Outcomes of Acute Pancreatitis in Lean Vs. Non-Lean Metabolic Dysfunction-Associated Steatotic Liver Disease (Masld) Patients: A Nationwide Analysis

Outcomes of Acute Pancreatitis in Lean Vs. Non-Lean Metabolic Dysfunction-Associated Steatotic Liver Disease (Masld) Patients: A Nationwide Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Outcomes of Acute Pancreatitis in Lean Vs. Non-Lean Metabolic Dysfunction-Associated Steatotic Liver Disease (Masld) Patients: A Nationwide Analysis Prince Addo Ameyaw, Sarpong Boateng, Yussif Issaka, Erika Sandra Ackah, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6694877/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Jul, 2025 Read the published version in Digestive Diseases and Sciences → Version 1 posted 8 You are reading this latest preprint version Abstract Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a key contributor to the severity and outcomes of acute pancreatitis (AP). This study compares the clinical outcomes of AP in patients with lean versus non-lean MASLD. Methods: We identified adult patients hospitalized with AP and a secondary diagnosis of MASLD from the National Inpatient Sample (NIS 2016-2020). Outcomes, including mortality, organ failures, and healthcare utilization, were analyzed using logistic and linear regression models, adjusting for demographic, clinical, and hospital factors. Results: We included 34,388 hospitalized patients with AP and MASLD, of whom 14,443 (42.0%) were non-lean. Annual admissions increased sharply in lean MASLD patients (5339 in 2016 to 8247 in 2020) compared to non-lean MASLD (2273 to 3635). Non-lean MASLD patients experienced higher inflation-adjusted hospital charges ($5,324.01; 95% CI: $3,273.42–$7,374.61, P < 0.01), a longer length of stay ((adjusted increase 0.25 days; 95% CI: 0.12–0.39, P < 0.05), increased odds of respiratory failure (aOR 4.60; 95% CI: 2.24–9.46, P <0.01), sepsis (aOR 1.11; 95% CI: 1.00–1.23, P = 0.04), cholecystectomy (aOR 2.05; 95% CI: 1.92–2.19, P < 0.01), ERCP (aOR of 1.42 95% CI: 1.11–1.82, P = 0.01). Mortality did not differ significantly. (aOR 0.90; 95% CI: 0.69–1.17, P = 0.43). Conclusion: Our study suggests that lean MASLD patients with AP may experience a higher rate of hospital admissions and distinct clinical profiles, including a similar mortality risk compared to non-lean MASLD patients, indicating a complex relationship between AP outcomes and MASLD beyond BMI. Acute Pancreatitis Metabolic-dysfunction Associated Steatotic Liver Disease Obesity Lean Clinical Outcomes Figures Figure 1 Figure 2 INTRODUCTION Acute pancreatitis (AP) is a complex disease process characterized by pancreatic autodigestion resulting from pancreatic acinar cell damage. The inflammatory response cascade can lead to increased vascular permeability, intravascular volume depletion, multiorgan dysfunction, and death.( 1 ) The global incidence of AP has been steadily increasing, with significant contributions from Western countries. ( 2 ) The annual hospitalization rates of AP in the United States (US) have seen a gradual increase with substantial short and long-term clinical and economic ramifications, which are further compounded by increasing disease severity.( 3 , 4 )The total financial burden of AP in the US doubled to $ 7.7 billion in 2016 compared to $ 3.9 billion in 2006.( 3 ) There has been a reduction in the case fatality rate of pancreatitis; however, the overall population mortality rate has stagnated, which may be attributed to the increase in incidence and improvement in clinical case management.( 5 ) Host characteristics (BMI, age, co-morbidities, etc.), risk stratification scoring systems, and clinical and laboratory evidence of response to therapy have been shown to predict outcomes in AP.( 6 ) The term metabolic dysfunction-associated steatotic liver disease (MASLD) was introduced to replace non-alcoholic fatty liver disease (NAFLD) by the multi-society Delphi consensus in 2023 to characterize better the synergistic roles of the metabolic syndrome in the disease etiology and enhance case identification and management( 7 ). Similar to the increasing global trend of AP, a systematic review and meta-analysis by Riazi et al.( 8 ) found a significant increase in the worldwide prevalence of MASLD from 25.5% in 2005 to 37.8% in 2016.( 8 ) Despite the significant association between increased body mass index (BMI) and metabolic syndrome, up to 26% of patients with MASLD fall into the lean/non-obese category (WHO definition of obesity: BMI > 25kg/m2 in Asia, BMI > 30kg/m2 in the rest of the world)( 9 ). Despite Obesity and MASLD being associated with increasing mortality and risk of moderate-severe AP,( 10 , 11 ) emerging literature points to comparable or even higher cardiovascular event and all-cause mortality rates in lean/non-obese MASLD patients compared to obese MASLD and lean patients without MASLD.( 12 – 15 ) Vancsa et al.( 11 ), in a post hoc analysis of an international AP registry, found an increased risk of moderate to severe AP (OR 1.43, CI 1.09-1,89), local and systemic complications in patients with MASLD compared to those without. They found no difference in in-hospital mortality between both groups. Similar results were found by Mikolasevic et al. ( 16 ) in a retrospective single-center study, which showed an increased incidence of moderate and severe AP, organ dysfunction, and local complications in the NAFLD group without a statistically significant difference in mortality. However, no studies have directly compared clinical outcomes, including mortality, in patients with lean versus non-lean MASLD presenting with AP. This study aims to fill that gap by evaluating and comparing the clinical outcomes of acute pancreatitis in these two distinct MASLD phenotypes. This study's findings can enhance risk stratification and inform tailored management strategies based on the MASLD phenotype. METHODS Study setting The National Inpatient Sample (NIS) database, provided by the Healthcare Cost and Utilization Project (HCUP) of the Agency for Healthcare Research and Quality, was utilized for this study. The NIS complies with the Health Insurance Portability and Accountability Act (HIPAA), ensuring patient, physician, and hospital privacy. As the largest inpatient database in the United States, the NIS comprises data from hospital discharges nationwide, representing over 40 million hospitalizations annually. This dataset offers a comprehensive view of clinical and resource utilization across the American population, including over 100 clinical and non-clinical outcome data points for each hospital stay, such as primary and secondary diagnoses, baseline population characteristics, patient comorbidity measures, total charges (US $ ), and hospital characteristics. The NIS database from 2016 onwards uses the International Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS). This system classifies codes into primary and secondary diagnoses, including all additional ICD-10 codes that do not represent the primary diagnosis. Study Population The NIS data from 2016 to 2020 were examined for all adult (≥ 18 years) hospitalized patients with a primary discharge diagnosis of AP and a secondary diagnosis of MASLD ICD-10-CM. Patients were then categorized based on obesity and overweight status, according to the ICD-10-CM codes, to compare outcomes between lean MASLD and non-lean MASLD individuals with AP. Lean MASLD was operationalized as a subset of non-obese MASLD with a BMI < 25 kg/m². We excluded patients with an ICD-10-CM history of alcohol-related liver disease and viral hepatitis. Outcomes The Primary outcome was in-hospital mortality. Secondary outcomes included a spectrum of complications, all based on ICD-10-CM, including organ failures (e.g., acute kidney injury, acute respiratory distress syndrome), systemic infections (e.g., sepsis, any bacterial infection), metabolic disturbances, venous thromboembolism, gastrointestinal complications, and the necessity for various medical interventions, based on ICD-10-PCS (e.g., mechanical ventilation, parenteral nutrition, imaging tests, and specific procedures related to pancreatitis management). Hospital-stay metrics and healthcare costs, adjusted for inflation to 2020 dollars, were also analyzed. Additionally, patients with a history of cirrhosis were evaluated for decompensating outcomes based on ICD-10-CM (Variceal bleeding, hepatorenal syndrome, hepatic encephalopathy, and ascites). The analysis adjusted results for baseline demographics, comorbidities, Charlson Comorbidity Index (CCI), income quartile, and hospital characteristics. Data were presented as population-weighted means ± standard error for continuous variables and population-weighted percentages ± standard error for categorical variables. Differences between lean MASLD and non-lean MASLD patients were evaluated using univariate and multivariable analyses, with continuous variables compared using t-tests and categorical variables using chi-square tests. Logistic and linear regression analyses assessed the association between obesity and in-hospital mortality, length of stay, and hospital charges, among other outcomes. Adjustments were made for age, gender, race, Charlson Comorbidity Index (CCI), median income quartile, and hospital characteristics in multivariable models. Inflation adjustments for cost analysis were made to 2020 dollars using the appropriate economic deflators. All statistical analyses were conducted using SAS software (version 9.4, SAS Institute, Cary, NC), considering the complex sampling design of the NIS and applying appropriate weights in the statistical models. RESULTS Patient Characteristics and Hospital Data Our study analyzed a cohort of 34,388 hospitalized patients with AP and MASLD, of whom 14,443 (42.0%) were categorized as non-lean MASLD and 19,945 (58.0%) as lean MASLD. The mean age of non-lean MASLD patients was significantly lower than that of lean MASLD patients (48.1 ± 15.18 vs. 52.1 ± 16.03 years, P < 0.01). The gender distribution differed between groups, with a higher proportion of females in the non-lean MASLD group (53.7%) compared to the lean MASLD group (49.4%) (P < 0.01). Regarding race/ethnicity, Hispanic patients were more prevalent in the non-lean MASLD group (21.5% vs. 19.0%, P < 0.01), while the distribution of White (62.0% vs. 62.5%, P = 0.22) and Black patients (10.2% vs. 10.0%, P = 0.22) remained similar across groups. Non-lean MASLD patients experienced higher hospitalization charges (mean $ 61,964 vs. $ 55,798, P < 0.01) and a slightly longer length of stay (5.2 days vs. 4.9 days, P < 0.01). Differences in insurance coverage and socioeconomic status were also observed, with a higher proportion of Medicaid recipients in the non-lean MASLD group (22.1% vs. 20.1%, P < 0.01) and a greater representation of lower-income quartiles (< $ 38,999/year) among non-lean MASLD patients (31.5% vs. 29.4%, P < 0.01). The distribution of hospitalizations showed notable regional differences. The South was the most common location for both subgroups, with 42% of lean MASLD patients and 40.2% of non-lean MASLD patients hospitalized in this region. Furthermore, the majority of hospitalizations occurred in teaching hospitals, accounting for 68.3% of cases in the non-lean MASLD subgroup. Detailed demographic and hospital characteristics are summarized in Table 1 . Table 1 Characteristics of Hospitalized US Adults with AP and MASLD, Categorized by Obese/Non-Obese MASLD Non-Lean MASLD No (N = 19945) Yes (N = 14443) Total (N = 34388) P-value Age in years at admission < 0.01 1 Mean (SD) 52.1 (16.03) 48.1 (15.18) 50.4 (15.80) Median 52.0 48.0 50.0 Range 18.0, 90.0 18.0, 90.0 18.0, 90.0 Gender < 0.01 2 Male 10089 (50.6%) 6684 (46.3%) 16773 (48.8%) Female 9854 (49.4%) 7754 (53.7%) 17608 (51.2%) Race /Ethnicity < 0.01 2 White 12158 (62.5%) 8749 (62.0%) 20907 (62.3%) Black 1950 (10.0%) 1437 (10.2%) 3387 (10.1%) Hispanic 3689 (19.0%) 3029 (21.5%) 6718 (20.0%) Asian or Pacific Islander 752 (3.9%) 309 (2.2%) 1061 (3.2%) Native American 153 (0.8%) 108 (0.8%) 261 (0.8%) Other 741 (3.8%) 471 (3.3%) 1212 (3.6%) Total charges ($) < 0.01 1 N 19811 14318 34129 Mean (SD) 55798.7 (86550.82) 61964.8 (93357.61) 58385.6 (89519.91) Median 35035.0 40165.5 37045.0 Range 589.0, 2427175.0 298.0, 3810065.0 298.0, 3810065.0 Length of stay (days) < 0.01 1 N 19945 14443 34388 Mean (SD) 4.9 (5.68) 5.2 (6.11) 5.0 (5.86) Median 4.0 4.0 4.0 Range 0.0, 198.0 0.0, 228.0 0.0, 228.0 Primary Payer Source < 0.01 2 Private Insurance 5783 (29.0%) 3325 (23.0%) 9108 (26.5%) Medicaid 4001 (20.1%) 3187 (22.1%) 7188 (20.9%) Medicare 7659 (38.5%) 6215 (43.1%) 13874 (40.4%) Other Payment Source 1683 (8.5%) 1182 (8.2%) 2865 (8.3%) Self-Pay 170 (0.9%) 118 (0.8%) 288 (0.8%) No Charge 613 (3.1%) 402 (2.8%) 1015 (3.0%) Median household income ($) < 0.01 2 63 000 3788 (19.3%) 2414 (16.9%) 6202 (18.3%) Hospital Size 0.96 2 Small 3611 (22.2%) 2579 (22.1%) 6190 (22.1%) Medium 4891 (30.0%) 3504 (30.0%) 8395 (30.0%) Large 7784 (47.8%) 5605 (48.0%) 13389 (47.9%) Region of hospital < 0.01 2 Northeast 2403 (14.8%) 1564 (13.4%) 3967 (14.2%) Midwest, 3239 (19.9%) 2647 (22.6%) 5886 (21.0%) South 6832 (42.0%) 4699 (40.2%) 11531 (41.2%) West 3812 (23.4%) 2778 (23.8%) 6590 (23.6%) Location of hospital 0.38 2 Rural 1028 (8.1%) 698 (7.8%) 1726 (8.0%) Urban 11599 (91.9%) 8235 (92.2%) 19834 (92.0%) Location/Teaching status 0.22 2 Rural 1335 (8.2%) 901 (7.7%) 2236 (8.0%) Urban Non-Teaching 3867 (23.7%) 2736 (23.4%) 6603 (23.6%) Urban Teaching 11084 (68.1%) 8051 (68.9%) 19135 (68.4%) Teaching status of hospital 0.05 2 Non-teaching 4164 (33.0%) 2833 (31.7%) 6997 (32.5%) Teaching 8463 (67.0%) 6100 (68.3%) 14563 (67.5%) Year of Admission < 0.05 2 2016 2923 (14.7%) 1929 (13.4%) 4852 (14.1%) 2017 3022 (15.2%) 2140 (14.8%) 5162 (15.0%) 2018 3267 (16.4%) 2355 (16.3%) 5622 (16.3%) 2019 3415 (17.1%) 2509 (17.4%) 5924 (17.2%) 2020 7318 (36.7%) 5510 (38.1%) 12828 (37.3%) Charlson index < 0.01 1 N 16286 11688 27974 Mean (SD) 2.2 (1.60) 2.3 (1.55) 2.2 (1.58) Median 2.0 2.0 2.0 Range 0.0, 13.0 0.0, 14.0 0.0, 14.0 Tobacco Smoking , n (%) < 0.01 2 No 15522 (77.8%) 11870 (82.2%) 27392 (79.7%) Yes 4423 (22.2%) 2573 (17.8%) 6996 (20.3%) Cirrhosis , n (%) 0.01 2 No 18884 (94.7%) 13763 (95.3%) 32647 (94.9%) Yes 1061 (5.3%) 680 (4.7%) 1741 (5.1%) 1 Kruskal-Wallis p-value; 2 Chi-Square p-value; Figure 1 depicts the annual hospital admissions for AP in patients with MASLD, stratified by lean/non-lean status from 2016 to 2020. The trend analysis over the five years reveals a consistent year-over-year increase in admissions for both lean and non-lean MASLD patients. Notably, admissions for lean MASLD patients showed a more pronounced rise. Clinical Outcomes Table 2 presents the results of clinical outcomes comparing AP outcomes between non-lean and lean MASLD patients. Several significant associations between obesity and AP complications were observed. Respiratory failure was significantly more common in non-lean MASLD patients, with an adjusted OR of 4.60 (95% CI: 2.24–9.46, P < 0.01). Similarly, sepsis showed a statistically significant increase in non-lean MASLD patients, with an adjusted OR of 1.11 (95% CI: 1.00–1.23, P = 0.04). Table 2 Association between non-lean MASLD and outcomes of AP in US Hospitalized Adults. outcome Unadjusted Adjusted OR (95% CI) P-value OR (95%CI) P-Value Cardiac Arrest 0.83(0.58–1.18) 0.29 0.91(0.60–1.40) 0.67 AKI 0.99(0.93–1.05) 0.77 0.95(0.88–1.02) 0.14 Respiratory Failure 2.51(1.36–4.62) < 0.01 4.60(2.24–9.46) < 0.01 Sepsis 1.07(0.98–1.16) 0.13 1.11(1.00-1.23) 0.04 Ileus 1.03(0.92–1.15) 0.58 1.06(0.93–1.20) 0.41 Acute MI 0.95(0.71–1.28) 0.75 1.21(0.86–1.71) 0.28 Shock 1.10(0.88–1.38) 0.40 1.11(0.85–1.46) 0.44 All Venous Thrombosis 0.75(0.64–0.89) < 0.01 0.70(0.57–0.84) < 0.01 PE 1.01(0.71–1.45) 0.95 1.16(0.76–1.76) 0.48 DVT 1.05(0.72–1.51) 0.81 1.22(0.79–1.86) 0.37 Portal Vein Thrombosis 0.65(0.52–0.80) < 0.01 0.64(0.50–0.82) < 0.01 GI Bleeding 0.82(0.69–0.98) 0.03 0.84(0.69–1.03) 0.09 Decompensated Liver Events 0.75(0.68–0.83) < 0.01 0.76(0.67–0.85) < 0.01 Abdominal CT 0.97(0.78–1.22) 0.82 1.10(0.85–1.43) 0.45 Intubation /ARDS 1.00(0.85–1.19) 0.96 1.08(0.89–1.32) 0.42 Paracentesis 0.83(0.69–0.99) 0.04 0.88(0.71–1.10) 0.26 Cholecystectomy 1.69(1.60–1.78) < 0.01 2.05(1.92–2.19) < 0.01 Percutaneous Cholecystostomy 1.04(0.23–4.63) 0.96 0.52(0.04–7.31) 0.63 Cholangiogram 1.45(1.35–1.57) < 0.01 1.72(1.57–1.87) < 0.01 EGD 1.04(0.96–1.13) 0.30 1.10(1.00-1.21) 0.03 Transfusion 0.74(0.64–0.86) < 0.01 0.84(0.71–1.01) 0.07 TPN 1.34(1.10–1.63) < 0.01 1.25(1.00-1.57) 0.05 Pancreatic Drainage 1.03(0.80–1.32) 0.82 1.12(0.84–1.50) 0.44 ERCP 1.20(0.97–1.49) 0.10 1.42(1.11–1.82) 0.01 MRCP 0.41(0.22–0.79) 0.01 0.40(0.18–0.89) 0.02 MACE 1.07(1.00-1.15) 0.06 1.19(1.05–1.35) < 0.01 Mortality 0.76(0.61–0.94) 0.01 0.90(0.69–1.17) 0.43 Continuous Outcomes Inflation-Adjusted Charges( $ ) 6162.31(4238.40-8086.21) < 0.01 5324.01(3273.42-7374.61) < 0.01 Length of Stay (Days) 0.39(0.26–0.51) < 0.01 0.25(0.12–0.39) < 0.01 Sub Analysis Of Outcomes among Patients with Cirrhosis Decompensated Liver Events 0.75(0.61–0.93) 0.01 0.78(0.61-1.00) 0.05 Mortality 1.06(0.63–1.77) 0.83 1.10(0.61-2.00) 0.92 Variceal bleed 3.14(0.78–12.60) 0.11 4.05(0.80-20.61) 0.09 Hepatorenal Syndrome 1.44(0.87–2.38) 0.16 1.25(0.67–2.34) 0.49 Hepatic Encephalopathy - - - - Ascites 0.70(0.56–0.87) < 0.01 0.735(0.57–0.94) 0.02 *Adjusted for age, gender, race, median income quartile, CCI, year of admission, day of admission and hospital characteristics AKI = Acute Kidney Injury, ARDS = Acute Respiratory Distress Syndrome, SIRS = Systemic Inflammatory Response Syndrome, CT = Computed Tomography, MRCP = Magnetic Resonance Cholangiopancreatography, ERCP = Endoscopic Retrograde Cholangiopancreatography, EGD = Esophagogastroduodenoscopy, GI Bleeding = Gastrointestinal Bleeding, TPN = Total Parenteral Nutrition, CCY = Cholecystectomy, MACE = Major Adverse Cardiovascular Events, PC = Percutaneous Cholecystostomy, PTHC = Percutaneous Transhepatic Cholangiogram In contrast, thromboembolic events showed a more nuanced pattern. Non-lean MASLD patients had significantly lower odds of all venous thrombosis (adjusted OR 0.70; 95% CI: 0.57–0.85, P < 0.01), particularly portal vein thrombosis (adjusted OR 0.64; 95% CI: 0.50–0.82, P < 0.01). However, the two groups had no significant differences in the pulmonary embolism or deep vein thrombosis rates. When evaluating liver-related outcomes, decompensated liver disease - including variceal bleeding, ascites, hepatic encephalopathy, or hepatorenal syndrome - was significantly less frequent in non-lean MASLD patients (adjusted OR 0.76; 95% CI: 0.67–0.85, P < 0.01). On procedural interventions, non-lean MASLD patients were significantly more likely to undergo cholecystectomy, with an adjusted OR of 2.05 (95% CI: 1.92–2.19, P < 0.01), as well as cholangiography, with an adjusted OR of 1.72 (95% CI: 1.57–1.87, P < 0.01). Furthermore, Endoscopic retrograde cholangiopancreatography (ERCP) was more common among non-lean MASLD patients, with an adjusted OR of 1.42 (95% CI: 1.11–1.82, P = 0.01). Similarly, esophagogastroduodenoscopy (EGD) was slightly more likely in non-lean MASLD patients (adjusted OR 1.10; 95% CI: 1.01–1.21, P = 0.03), whereas magnetic resonance cholangiopancreatography (MRCP) was less frequently performed in this group (adjusted OR 0.40; 95% CI: 0.18–0.89, P = 0.02). Percutaneous cholecystostomy was not significantly different between groups (adjusted OR 0.52; 95% CI: 0.04–7.31, P = 0.63). The likelihood for total parenteral nutrition (TPN) was slightly higher in non-lean MASLD patients but did not reach statistical significance (adjusted OR 1.25; 95% CI: 1.00–1.57, P = 0.05). Despite the differences in complications and interventions, mortality rates were not significantly different between non-lean and lean MASLD patients, with an adjusted OR of 0.90 (95% CI: 0.69–1.17, P = 0.43). There was no difference in the likelihood of cardiac arrest (adjusted OR 0.91; 95% CI: 0.60–1.39, P = 0.67), acute myocardial infarction (adjusted OR 1.21; 95% CI: 0.86–1.71, P = 0.28), acute kidney injury (adjusted OR 0.95; 95% CI: 0.88–1.02, P = 0.14), shock (adjusted OR 1.11; 95% CI: 0.85–1.46, P = 0.44) or ileus (adjusted OR 1.05; 95% CI: 0.93–1.20, P = 0.41). Continuous outcomes further demonstrated increased healthcare utilization in non-lean MASLD patients. Inflation-adjusted hospital charges were significantly higher for non-lean MASLD patients by an average of $ 5,324 (95% CI: $ 3,273– $ 7,375, P < 0.01). Non-lean MASLD patients had an increased length of hospital stay, with an adjusted increase of 0.25 days (95% CI: 0.12–0.39, P < 0.01). Subgroup Analysis of Cirrhosis Patients Among patients with cirrhosis, trends were observed for decompensating events. Non-lean MASLD patients had lower odds of decompensated liver disease, with an adjusted OR of 0.78 (95% CI: 0.61–1.00, P = 0.05). Ascites was significantly less likely in non-lean MASLD patients with cirrhosis, with an adjusted OR of 0.74 (95% CI: 0.57–0.94, P = 0.02). Variceal bleeding was comparable in lean and non-lean MASLD patients (adjusted OR 4.05; 95% CI: 0.80–20.61, P = 0.09). Similarly, hepatorenal syndrome showed a slight but non-significant increase in non-lean MASLD patients (adjusted OR 1.25; 95% CI: 0.67–2.32, P = 0.49). Mortality did not differ significantly in this subgroup (adjusted OR 1.10; 95% CI: 0.61–2.00, P = 0.92). DISCUSSION This study aimed to evaluate and compare clinical outcomes of AP in patients with lean versus non-lean MASLD—a distinction that, to our knowledge, has not been previously explored. While prior literature has established MASLD as a risk factor for increased AP severity, it remains unclear whether the lean phenotype carries similar or even greater risk than its non-lean counterpart. Given the rising prevalence of both AP and MASLD, along with emerging evidence highlighting the distinct metabolic profiles of lean MASLD patients, this investigation addresses an essential gap in the literature and offers clinically relevant insights. In this nationally representative cohort, we found that lean MASLD accounted for the majority of AP hospitalizations and was associated with a higher likelihood of decompensated liver events. In contrast, non-lean MASLD was associated with an increased risk of sepsis, respiratory failure, cholecystectomy, greater healthcare resource utilization, and longer length of hospital stay. Notably, there was no difference in in-hospital mortality between the two groups. Disease severity and risk stratification are essential components of AP disease management. Several available risk-scoring systems help determine the appropriate hospital level of care and predict outcomes, including organ dysfunction and mortality.( 1 ) Increasing BMI has been associated with mortality in AP, despite its absence as a variable of interest in AP risk scoring systems, including the APACHE II, Ranson, and BISAP.( 1 , 10 ) Obesity was associated with a 3-fold increase in mortality in AP in a meta-analysis involving 19 studies by Dobzai et al.( 10 ) Obesity and its attendant increase in peripancreatic fat accumulation exacerbates pancreatic injury-induced inflammatory dysregulation, tissue necrosis, peripancreatic infection/sepsis, respiratory failure, and multiorgan dysfunction leading to the observed increase in mortality.( 17 ) Patients with lean MASLD are known to have increased visceral adipocyte mass and tissue inflammation, insulin resistance, and sarcopenia and thus share a similar cardiometabolic risk profile compared with their non-lean counterparts.( 12 , 18 , 19 ) The complex interactions between cardiometabolic risk profiles of patients with lean MASLD and AP physiology may influence mortality outcomes irrespective of BMI. The risk of all-cause mortality and cardiovascular mortality may be similar ( 15 ) or even higher ( 12 , 20 , 21 ) in lean MASLD compared to patients with non-lean MASLD. A prospective single-center database analysis from England of patients with admissions for severe AP complicated by organ failure found an increase in mortality in patients with sarcopenia compared to those without.( 22 ) A fraction of the lean MASLD population in our study may represent patients with overweight or obesity who have experienced a reduction in BMI from significant weight and muscle loss/sarcopenia from poor glycemic control, reduced physical activity, and advanced MASLD-associated chronic liver disease.( 18 , 19 , 23 ) Patients with cirrhosis in the lean-MASLD were more likely to have overall decompensated liver events. This observation was driven by the increased likelihood of ascites in the lean-MASLD cirrhosis cohort, as no significant difference was observed in the other components of decompensated cirrhosis. Ha et al.( 15 ) in a meta-analysis involving 10 cohort studies identified a comparable risk of decompensated liver events and an increased risk of liver-related mortality in patients with lean MASLD. A longitudinal study involving 169303 patients from the French national Constances cohort identified an increased risk of advanced fibrosis, liver-related events, and all-cause mortality in the lean MASLD group. ( 23 ) Simons-Linares et al. ( 24 ) found an increased risk of in-patient mortality in patients with AP and cirrhosis compared to patients without cirrhosis. Patients with decompensated cirrhosis had higher risks of in-patient mortality among the cirrhosis group.( 24 ) However, we found no difference in mortality between both cirrhosis groups despite an increase in overall decompensating events in the lean-MASLD group. Patients with non-lean MASLD had a 36% lower risk of developing portal vein thrombosis (PVT). However, there was no difference in DVT and PE between both groups. In a retrospective study involving patients with AP, patients with obesity were found to have a 17% lower risk of developing PVT. ( 25 ) A meta-analysis involving 22 studies by Li et al.