584269664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.508828250401283%\" valign=\"top\"\u003e\n \u003cp\u003e33,255 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e4,330 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.669341894060995%\" valign=\"top\"\u003e\n \u003cp\u003e5,935 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\" valign=\"top\"\u003e\n \u003cp\u003eP \u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.853932584269664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver transplant\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.508828250401283%\" valign=\"top\"\u003e\n \u003cp\u003e1,255 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e95 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.669341894060995%\" valign=\"top\"\u003e\n \u003cp\u003e185 (0.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\" valign=\"top\"\u003e\n \u003cp\u003eP 0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.853932584269664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of Stay (Days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.508828250401283%\" valign=\"top\"\u003e\n \u003cp\u003e6.2 (6.1 to 6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e6 (5.9 to 6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.669341894060995%\" valign=\"top\"\u003e\n \u003cp\u003e6.1 (6 to 6.2)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\" valign=\"top\"\u003e\n \u003cp\u003eP \u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Multivariate analysis of Alcoholic Hepatitis hospitalization In-hospital Complication between Racial/Ethnic groups between 2012 to 2020, reference group to Non-Hispanic White\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.53846153846154%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Hispanic Black\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.46153846153846%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanic\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Outcome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003eCrude OR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003eaOR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003eCrude OR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003eaOR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (0.79 to 0.92)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.68 to 0.79)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e1.01 (0.95 to 1.08)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.99 to 1.14)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary Outcomes:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.46153846153846%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver transplant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.5 (0.31 to 0.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.5 (0.3 to 0.83)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e0.83 (0.57 to 1.21)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e0.77 (0.52 to 1.12)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute kidney injury\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e1.27 (1.23 to 1.32)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (1.1 to 1.1)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e0.97 (0.94 to 1)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.95 to 1.02)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHepatorenal syndrome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.65 (0.6 to 0.71)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.53 (0.49 to 0.58)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (1 to 1.13)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e1.03 (0.96 to 1.1)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAscites\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.65 (0.62 to 0.67)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (0.58 to 0.62)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (1.03 to 1.1)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (1.06 to 1.14)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHepatic Encephalopathy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.84 to 0.92)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.81 (0.77 to 0.85)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e0.91 (0.87 to 0.95)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e0.96 (0.91 to 1)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSepsis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (1.01 to 1.11)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.99 (0.94 to 1.04)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e1.17 (1.12 to 1.22)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e1.24 (1.18 to 1.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariceal Hemorrhage \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.67 to 0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\" valign=\"top\"\u003e\n \u003cp\u003e0.72 (0.65 to 0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.307692307692307%\" valign=\"top\"\u003e\n \u003cp\u003e1.75 (1.65 to 1.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e1.61 (1.51 to 1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Odd Ratio are calculated compared to Non-Hispanic White as reference group, Multivariate model are adjusted to gender, age, hospital characteristics.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"digestive-diseases-and-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ddsj","sideBox":"Learn more about [Digestive Diseases and Sciences](http://link.springer.com/journal/10620)","snPcode":"10620","submissionUrl":"https://submission.nature.com/new-submission/10620/3","title":"Digestive Diseases and Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Alcoholic Hepatitis, Racial Disparities, HCUP-NIS, Liver Disease","lastPublishedDoi":"10.21203/rs.3.rs-4138145/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4138145/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction:\u003c/p\u003e\n\u003cp\u003eAlcoholic Hepatitis (AH) is a serious complication of alcohol consumption with high morbidity and mortality, particularly in the United States where alcohol-related liver diseases rank as one of the leading causes of preventable death. Our study aims to analyze the morbidity and mortality of AH across racial groups and project hospitalization trends up to 2028, thereby informing public health initiatives.\u003c/p\u003e\n\u003cp\u003eMethods:\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional study utilizing data from the Nationwide Inpatient Sample (NIS) spanning 2012 to 2021. The study population comprised hospitalizations identified using specific ICD-9-CM and ICD-10-CM codes for AH. We assessed hospitalizations, in-hospital mortality rates, length of stay (LOS), and morbidities related to alcoholic hepatitis adjusting for sociodemographic factors and hospital characteristics. Statistical analyses were performed using Stata and R software, employing logistic and linear regression analyses, and SARIMA models for forecasting.\u003c/p\u003e\n\u003cp\u003eResults:\u003c/p\u003e\n\u003cp\u003eOur results indicated a predominantly White cohort (68%), with a notable increase in AH hospitalizations among Hispanics (129.1% from 2012 to 2021). Racial disparities were observed in inpatient mortality, liver transplant accessibility, and the occurrence of in-hospital complications. The study forecasts a continued rise in hospitalizations across all racial groups, with Hispanics experiencing the sharpest increase.\u003c/p\u003e\n\u003cp\u003eConclusion:\u003c/p\u003e\n\u003cp\u003eOur study reveals a disproportionate rise in the AH burden among Hispanics with projections indicating a persistent upward trend through 2028. These findings highlight the need for targeted public health strategies and improved healthcare access to mitigate the increasing AH burden and address disparities in care and outcomes.\u003c/p\u003e","manuscriptTitle":"Racial Disparities in Alcoholic Hepatitis Hospitalizations in the United States: Trends, Outcomes, and Future Projections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-26 09:20:38","doi":"10.21203/rs.3.rs-4138145/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-12T21:21:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-08T21:27:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3829f14c-a5d8-4929-b4e0-768bcdf526e4","date":"2024-03-25T17:38:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-23T16:38:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-22T22:16:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-22T05:04:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Digestive Diseases and Sciences","date":"2024-03-20T15:09:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"digestive-diseases-and-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ddsj","sideBox":"Learn more about [Digestive Diseases and Sciences](http://link.springer.com/journal/10620)","snPcode":"10620","submissionUrl":"https://submission.nature.com/new-submission/10620/3","title":"Digestive Diseases and Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1cea407c-37d6-492c-97a7-f073b9488433","owner":[],"postedDate":"March 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-30T00:54:45+00:00","versionOfRecord":{"articleIdentity":"rs-4138145","link":"https://doi.org/10.1007/s10620-024-08462-1","journal":{"identity":"digestive-diseases-and-sciences","isVorOnly":false,"title":"Digestive Diseases and Sciences"},"publishedOn":"2024-05-29 00:54:45","publishedOnDateReadable":"May 29th, 2024"},"versionCreatedAt":"2024-03-26 09:20:38","video":"","vorDoi":"10.1007/s10620-024-08462-1","vorDoiUrl":"https://doi.org/10.1007/s10620-024-08462-1","workflowStages":[]},"version":"v1","identity":"rs-4138145","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4138145","identity":"rs-4138145","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}