( 26 ) identified metabolic dysfunction, including non-alcoholic fatty liver disease, diabetes mellitus, and hypercholesterolemia, to be associated with increased risk of PVT in patients with cirrhosis irrespective of BMI. The pathophysiologic mechanisms of PVT as a complication of AP involve an interplay of the proximity of the portal vein to the pancreas and vascular endothelial dysfunction from inflammatory and coagulation cascade activation. ( 27 ) Patients with non-lean MASLD were more likely to have sepsis and respiratory failure during hospitalization. Gajendran et al. ( 28 ) in a retrospective study of hospitalized patients with AP, identified sepsis as the strongest predictor of acute respiratory failure (OR 15; 95% CI 14.7–15.4). Obesity, chronic lung disease, and cardiogenic shock were other notable predictors of respiratory failure.( 28 ) Our findings have important practice implications, as non-lean MASLD patients may be more susceptible to volume-associated respiratory failure with aggressive intravenous fluid resuscitation. Obesity is a known risk factor for sepsis. Possible mechanisms include a dysregulated immune response, effects of obesity-related comorbidities, impaired micro/macro-circulation, and impaired wound healing. ( 29 ) Poor glycemic control from insulin resistance and stress hyperglycemia in AP has been associated with an increasing risk of extra-pancreatic abdominal infections and infected pancreatic necrosis.( 30 ) Compared with sterile necrosis, patients with infected pancreatic necrosis have a higher rate of mortality from sepsis and multi-organ failure in AP.( 6 ) Obesity restricts chest wall and diaphragmatic movements, negatively affecting lung volumes and capacities. The development of physiologic pulmonary shunts leads to respiratory failure and increasing intubation requirements, which can further aggravate organ dysfunction in AP. ( 17 ) Conversely, another retrospective study involving 359 patients admitted to a teaching hospital with AP in Denmark identified age and smoking as predictors of respiratory failure in the early phase of AP with no significant contribution from BMI. ( 31 ) A paradoxical improvement in survival and functional outcomes has been observed in hospitalized patients with sepsis and obesity in some studies( 32 – 34 ). Further studies are needed to evaluate this observation in patients with MASLD and AP. Non-lean MASLD was associated with increased healthcare resource utilization in terms of higher inflation-adjusted hospital charges and increased length of hospital stay. The total financial cost of pancreatitis to the US healthcare system nearly doubled from $ 3.9 billion in 1996 to $ 7.7 billion in 2016, with inpatient care accounting for 75.1% of spending.( 3 ) The rising cost has been attributed to increased hospitalizations despite a relatively stable disease incidence and increased intensity and financial cost of inpatient case management.( 3 ) Our study demonstrated a similar trend of increasing hospitalizations in both groups, with a more pronounced rise in the lean MASLD group. Intensive care unit (ICU) stay, biliary etiology of AP, peripancreatic necrotic fluid collections, and necrosectomy are significant determinants of hospitalization costs in patients with AP.( 35 , 36 ) The increased length of stay and the likelihood of sepsis, respiratory failure, and increased utilization of investigations and interventions, including cholangiogram, cholecystectomy, and ERCP in the non-lean MASLD group, could account for their increased healthcare resource utilization in our study. Despite dataset limitations on the etiology and severity of AP in our cohort, patients in the non-lean MASLD group’s increased utilization of the abovementioned interventions could suggest a higher frequency of biliary pancreatitis and higher hospital level of care. A single tertiary center prospective cohort study by Singh et al. ( 37 ) involving 231 patients with AP identified the performance of cholecystectomy and ongoing pancreatitis-related symptoms as the main determining factors for increased length of hospital stay ( 37 ). Intolerance to oral feeding, a fasting period of 3 or more days, and the performance of ERCP was independently associated with increased length of hospital stay in patients with AP in a study by Francisco et al ( 38 ). Strengths and Limitations Our study has several strengths and limitations. A major strength of this study is the use of the NIS. This large, nationally representative database enables comprehensive analysis of AP hospitalizations among patients with MASLD across the United States. The dataset’s breadth—capturing patient characteristics, hospital factors, and comorbidities—provides valuable insight into epidemiologic trends, complications, and healthcare utilization at a population level. However, the retrospective nature of the NIS introduces limitations. The database lacks granular data on MASLD severity, disease duration, medication use, and laboratory parameters. The etiology, severity, and recurrence of AP could not be determined. The use of ICD codes carries the risk of misclassification, and because the unit of analysis is hospitalizations, repeat admissions for the same patient may inflate event rates. Additionally, the NIS is limited to inpatient encounters, precluding post-discharge outcomes and long-term prognosis assessment. Future Research Future studies should aim to clarify the pathophysiologic mechanisms underlying the differential outcomes observed between lean and non-lean MASLD patients with AP, focusing on the roles of sarcopenia, visceral adiposity, and insulin resistance. Prospective studies incorporating clinical, laboratory, and imaging data are needed to better characterize MASLD phenotypes and their influence on AP severity and progression. Additionally, longitudinal research is warranted to evaluate post-discharge outcomes and long-term complications. Given the observed differences in healthcare utilization, future investigations should also assess the cost-effectiveness of tailored management strategies across MASLD phenotypes, which may inform resource allocation and clinical guidelines. CONCLUSIONS Our study revealed increased acute pancreatitis hospitalizations and distinct clinical profiles, including higher rates of decompensating liver events in lean-MASLD patients compared to non-lean MASLD patients. Despite an increase in healthcare resource utilization and incidence of sepsis and respiratory failure in patients with non-lean MASLD admitted with AP compared with the lean cohort, no difference in in-patient mortality was observed between both groups. These findings suggest a complex relationship between the pathophysiology of AP and MASLD beyond BMI. Future calls for incorporating MASLD into prognostic tools of AP should include increased sensitization about lean-MASLD and the need for equal vigilance regardless of BMI to ensure favorable outcomes. Declarations Author Contribution Author Contributions: Prince Addo Ameyaw participated in the manuscript's concept, research design, writing, final revision, and formatting.Sarpong Boateng participated in the manuscript's concept and research design, data analysis, writing, and formatting.Yussif Issaka, Amita Ashokkumar Kasar, and Erika Sandra Ackah participated in the writing and formatting of the manuscriptYazan A. Al-Ajlouni participated in the writing and final revision of the manuscriptBasile Njei was the supervising investigator and participated in the manuscript's concept and research design, data analysis, and final manuscript revision. References Mederos MA, Reber HA, Girgis MD. Acute Pancreatitis: A Review. JAMA. 2021;325(4):382-90. Iannuzzi JP, King JA, Leong JH, Quan J, Windsor JW, Tanyingoh D, et al. Global Incidence of Acute Pancreatitis Is Increasing Over Time: A Systematic Review and Meta-Analysis. Gastroenterology. 2022;162(1):122-34. Ahmed NS, Forbes N, Stukalin I, Singh S, Shaheen AA, Ma C, et al. Population-based Trends in Healthcare Utilization and National Healthcare Spending on Pancreatitis in North America. Gastroenterology. 2021;161(5):1698-701 e5. Pokras S, Ray M, Zheng S, Ding Y, Chen CC. The Short- and Long-Term Burden of Acute Pancreatitis in the United States: A Retrospective Cohort Study. Pancreas. 2021;50(3):330-40. Ingraham NE, King S, Proper J, Siegel L, Zolfaghari EJ, Murray TA, et al. Morbidity and Mortality Trends of Pancreatitis: An Observational Study. Surg Infect (Larchmt). 2021;22(10):1021-30. Tenner S, Baillie J, DeWitt J, Vege SS, American College of G. American College of Gastroenterology guideline: management of acute pancreatitis. Am J Gastroenterol. 2013;108(9):1400-15; 16. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Hepatology. 2023;78(6):1966-86. Riazi K, Azhari H, Charette JH, Underwood FE, King JA, Afshar EE, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2022;7(9):851-61. Ahadi M, Molooghi K, Masoudifar N, Namdar AB, Vossoughinia H, Farzanehfar M. A review of non-alcoholic fatty liver disease in non-obese and lean individuals. J Gastroenterol Hepatol. 2021;36(6):1497-507. Dobszai D, Matrai P, Gyongyi Z, Csupor D, Bajor J, Eross B, et al. Body-mass index correlates with severity and mortality in acute pancreatitis: A meta-analysis. World J Gastroenterol. 2019;25(6):729-43. Vancsa S, Sipos Z, Varadi A, Nagy R, Ocskay K, Juhasz FM, et al. Metabolic-associated fatty liver disease is associated with acute pancreatitis with more severe course: Post hoc analysis of a prospectively collected international registry. United European Gastroenterol J. 2023;11(4):371-82. Ahmed OT, Gidener T, Mara KC, Larson JJ, Therneau TM, Allen AM. Natural History of Nonalcoholic Fatty Liver Disease With Normal Body Mass Index: A Population-Based Study. Clin Gastroenterol Hepatol. 2022;20(6):1374-81 e6. Zou B, Yeo YH, Nguyen VH, Cheung R, Ingelsson E, Nguyen MH. Prevalence, characteristics and mortality outcomes of obese, nonobese and lean NAFLD in the United States, 1999-2016. J Intern Med. 2020;288(1):139-51. Chrysavgis L, Ztriva E, Protopapas A, Tziomalos K, Cholongitas E. Nonalcoholic fatty liver disease in lean subjects: Prognosis, outcomes and management. World J Gastroenterol. 2020;26(42):6514-28. Ha J, Yim SY, Karagozian R. Mortality and Liver-Related Events in Lean Versus Non-Lean Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis. Clin Gastroenterol Hepatol. 2023;21(10):2496-507 e5. Mikolasevic I, Orlic L, Poropat G, Jakopcic I, Stimac D, Klanac A, et al. Nonalcoholic fatty liver and the severity of acute pancreatitis. Eur J Intern Med. 2017;38:73-8. Katuchova J, Bober J, Harbulak P, Hudak A, Gajdzik T, Kalanin R, et al. Obesity as a risk factor for severe acute pancreatitis patients. Wien Klin Wochenschr. 2014;126(7-8):223-7. Ding C, Chan Z, Magkos F. Lean, but not healthy: the 'metabolically obese, normal-weight' phenotype. Curr Opin Clin Nutr Metab Care. 2016;19(6):408-17. Chan WK. Comparison between obese and non-obese nonalcoholic fatty liver disease. Clin Mol Hepatol. 2023;29(Suppl):S58-S67. Huang S, Bao Y, Zhang N, Niu R, Tian L. Long-term outcomes in lean and non-lean NAFLD patients: a systematic review and meta-analysis. Endocrine. 2023. Ye Q, Zou B, Yeo YH, Li J, Huang DQ, Wu Y, et al. Global prevalence, incidence, and outcomes of non-obese or lean non-alcoholic fatty liver disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2020;5(8):739-52. Farquhar R, Matthews S, Baxter N, Rayers G, Ratnayake CBB, Robertson FP, et al. Sarcopenia and Sarcopenic Obesity on Body Composition Analysis is a Significant Predictor of Mortality in Severe Acute Pancreatitis: A Longitudinal Observational Study. World J Surg. 2023;47(11):2825-33. Nabi O, Lapidus N, Boursier J, de Ledinghen V, Petit JM, Kab S, et al. Lean individuals with NAFLD have more severe liver disease and poorer clinical outcomes (NASH-CO Study). Hepatology. 2023;78(1):272-83. Simons-Linares CR, Romero-Marrero C, Jang S, Bhatt A, Lopez R, Vargo J, et al. Clinical outcomes of acute pancreatitis in patients with cirrhosis. Pancreatology. 2020;20(1):44-50. Chaudhry H, Sohal A, Bains K, Dhaliwal A, Dukovic D, Singla P, et al. Incidence and factors associated with portal vein thrombosis in patients with acute pancreatitis: A United States national retrospective study. Pancreatology. 2023;23(4):350-7. Li J, Wang Q, Yang M, Sun X. Metabolic Disorders and Risk of Portal Vein Thrombosis in Liver Cirrhosis: A Systematic Review and Meta-Analysis. Turk J Gastroenterol. 2022;33(7):541-53. Garg R, Mohammed A, Singh A, Siddiki H, Bhatt A, Sanaka MR, et al. Mortality Trends, Outcomes, and Predictors of Portal Vein Thrombosis in Acute Pancreatitis Patients: A Propensity-Matched National Study. Dig Dis Sci. 2023;68(6):2674-82. Gajendran M, Prakash B, Perisetti A, Umapathy C, Gupta V, Collins L, et al. Predictors and outcomes of acute respiratory failure in hospitalised patients with acute pancreatitis. Frontline Gastroenterol. 2021;12(6):478-86. Huttunen R, Syrjanen J. Obesity and the risk and outcome of infection. Int J Obes (Lond). 2013;37(3):333-40. Jin Y, Tao S, Yu G, Li C, Hu Z, Jiang L. Predictive value of hyperglycemia on infection in critically ill patients with acute pancreatitis. Sci Rep. 2023;13(1):4106. Dombernowsky T, Kristensen MO, Rysgaard S, Gluud LL, Novovic S. Risk factors for and impact of respiratory failure on mortality in the early phase of acute pancreatitis. Pancreatology. 2016;16(5):756-60. Yeo HJ, Kim TH, Jang JH, Jeon K, Oh DK, Park MH, et al. Obesity Paradox and Functional Outcomes in Sepsis: A Multicenter Prospective Study. Crit Care Med. 2023;51(6):742-52. Jagan N, Morrow LE, Walters RW, Plambeck RW, Wallen TJ, Patel TM, et al. Sepsis and the Obesity Paradox: Size Matters in More Than One Way. Crit Care Med. 2020;48(9):e776-e82. Bai L, Huang J, Wang D, Zhu D, Zhao Q, Li T, et al. Association of body mass index with mortality of sepsis or septic shock: an updated meta-analysis. J Intensive Care. 2023;11(1):27. Murata A, Matsuda S, Mayumi T, Okamoto K, Kuwabara K, Ichimiya Y, et al. Multivariate analysis of factors influencing medical costs of acute pancreatitis hospitalizations based on a national administrative database. Dig Liver Dis. 2012;44(2):143-8. Pahomeanu MR, Constantinescu DI, Diaconu IS, Corbu DG, Negreanu L. Acute Pancreatitis-Drivers of Hospitalisation Cost-A Seven-Year Retrospective Study from a Large Tertiary Center. Healthcare (Basel). 2023;11(18). Singh H, Gougol A, Mounzer R, Yadav D, Koutroumpakis E, Slivka A, et al. Which Patients with Mild Acute Pancreatitis Require Prolonged Hospitalization? Clin Transl Gastroenterol. 2017;8(12):e129. Francisco M, Valentin F, Cubiella J, Fernandez-Seara J. Factors related to length of hospital admission in mild interstitial acute pancreatitis. Rev Esp Enferm Dig. 2013;105(2):84-92. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Jul, 2025 Read the published version in Digestive Diseases and Sciences → Version 1 posted Editorial decision: Revision requested 12 Jun, 2025 Reviews received at journal 24 May, 2025 Reviewers agreed at journal 21 May, 2025 Reviewers agreed at journal 21 May, 2025 Reviewers invited by journal 21 May, 2025 Editor assigned by journal 19 May, 2025 Submission checks completed at journal 19 May, 2025 First submitted to journal 19 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-6694877","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":460148060,"identity":"22b233e1-e379-4b0a-a187-400e7c056c56","order_by":0,"name":"Prince Addo Ameyaw","email":"","orcid":"","institution":"Bridgeport Hospital – Yale New Haven Health","correspondingAuthor":false,"prefix":"","firstName":"Prince","middleName":"Addo","lastName":"Ameyaw","suffix":""},{"id":460148062,"identity":"438b576a-3062-4c4c-9358-3a7db75a1054","order_by":1,"name":"Sarpong Boateng","email":"","orcid":"","institution":"Bridgeport Hospital – Yale New Haven Health","correspondingAuthor":false,"prefix":"","firstName":"Sarpong","middleName":"","lastName":"Boateng","suffix":""},{"id":460148063,"identity":"8ae31136-dd71-43c7-9ae2-d1b59ec56235","order_by":2,"name":"Yussif Issaka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYLCCBBsGHiDFzMBQcYCBQYIoLWkwLWcOMPAQpYUhDUwyMzC2EaHF4Eb64w8PEhhk5PsPPzb4Oe9Onr108+HPBQw2+fIOuLTkmEkkJDDwGNxIM07s3fasmEfmWJr0DIY0y40HcGphY0j8AdQiwWB8gHfb4cQeiRwzZh6GwwaGDXgcBrJFvv/454N/54C1GH/GryXBAOwwhgM5xsm8DWAtBtIgLfI4vC955g3ILxJAv+QUG8scA/rlRhrQLwZpBgY4tPAdT3/88UeCjT3QYZsl39TcyWOfkQwMsQobA3kcDlOABAsiLhJABDMD0AqDA9i1YBgF1YJNahSMglEwCkYqAADMr1wy/ejMlgAAAABJRU5ErkJggg==","orcid":"","institution":"Bridgeport Hospital – Yale New Haven Health","correspondingAuthor":true,"prefix":"","firstName":"Yussif","middleName":"","lastName":"Issaka","suffix":""},{"id":460148064,"identity":"c5579429-7200-4883-b6f9-f17ba4ef8340","order_by":3,"name":"Erika Sandra Ackah","email":"","orcid":"","institution":"University of Cape Coast","correspondingAuthor":false,"prefix":"","firstName":"Erika","middleName":"Sandra","lastName":"Ackah","suffix":""},{"id":460148065,"identity":"18d75d82-1254-415a-9907-06ca962f6dcd","order_by":4,"name":"Amita Ashokkumar Kasar","email":"","orcid":"","institution":"Poplar Bluff Regional Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Amita","middleName":"Ashokkumar","lastName":"Kasar","suffix":""},{"id":460148066,"identity":"fd2e6931-417f-46d0-89db-8981208e8b16","order_by":5,"name":"Yazan A. Al-Ajlouni","email":"","orcid":"","institution":"Staten Island University Hospital, New York Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yazan","middleName":"A.","lastName":"Al-Ajlouni","suffix":""},{"id":460148067,"identity":"20a4f7c4-e285-4b8f-a29b-1428d7141b4d","order_by":6,"name":"Basile Njei","email":"","orcid":"","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Basile","middleName":"","lastName":"Njei","suffix":""}],"badges":[],"createdAt":"2025-05-19 04:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6694877/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6694877/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10620-025-09245-y","type":"published","date":"2025-07-26T15:57:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83421555,"identity":"12657764-3af6-4b40-861e-5b35c840c5f3","added_by":"auto","created_at":"2025-05-26 02:08:41","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59087,"visible":true,"origin":"","legend":"\u003cp\u003eYearly Admissions for Acute Pancreatitis with MASLD: This line graph shows the number of admissions for lean and non-lean MASLD patients from 2016 to 2020. It illustrates trends over time for both groups, indicating a steady increase in admissions\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6694877/v1/783ac8ea71b532f911be7bae.jpg"},{"id":83421741,"identity":"df923c91-ecd0-46f9-9bb1-ac862d313121","added_by":"auto","created_at":"2025-05-26 02:16:41","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45695,"visible":true,"origin":"","legend":"\u003cp\u003eAdjusted Outcomes of Hospitalized US Adults with Acute Pancreatitis, obese MASLD vs. non-obese MASLD. The forest plot displays odds ratios (with 95% confidence intervals) for various outcomes associated with obese MASLD in acute pancreatitis patients. An odds ratio greater than 1 suggests a higher risk of the outcome in obese patients, while an odds ratio less than 1 suggests a lower risk, when compared to non-obese MASLD patients.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6694877/v1/4f5a9f2d99745ef39f508016.jpg"},{"id":87756702,"identity":"83c03430-893d-43bd-8612-ade851cf5e9b","added_by":"auto","created_at":"2025-07-28 16:07:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1210702,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6694877/v1/eb698fb9-f6fd-4d37-92e8-002e9be5efc3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eOutcomes of Acute Pancreatitis in Lean Vs. Non-Lean Metabolic Dysfunction-Associated Steatotic Liver Disease (Masld) Patients: A Nationwide Analysis \u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAcute pancreatitis (AP) is a complex disease process characterized by pancreatic autodigestion resulting from pancreatic acinar cell damage. The inflammatory response cascade can lead to increased vascular permeability, intravascular volume depletion, multiorgan dysfunction, and death.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The global incidence of AP has been steadily increasing, with significant contributions from Western countries. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The annual hospitalization rates of AP in the United States (US) have seen a gradual increase with substantial short and long-term clinical and economic ramifications, which are further compounded by increasing disease severity.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)The total financial burden of AP in the US doubled to \u003cspan\u003e$\u003c/span\u003e7.7\u0026nbsp;billion in 2016 compared to \u003cspan\u003e$\u003c/span\u003e3.9\u0026nbsp;billion in 2006.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) There has been a reduction in the case fatality rate of pancreatitis; however, the overall population mortality rate has stagnated, which may be attributed to the increase in incidence and improvement in clinical case management.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eHost characteristics (BMI, age, co-morbidities, etc.), risk stratification scoring systems, and clinical and laboratory evidence of response to therapy have been shown to predict outcomes in AP.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) The term metabolic dysfunction-associated steatotic liver disease (MASLD) was introduced to replace non-alcoholic fatty liver disease (NAFLD) by the multi-society Delphi consensus in 2023 to characterize better the synergistic roles of the metabolic syndrome in the disease etiology and enhance case identification and management(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Similar to the increasing global trend of AP, a systematic review and meta-analysis by Riazi et al.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) found a significant increase in the worldwide prevalence of MASLD from 25.5% in 2005 to 37.8% in 2016.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) Despite the significant association between increased body mass index (BMI) and metabolic syndrome, up to 26% of patients with MASLD fall into the lean/non-obese category (WHO definition of obesity: BMI\u0026thinsp;\u0026gt;\u0026thinsp;25kg/m2 in Asia, BMI\u0026thinsp;\u0026gt;\u0026thinsp;30kg/m2 in the rest of the world)(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Despite Obesity and MASLD being associated with increasing mortality and risk of moderate-severe AP,(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) emerging literature points to comparable or even higher cardiovascular event and all-cause mortality rates in lean/non-obese MASLD patients compared to obese MASLD and lean patients without MASLD.(\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) Vancsa et al.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), in a post hoc analysis of an international AP registry, found an increased risk of moderate to severe AP (OR 1.43, CI 1.09-1,89), local and systemic complications in patients with MASLD compared to those without. They found no difference in in-hospital mortality between both groups. Similar results were found by Mikolasevic et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) in a retrospective single-center study, which showed an increased incidence of moderate and severe AP, organ dysfunction, and local complications in the NAFLD group without a statistically significant difference in mortality. However, no studies have directly compared clinical outcomes, including mortality, in patients with lean versus non-lean MASLD presenting with AP. This study aims to fill that gap by evaluating and comparing the clinical outcomes of acute pancreatitis in these two distinct MASLD phenotypes. This study's findings can enhance risk stratification and inform tailored management strategies based on the MASLD phenotype.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting\u003c/h2\u003e \u003cp\u003eThe National Inpatient Sample (NIS) database, provided by the Healthcare Cost and Utilization Project (HCUP) of the Agency for Healthcare Research and Quality, was utilized for this study. The NIS complies with the Health Insurance Portability and Accountability Act (HIPAA), ensuring patient, physician, and hospital privacy. As the largest inpatient database in the United States, the NIS comprises data from hospital discharges nationwide, representing over 40\u0026nbsp;million hospitalizations annually. This dataset offers a comprehensive view of clinical and resource utilization across the American population, including over 100 clinical and non-clinical outcome data points for each hospital stay, such as primary and secondary diagnoses, baseline population characteristics, patient comorbidity measures, total charges (US\u003cspan\u003e$\u003c/span\u003e), and hospital characteristics. The NIS database from 2016 onwards uses the International Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS). This system classifies codes into primary and secondary diagnoses, including all additional ICD-10 codes that do not represent the primary diagnosis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThe NIS data from 2016 to 2020 were examined for all adult (\u0026ge;\u0026thinsp;18 years) hospitalized patients with a primary discharge diagnosis of AP and a secondary diagnosis of MASLD ICD-10-CM. Patients were then categorized based on obesity and overweight status, according to the ICD-10-CM codes, to compare outcomes between lean MASLD and non-lean MASLD individuals with AP. Lean MASLD was operationalized as a subset of non-obese MASLD with a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m\u0026sup2;. We excluded patients with an ICD-10-CM history of alcohol-related liver disease and viral hepatitis.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe Primary outcome was in-hospital mortality. Secondary outcomes included a spectrum of complications, all based on ICD-10-CM, including organ failures (e.g., acute kidney injury, acute respiratory distress syndrome), systemic infections (e.g., sepsis, any bacterial infection), metabolic disturbances, venous thromboembolism, gastrointestinal complications, and the necessity for various medical interventions, based on ICD-10-PCS (e.g., mechanical ventilation, parenteral nutrition, imaging tests, and specific procedures related to pancreatitis management). Hospital-stay metrics and healthcare costs, adjusted for inflation to 2020 dollars, were also analyzed. Additionally, patients with a history of cirrhosis were evaluated for decompensating outcomes based on ICD-10-CM (Variceal bleeding, hepatorenal syndrome, hepatic encephalopathy, and ascites). The analysis adjusted results for baseline demographics, comorbidities, Charlson Comorbidity Index (CCI), income quartile, and hospital characteristics.\u003c/p\u003e \u003cp\u003eData were presented as population-weighted means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error for continuous variables and population-weighted percentages\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error for categorical variables. Differences between lean MASLD and non-lean MASLD patients were evaluated using univariate and multivariable analyses, with continuous variables compared using t-tests and categorical variables using chi-square tests. Logistic and linear regression analyses assessed the association between obesity and in-hospital mortality, length of stay, and hospital charges, among other outcomes. Adjustments were made for age, gender, race, Charlson Comorbidity Index (CCI), median income quartile, and hospital characteristics in multivariable models. Inflation adjustments for cost analysis were made to 2020 dollars using the appropriate economic deflators.\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using SAS software (version 9.4, SAS Institute, Cary, NC), considering the complex sampling design of the NIS and applying appropriate weights in the statistical models.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics and Hospital Data\u003c/h2\u003e \u003cp\u003eOur study analyzed a cohort of 34,388 hospitalized patients with AP and MASLD, of whom 14,443 (42.0%) were categorized as non-lean MASLD and 19,945 (58.0%) as lean MASLD. The mean age of non-lean MASLD patients was significantly lower than that of lean MASLD patients (48.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.18 vs. 52.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.03 years, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The gender distribution differed between groups, with a higher proportion of females in the non-lean MASLD group (53.7%) compared to the lean MASLD group (49.4%) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eRegarding race/ethnicity, Hispanic patients were more prevalent in the non-lean MASLD group (21.5% vs. 19.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while the distribution of White (62.0% vs. 62.5%, P\u0026thinsp;=\u0026thinsp;0.22) and Black patients (10.2% vs. 10.0%, P\u0026thinsp;=\u0026thinsp;0.22) remained similar across groups. Non-lean MASLD patients experienced higher hospitalization charges (mean \u003cspan\u003e$\u003c/span\u003e61,964 vs. \u003cspan\u003e$\u003c/span\u003e55,798, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and a slightly longer length of stay (5.2 days vs. 4.9 days, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Differences in insurance coverage and socioeconomic status were also observed, with a higher proportion of Medicaid recipients in the non-lean MASLD group (22.1% vs. 20.1%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and a greater representation of lower-income quartiles (\u0026lt;\u003cspan\u003e$\u003c/span\u003e38,999/year) among non-lean MASLD patients (31.5% vs. 29.4%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eThe distribution of hospitalizations showed notable regional differences. The South was the most common location for both subgroups, with 42% of lean MASLD patients and 40.2% of non-lean MASLD patients hospitalized in this region. Furthermore, the majority of hospitalizations occurred in teaching hospitals, accounting for 68.3% of cases in the non-lean MASLD subgroup. Detailed demographic and hospital characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of Hospitalized US Adults with AP and MASLD, Categorized by Obese/Non-Obese MASLD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eNon-Lean MASLD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;19945)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;14443)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;34388)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge in years at admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.1 (16.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.1 (15.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.4 (15.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.0, 90.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.0, 90.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.0, 90.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10089 (50.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6684 (46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16773 (48.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9854 (49.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7754 (53.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17608 (51.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace /Ethnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWhite\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12158 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8749 (62.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20907 (62.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBlack\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1950 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1437 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3387 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHispanic\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3689 (19.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3029 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6718 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAsian or Pacific Islander\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e752 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1061 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNative American\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e261 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e741 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e471 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1212 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal charges ($)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55798.7 (86550.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61964.8 (93357.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58385.6 (89519.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35035.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40165.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37045.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e589.0, 2427175.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298.0, 3810065.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e298.0, 3810065.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9 (5.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2 (6.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0 (5.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0, 198.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0, 228.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0, 228.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Payer Source\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePrivate Insurance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5783 (29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3325 (23.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9108 (26.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMedicaid\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4001 (20.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3187 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7188 (20.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMedicare\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7659 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6215 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13874 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOther Payment Source\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1683 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1182 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2865 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSelf-Pay\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e288 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo Charge\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e613 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e402 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1015 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian household income ($)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;38 999\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5777 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4484 (31.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10261 (30.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e39 000\u0026ndash;47 999\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5383 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3908 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9291 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e48 000\u0026ndash;62 999\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4669 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3450 (24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8119 (24.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e\u0026gt;\u0026thinsp;63 000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3788 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2414 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6202 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSmall\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3611 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2579 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6190 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMedium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4891 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3504 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8395 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLarge\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7784 (47.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5605 (48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13389 (47.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion of hospital\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2403 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1564 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3967 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3239 (19.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2647 (22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5886 (21.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6832 (42.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4699 (40.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11531 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3812 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2778 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6590 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocation of hospital\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1028 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e698 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1726 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11599 (91.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8235 (92.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19834 (92.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocation/Teaching status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRural\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1335 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e901 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2236 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrban Non-Teaching\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3867 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2736 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6603 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrban Teaching\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11084 (68.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8051 (68.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19135 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTeaching status of hospital\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4164 (33.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2833 (31.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6997 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8463 (67.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6100 (68.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14563 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear of Admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2923 (14.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1929 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4852 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3022 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2140 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5162 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3267 (16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2355 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5622 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3415 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2509 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5924 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7318 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5510 (38.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12828 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharlson index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2 (1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3 (1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2 (1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0, 13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0, 14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0, 14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTobacco Smoking\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15522 (77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11870 (82.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27392 (79.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4423 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2573 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6996 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCirrhosis\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18884 (94.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13763 (95.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32647 (94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1061 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e680 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1741 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eKruskal-Wallis\u0026nbsp;p-value;\u0026nbsp;\u003csup\u003e2\u003c/sup\u003eChi-Square\u0026nbsp;p-value;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the annual hospital admissions for AP in patients with MASLD, stratified by lean/non-lean status from 2016 to 2020. The trend analysis over the five years reveals a consistent year-over-year increase in admissions for both lean and non-lean MASLD patients. Notably, admissions for lean MASLD patients showed a more pronounced rise.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical Outcomes\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the results of clinical outcomes comparing AP outcomes between non-lean and lean MASLD patients. Several significant associations between obesity and AP complications were observed. Respiratory failure was significantly more common in non-lean MASLD patients, with an adjusted OR of 4.60 (95% CI: 2.24\u0026ndash;9.46, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Similarly, sepsis showed a statistically significant increase in non-lean MASLD patients, with an adjusted OR of 1.11 (95% CI: 1.00\u0026ndash;1.23, P\u0026thinsp;=\u0026thinsp;0.04).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between non-lean MASLD and outcomes of AP in US Hospitalized Adults.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eoutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.83(0.58\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91(0.60\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.99(0.93\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95(0.88\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory Failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2.51(1.36\u0026ndash;4.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.60(2.24\u0026ndash;9.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.07(0.98\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.11(1.00-1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIleus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.03(0.92\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06(0.93\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.95(0.71\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.21(0.86\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.10(0.88\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.11(0.85\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll Venous Thrombosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.75(0.64\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70(0.57\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.01(0.71\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16(0.76\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDVT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.05(0.72\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22(0.79\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortal Vein Thrombosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.65(0.52\u0026ndash;0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64(0.50\u0026ndash;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI Bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.82(0.69\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84(0.69\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecompensated Liver Events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.75(0.68\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76(0.67\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal CT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.97(0.78\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10(0.85\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntubation /ARDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.00(0.85\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08(0.89\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParacentesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.83(0.69\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88(0.71\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholecystectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.69(1.60\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.05(1.92\u0026ndash;2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercutaneous Cholecystostomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.04(0.23\u0026ndash;4.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52(0.04\u0026ndash;7.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholangiogram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.45(1.35\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.72(1.57\u0026ndash;1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.04(0.96\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10(1.00-1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.74(0.64\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84(0.71\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTPN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.34(1.10\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25(1.00-1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatic Drainage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.03(0.80\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.12(0.84\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.20(0.97\u0026ndash;1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.42(1.11\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.41(0.22\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.40(0.18\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMACE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1.07(1.00-1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.19(1.05\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.76(0.61\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.90(0.69\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eContinuous Outcomes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eInflation-Adjusted Charges(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6162.31(4238.40-8086.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5324.01(3273.42-7374.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLength of Stay (Days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.39(0.26\u0026ndash;0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25(0.12\u0026ndash;0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eSub Analysis Of Outcomes among Patients with Cirrhosis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDecompensated Liver Events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75(0.61\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.78(0.61-1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06(0.63\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.10(0.61-2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eVariceal bleed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.14(0.78\u0026ndash;12.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4.05(0.80-20.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eHepatorenal Syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.44(0.87\u0026ndash;2.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.25(0.67\u0026ndash;2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eHepatic Encephalopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAscites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70(0.56\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.735(0.57\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*Adjusted for age, gender, race, median income quartile, CCI, year of admission, day of admission and hospital characteristics\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eAKI\u0026thinsp;=\u0026thinsp;Acute Kidney Injury, ARDS\u0026thinsp;=\u0026thinsp;Acute Respiratory Distress Syndrome, SIRS\u0026thinsp;=\u0026thinsp;Systemic Inflammatory Response Syndrome, CT\u0026thinsp;=\u0026thinsp;Computed Tomography, MRCP\u0026thinsp;=\u0026thinsp;Magnetic Resonance Cholangiopancreatography, ERCP\u0026thinsp;=\u0026thinsp;Endoscopic Retrograde Cholangiopancreatography, EGD\u0026thinsp;=\u0026thinsp;Esophagogastroduodenoscopy, GI Bleeding\u0026thinsp;=\u0026thinsp;Gastrointestinal Bleeding, TPN\u0026thinsp;=\u0026thinsp;Total Parenteral Nutrition, CCY\u0026thinsp;=\u0026thinsp;Cholecystectomy, MACE\u0026thinsp;=\u0026thinsp;Major Adverse Cardiovascular Events, PC\u0026thinsp;=\u0026thinsp;Percutaneous Cholecystostomy, PTHC\u0026thinsp;=\u0026thinsp;Percutaneous Transhepatic Cholangiogram\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn contrast, thromboembolic events showed a more nuanced pattern. Non-lean MASLD patients had significantly lower odds of all venous thrombosis (adjusted OR 0.70; 95% CI: 0.57\u0026ndash;0.85, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), particularly portal vein thrombosis (adjusted OR 0.64; 95% CI: 0.50\u0026ndash;0.82, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). However, the two groups had no significant differences in the pulmonary embolism or deep vein thrombosis rates. When evaluating liver-related outcomes, decompensated liver disease - including variceal bleeding, ascites, hepatic encephalopathy, or hepatorenal syndrome - was significantly less frequent in non-lean MASLD patients (adjusted OR 0.76; 95% CI: 0.67\u0026ndash;0.85, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eOn procedural interventions, non-lean MASLD patients were significantly more likely to undergo cholecystectomy, with an adjusted OR of 2.05 (95% CI: 1.92\u0026ndash;2.19, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as well as cholangiography, with an adjusted OR of 1.72 (95% CI: 1.57\u0026ndash;1.87, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Furthermore, Endoscopic retrograde cholangiopancreatography (ERCP) was more common among non-lean MASLD patients, with an adjusted OR of 1.42 (95% CI: 1.11\u0026ndash;1.82, P\u0026thinsp;=\u0026thinsp;0.01). Similarly, esophagogastroduodenoscopy (EGD) was slightly more likely in non-lean MASLD patients (adjusted OR 1.10; 95% CI: 1.01\u0026ndash;1.21, P\u0026thinsp;=\u0026thinsp;0.03), whereas magnetic resonance cholangiopancreatography (MRCP) was less frequently performed in this group (adjusted OR 0.40; 95% CI: 0.18\u0026ndash;0.89, P\u0026thinsp;=\u0026thinsp;0.02). Percutaneous cholecystostomy was not significantly different between groups (adjusted OR 0.52; 95% CI: 0.04\u0026ndash;7.31, P\u0026thinsp;=\u0026thinsp;0.63). The likelihood for total parenteral nutrition (TPN) was slightly higher in non-lean MASLD patients but did not reach statistical significance (adjusted OR 1.25; 95% CI: 1.00\u0026ndash;1.57, P\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eDespite the differences in complications and interventions, mortality rates were not significantly different between non-lean and lean MASLD patients, with an adjusted OR of 0.90 (95% CI: 0.69\u0026ndash;1.17, P\u0026thinsp;=\u0026thinsp;0.43). There was no difference in the likelihood of cardiac arrest (adjusted OR 0.91; 95% CI: 0.60\u0026ndash;1.39, P\u0026thinsp;=\u0026thinsp;0.67), acute myocardial infarction (adjusted OR 1.21; 95% CI: 0.86\u0026ndash;1.71, P\u0026thinsp;=\u0026thinsp;0.28), acute kidney injury (adjusted OR 0.95; 95% CI: 0.88\u0026ndash;1.02, P\u0026thinsp;=\u0026thinsp;0.14), shock (adjusted OR 1.11; 95% CI: 0.85\u0026ndash;1.46, P\u0026thinsp;=\u0026thinsp;0.44) or ileus (adjusted OR 1.05; 95% CI: 0.93\u0026ndash;1.20, P\u0026thinsp;=\u0026thinsp;0.41).\u003c/p\u003e \u003cp\u003eContinuous outcomes further demonstrated increased healthcare utilization in non-lean MASLD patients. Inflation-adjusted hospital charges were significantly higher for non-lean MASLD patients by an average of \u003cspan\u003e$\u003c/span\u003e5,324 (95% CI: \u003cspan\u003e$\u003c/span\u003e3,273\u0026ndash;\u003cspan\u003e$\u003c/span\u003e7,375, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Non-lean MASLD patients had an increased length of hospital stay, with an adjusted increase of 0.25 days (95% CI: 0.12\u0026ndash;0.39, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSubgroup Analysis of Cirrhosis Patients\u003c/h3\u003e\n\u003cp\u003eAmong patients with cirrhosis, trends were observed for decompensating events. Non-lean MASLD patients had lower odds of decompensated liver disease, with an adjusted OR of 0.78 (95% CI: 0.61\u0026ndash;1.00, P\u0026thinsp;=\u0026thinsp;0.05). Ascites was significantly less likely in non-lean MASLD patients with cirrhosis, with an adjusted OR of 0.74 (95% CI: 0.57\u0026ndash;0.94, P\u0026thinsp;=\u0026thinsp;0.02). Variceal bleeding was comparable in lean and non-lean MASLD patients (adjusted OR 4.05; 95% CI: 0.80\u0026ndash;20.61, P\u0026thinsp;=\u0026thinsp;0.09). Similarly, hepatorenal syndrome showed a slight but non-significant increase in non-lean MASLD patients (adjusted OR 1.25; 95% CI: 0.67\u0026ndash;2.32, P\u0026thinsp;=\u0026thinsp;0.49). Mortality did not differ significantly in this subgroup (adjusted OR 1.10; 95% CI: 0.61\u0026ndash;2.00, P\u0026thinsp;=\u0026thinsp;0.92).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study aimed to evaluate and compare clinical outcomes of AP in patients with lean versus non-lean MASLD\u0026mdash;a distinction that, to our knowledge, has not been previously explored. While prior literature has established MASLD as a risk factor for increased AP severity, it remains unclear whether the lean phenotype carries similar or even greater risk than its non-lean counterpart. Given the rising prevalence of both AP and MASLD, along with emerging evidence highlighting the distinct metabolic profiles of lean MASLD patients, this investigation addresses an essential gap in the literature and offers clinically relevant insights. In this nationally representative cohort, we found that lean MASLD accounted for the majority of AP hospitalizations and was associated with a higher likelihood of decompensated liver events. In contrast, non-lean MASLD was associated with an increased risk of sepsis, respiratory failure, cholecystectomy, greater healthcare resource utilization, and longer length of hospital stay. Notably, there was no difference in in-hospital mortality between the two groups.\u003c/p\u003e \u003cp\u003eDisease severity and risk stratification are essential components of AP disease management. Several available risk-scoring systems help determine the appropriate hospital level of care and predict outcomes, including organ dysfunction and mortality.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Increasing BMI has been associated with mortality in AP, despite its absence as a variable of interest in AP risk scoring systems, including the APACHE II, Ranson, and BISAP.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Obesity was associated with a 3-fold increase in mortality in AP in a meta-analysis involving 19 studies by Dobzai et al.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Obesity and its attendant increase in peripancreatic fat accumulation exacerbates pancreatic injury-induced inflammatory dysregulation, tissue necrosis, peripancreatic infection/sepsis, respiratory failure, and multiorgan dysfunction leading to the observed increase in mortality.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) Patients with lean MASLD are known to have increased visceral adipocyte mass and tissue inflammation, insulin resistance, and sarcopenia and thus share a similar cardiometabolic risk profile compared with their non-lean counterparts.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) The complex interactions between cardiometabolic risk profiles of patients with lean MASLD and AP physiology may influence mortality outcomes irrespective of BMI. The risk of all-cause mortality and cardiovascular mortality may be similar (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) or even higher (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) in lean MASLD compared to patients with non-lean MASLD. A prospective single-center database analysis from England of patients with admissions for severe AP complicated by organ failure found an increase in mortality in patients with sarcopenia compared to those without.(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) A fraction of the lean MASLD population in our study may represent patients with overweight or obesity who have experienced a reduction in BMI from significant weight and muscle loss/sarcopenia from poor glycemic control, reduced physical activity, and advanced MASLD-associated chronic liver disease.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePatients with cirrhosis in the lean-MASLD were more likely to have overall decompensated liver events. This observation was driven by the increased likelihood of ascites in the lean-MASLD cirrhosis cohort, as no significant difference was observed in the other components of decompensated cirrhosis. Ha et al.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) in a meta-analysis involving 10 cohort studies identified a comparable risk of decompensated liver events and an increased risk of liver-related mortality in patients with lean MASLD. A longitudinal study involving 169303 patients from the French national Constances cohort identified an increased risk of advanced fibrosis, liver-related events, and all-cause mortality in the lean MASLD group. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) Simons-Linares et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) found an increased risk of in-patient mortality in patients with AP and cirrhosis compared to patients without cirrhosis. Patients with decompensated cirrhosis had higher risks of in-patient mortality among the cirrhosis group.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) However, we found no difference in mortality between both cirrhosis groups despite an increase in overall decompensating events in the lean-MASLD group.\u003c/p\u003e \u003cp\u003ePatients with non-lean MASLD had a 36% lower risk of developing portal vein thrombosis (PVT). However, there was no difference in DVT and PE between both groups. In a retrospective study involving patients with AP, patients with obesity were found to have a 17% lower risk of developing PVT. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) A meta-analysis involving 22 studies by Li et al.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) identified metabolic dysfunction, including non-alcoholic fatty liver disease, diabetes mellitus, and hypercholesterolemia, to be associated with increased risk of PVT in patients with cirrhosis irrespective of BMI. The pathophysiologic mechanisms of PVT as a complication of AP involve an interplay of the proximity of the portal vein to the pancreas and vascular endothelial dysfunction from inflammatory and coagulation cascade activation. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePatients with non-lean MASLD were more likely to have sepsis and respiratory failure during hospitalization. Gajendran et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) in a retrospective study of hospitalized patients with AP, identified sepsis as the strongest predictor of acute respiratory failure (OR 15; 95% CI 14.7\u0026ndash;15.4). Obesity, chronic lung disease, and cardiogenic shock were other notable predictors of respiratory failure.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) Our findings have important practice implications, as non-lean MASLD patients may be more susceptible to volume-associated respiratory failure with aggressive intravenous fluid resuscitation. Obesity is a known risk factor for sepsis. Possible mechanisms include a dysregulated immune response, effects of obesity-related comorbidities, impaired micro/macro-circulation, and impaired wound healing. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) Poor glycemic control from insulin resistance and stress hyperglycemia in AP has been associated with an increasing risk of extra-pancreatic abdominal infections and infected pancreatic necrosis.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) Compared with sterile necrosis, patients with infected pancreatic necrosis have a higher rate of mortality from sepsis and multi-organ failure in AP.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Obesity restricts chest wall and diaphragmatic movements, negatively affecting lung volumes and capacities. The development of physiologic pulmonary shunts leads to respiratory failure and increasing intubation requirements, which can further aggravate organ dysfunction in AP. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) Conversely, another retrospective study involving 359 patients admitted to a teaching hospital with AP in Denmark identified age and smoking as predictors of respiratory failure in the early phase of AP with no significant contribution from BMI. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) A paradoxical improvement in survival and functional outcomes has been observed in hospitalized patients with sepsis and obesity in some studies(\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Further studies are needed to evaluate this observation in patients with MASLD and AP.\u003c/p\u003e \u003cp\u003eNon-lean MASLD was associated with increased healthcare resource utilization in terms of higher inflation-adjusted hospital charges and increased length of hospital stay. The total financial cost of pancreatitis to the US healthcare system nearly doubled from \u003cspan\u003e$\u003c/span\u003e3.9\u0026nbsp;billion in 1996 to \u003cspan\u003e$\u003c/span\u003e7.7\u0026nbsp;billion in 2016, with inpatient care accounting for 75.1% of spending.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) The rising cost has been attributed to increased hospitalizations despite a relatively stable disease incidence and increased intensity and financial cost of inpatient case management.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Our study demonstrated a similar trend of increasing hospitalizations in both groups, with a more pronounced rise in the lean MASLD group. Intensive care unit (ICU) stay, biliary etiology of AP, peripancreatic necrotic fluid collections, and necrosectomy are significant determinants of hospitalization costs in patients with AP.(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) The increased length of stay and the likelihood of sepsis, respiratory failure, and increased utilization of investigations and interventions, including cholangiogram, cholecystectomy, and ERCP in the non-lean MASLD group, could account for their increased healthcare resource utilization in our study. Despite dataset limitations on the etiology and severity of AP in our cohort, patients in the non-lean MASLD group\u0026rsquo;s increased utilization of the abovementioned interventions could suggest a higher frequency of biliary pancreatitis and higher hospital level of care. A single tertiary center prospective cohort study by Singh et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) involving 231 patients with AP identified the performance of cholecystectomy and ongoing pancreatitis-related symptoms as the main determining factors for increased length of hospital stay (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Intolerance to oral feeding, a fasting period of 3 or more days, and the performance of ERCP was independently associated with increased length of hospital stay in patients with AP in a study by Francisco et al (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eOur study has several strengths and limitations. A major strength of this study is the use of the NIS. This large, nationally representative database enables comprehensive analysis of AP hospitalizations among patients with MASLD across the United States. The dataset\u0026rsquo;s breadth\u0026mdash;capturing patient characteristics, hospital factors, and comorbidities\u0026mdash;provides valuable insight into epidemiologic trends, complications, and healthcare utilization at a population level. However, the retrospective nature of the NIS introduces limitations. The database lacks granular data on MASLD severity, disease duration, medication use, and laboratory parameters. The etiology, severity, and recurrence of AP could not be determined. The use of ICD codes carries the risk of misclassification, and because the unit of analysis is hospitalizations, repeat admissions for the same patient may inflate event rates. Additionally, the NIS is limited to inpatient encounters, precluding post-discharge outcomes and long-term prognosis assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFuture Research\u003c/h2\u003e \u003cp\u003eFuture studies should aim to clarify the pathophysiologic mechanisms underlying the differential outcomes observed between lean and non-lean MASLD patients with AP, focusing on the roles of sarcopenia, visceral adiposity, and insulin resistance. Prospective studies incorporating clinical, laboratory, and imaging data are needed to better characterize MASLD phenotypes and their influence on AP severity and progression. Additionally, longitudinal research is warranted to evaluate post-discharge outcomes and long-term complications. Given the observed differences in healthcare utilization, future investigations should also assess the cost-effectiveness of tailored management strategies across MASLD phenotypes, which may inform resource allocation and clinical guidelines.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eOur study revealed increased acute pancreatitis hospitalizations and distinct clinical profiles, including higher rates of decompensating liver events in lean-MASLD patients compared to non-lean MASLD patients. Despite an increase in healthcare resource utilization and incidence of sepsis and respiratory failure in patients with non-lean MASLD admitted with AP compared with the lean cohort, no difference in in-patient mortality was observed between both groups. These findings suggest a complex relationship between the pathophysiology of AP and MASLD beyond BMI. Future calls for incorporating MASLD into prognostic tools of AP should include increased sensitization about lean-MASLD and the need for equal vigilance regardless of BMI to ensure favorable outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions: Prince Addo Ameyaw participated in the manuscript's concept, research design, writing, final revision, and formatting.Sarpong Boateng participated in the manuscript's concept and research design, data analysis, writing, and formatting.Yussif Issaka, Amita Ashokkumar Kasar, and Erika Sandra Ackah participated in the writing and formatting of the manuscriptYazan A. Al-Ajlouni participated in the writing and final revision of the manuscriptBasile Njei was the supervising investigator and participated in the manuscript's concept and research design, data analysis, and final manuscript revision.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMederos MA, Reber HA, Girgis MD. Acute Pancreatitis: A Review. JAMA. 2021;325(4):382-90.\u003c/li\u003e\n\u003cli\u003eIannuzzi JP, King JA, Leong JH, Quan J, Windsor JW, Tanyingoh D, et al. Global Incidence of Acute Pancreatitis Is Increasing Over Time: A Systematic Review and Meta-Analysis. Gastroenterology. 2022;162(1):122-34.\u003c/li\u003e\n\u003cli\u003eAhmed NS, Forbes N, Stukalin I, Singh S, Shaheen AA, Ma C, et al. Population-based Trends in Healthcare Utilization and National Healthcare Spending on Pancreatitis in North America. Gastroenterology. 2021;161(5):1698-701 e5.\u003c/li\u003e\n\u003cli\u003ePokras S, Ray M, Zheng S, Ding Y, Chen CC. 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Lancet Gastroenterol Hepatol. 2022;7(9):851-61.\u003c/li\u003e\n\u003cli\u003eAhadi M, Molooghi K, Masoudifar N, Namdar AB, Vossoughinia H, Farzanehfar M. A review of non-alcoholic fatty liver disease in non-obese and lean individuals. J Gastroenterol Hepatol. 2021;36(6):1497-507.\u003c/li\u003e\n\u003cli\u003eDobszai D, Matrai P, Gyongyi Z, Csupor D, Bajor J, Eross B, et al. Body-mass index correlates with severity and mortality in acute pancreatitis: A meta-analysis. World J Gastroenterol. 2019;25(6):729-43.\u003c/li\u003e\n\u003cli\u003eVancsa S, Sipos Z, Varadi A, Nagy R, Ocskay K, Juhasz FM, et al. Metabolic-associated fatty liver disease is associated with acute pancreatitis with more severe course: Post hoc analysis of a prospectively collected international registry. United European Gastroenterol J. 2023;11(4):371-82.\u003c/li\u003e\n\u003cli\u003eAhmed OT, Gidener T, Mara KC, Larson JJ, Therneau TM, Allen AM. Natural History of Nonalcoholic Fatty Liver Disease With Normal Body Mass Index: A Population-Based Study. Clin Gastroenterol Hepatol. 2022;20(6):1374-81 e6.\u003c/li\u003e\n\u003cli\u003eZou B, Yeo YH, Nguyen VH, Cheung R, Ingelsson E, Nguyen MH. Prevalence, characteristics and mortality outcomes of obese, nonobese and lean NAFLD in the United States, 1999-2016. J Intern Med. 2020;288(1):139-51.\u003c/li\u003e\n\u003cli\u003eChrysavgis L, Ztriva E, Protopapas A, Tziomalos K, Cholongitas E. Nonalcoholic fatty liver disease in lean subjects: Prognosis, outcomes and management. World J Gastroenterol. 2020;26(42):6514-28.\u003c/li\u003e\n\u003cli\u003eHa J, Yim SY, Karagozian R. Mortality and Liver-Related Events in Lean Versus Non-Lean Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis. Clin Gastroenterol Hepatol. 2023;21(10):2496-507 e5.\u003c/li\u003e\n\u003cli\u003eMikolasevic I, Orlic L, Poropat G, Jakopcic I, Stimac D, Klanac A, et al. Nonalcoholic fatty liver and the severity of acute pancreatitis. Eur J Intern Med. 2017;38:73-8.\u003c/li\u003e\n\u003cli\u003eKatuchova J, Bober J, Harbulak P, Hudak A, Gajdzik T, Kalanin R, et al. Obesity as a risk factor for severe acute pancreatitis patients. Wien Klin Wochenschr. 2014;126(7-8):223-7.\u003c/li\u003e\n\u003cli\u003eDing C, Chan Z, Magkos F. Lean, but not healthy: the \u0026apos;metabolically obese, normal-weight\u0026apos; phenotype. Curr Opin Clin Nutr Metab Care. 2016;19(6):408-17.\u003c/li\u003e\n\u003cli\u003eChan WK. Comparison between obese and non-obese nonalcoholic fatty liver disease. Clin Mol Hepatol. 2023;29(Suppl):S58-S67.\u003c/li\u003e\n\u003cli\u003eHuang S, Bao Y, Zhang N, Niu R, Tian L. Long-term outcomes in lean and non-lean NAFLD patients: a systematic review and meta-analysis. Endocrine. 2023.\u003c/li\u003e\n\u003cli\u003eYe Q, Zou B, Yeo YH, Li J, Huang DQ, Wu Y, et al. 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Pancreatology. 2020;20(1):44-50.\u003c/li\u003e\n\u003cli\u003eChaudhry H, Sohal A, Bains K, Dhaliwal A, Dukovic D, Singla P, et al. Incidence and factors associated with portal vein thrombosis in patients with acute pancreatitis: A United States national retrospective study. Pancreatology. 2023;23(4):350-7.\u003c/li\u003e\n\u003cli\u003eLi J, Wang Q, Yang M, Sun X. Metabolic Disorders and Risk of Portal Vein Thrombosis in Liver Cirrhosis: A Systematic Review and Meta-Analysis. Turk J Gastroenterol. 2022;33(7):541-53.\u003c/li\u003e\n\u003cli\u003eGarg R, Mohammed A, Singh A, Siddiki H, Bhatt A, Sanaka MR, et al. Mortality Trends, Outcomes, and Predictors of Portal Vein Thrombosis in Acute Pancreatitis Patients: A Propensity-Matched National Study. Dig Dis Sci. 2023;68(6):2674-82.\u003c/li\u003e\n\u003cli\u003eGajendran M, Prakash B, Perisetti A, Umapathy C, Gupta V, Collins L, et al. Predictors and outcomes of acute respiratory failure in hospitalised patients with acute pancreatitis. Frontline Gastroenterol. 2021;12(6):478-86.\u003c/li\u003e\n\u003cli\u003eHuttunen R, Syrjanen J. Obesity and the risk and outcome of infection. Int J Obes (Lond). 2013;37(3):333-40.\u003c/li\u003e\n\u003cli\u003eJin Y, Tao S, Yu G, Li C, Hu Z, Jiang L. Predictive value of hyperglycemia on infection in critically ill patients with acute pancreatitis. Sci Rep. 2023;13(1):4106.\u003c/li\u003e\n\u003cli\u003eDombernowsky T, Kristensen MO, Rysgaard S, Gluud LL, Novovic S. Risk factors for and impact of respiratory failure on mortality in the early phase of acute pancreatitis. Pancreatology. 2016;16(5):756-60.\u003c/li\u003e\n\u003cli\u003eYeo HJ, Kim TH, Jang JH, Jeon K, Oh DK, Park MH, et al. Obesity Paradox and Functional Outcomes in Sepsis: A Multicenter Prospective Study. Crit Care Med. 2023;51(6):742-52.\u003c/li\u003e\n\u003cli\u003eJagan N, Morrow LE, Walters RW, Plambeck RW, Wallen TJ, Patel TM, et al. Sepsis and the Obesity Paradox: Size Matters in More Than One Way. Crit Care Med. 2020;48(9):e776-e82.\u003c/li\u003e\n\u003cli\u003eBai L, Huang J, Wang D, Zhu D, Zhao Q, Li T, et al. Association of body mass index with mortality of sepsis or septic shock: an updated meta-analysis. J Intensive Care. 2023;11(1):27.\u003c/li\u003e\n\u003cli\u003eMurata A, Matsuda S, Mayumi T, Okamoto K, Kuwabara K, Ichimiya Y, et al. Multivariate analysis of factors influencing medical costs of acute pancreatitis hospitalizations based on a national administrative database. Dig Liver Dis. 2012;44(2):143-8.\u003c/li\u003e\n\u003cli\u003ePahomeanu MR, Constantinescu DI, Diaconu IS, Corbu DG, Negreanu L. Acute Pancreatitis-Drivers of Hospitalisation Cost-A Seven-Year Retrospective Study from a Large Tertiary Center. Healthcare (Basel). 2023;11(18).\u003c/li\u003e\n\u003cli\u003eSingh H, Gougol A, Mounzer R, Yadav D, Koutroumpakis E, Slivka A, et al. Which Patients with Mild Acute Pancreatitis Require Prolonged Hospitalization? Clin Transl Gastroenterol. 2017;8(12):e129.\u003c/li\u003e\n\u003cli\u003eFrancisco M, Valentin F, Cubiella J, Fernandez-Seara J. Factors related to length of hospital admission in mild interstitial acute pancreatitis. Rev Esp Enferm Dig. 2013;105(2):84-92.\u003c/li\u003e\n\u003c/ol\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":"Acute Pancreatitis, Metabolic-dysfunction Associated Steatotic Liver Disease, Obesity, Lean, Clinical Outcomes","lastPublishedDoi":"10.21203/rs.3.rs-6694877/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6694877/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Metabolic dysfunction-associated steatotic liver disease (MASLD) is a key contributor to the severity and outcomes of acute pancreatitis (AP). This study compares the clinical outcomes of AP in patients with lean versus non-lean MASLD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We identified adult patients hospitalized with AP and a secondary diagnosis of MASLD from the National Inpatient Sample (NIS 2016-2020). Outcomes, including mortality, organ failures, and healthcare utilization, were analyzed using logistic and linear regression models, adjusting for demographic, clinical, and hospital factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e We included 34,388 hospitalized patients with AP and MASLD, of whom 14,443 (42.0%) were non-lean. Annual admissions increased sharply in lean MASLD patients (5339 in 2016 to 8247 in 2020) compared to non-lean MASLD (2273 to 3635). Non-lean MASLD patients experienced higher inflation-adjusted hospital charges ($5,324.01; 95% CI: $3,273.42–$7,374.61, P \u0026lt; 0.01), a longer length of stay ((adjusted increase 0.25 days; 95% CI: 0.12–0.39, P \u0026lt; 0.05), increased odds of respiratory failure (aOR 4.60; 95% CI: 2.24–9.46, P \u0026lt;0.01), sepsis (aOR 1.11; 95% CI: 1.00–1.23, P = 0.04), cholecystectomy (aOR 2.05; 95% CI: 1.92–2.19, P \u0026lt; 0.01), ERCP (aOR of 1.42 95% CI: 1.11–1.82, P = 0.01). Mortality did not differ significantly. (aOR 0.90; 95% CI: 0.69–1.17, P = 0.43).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Our study suggests that lean MASLD patients with AP may experience a higher rate of hospital admissions and distinct clinical profiles, including a similar mortality risk compared to non-lean MASLD patients, indicating a complex relationship between AP outcomes and MASLD beyond BMI.\u003c/p\u003e","manuscriptTitle":"Outcomes of Acute Pancreatitis in Lean Vs. Non-Lean Metabolic Dysfunction-Associated Steatotic Liver Disease (Masld) Patients: A Nationwide Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-26 02:08:37","doi":"10.21203/rs.3.rs-6694877/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-12T19:07:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-24T16:39:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313484655033285360476142782366316480879","date":"2025-05-21T15:20:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157374457158530445707598777213242239346","date":"2025-05-21T15:18:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-21T15:16:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-19T21:51:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-19T16:50:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Digestive Diseases and Sciences","date":"2025-05-19T04:14:12+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":"38981ef9-362a-4708-83a6-2ea5b135efe0","owner":[],"postedDate":"May 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-28T16:01:15+00:00","versionOfRecord":{"articleIdentity":"rs-6694877","link":"https://doi.org/10.1007/s10620-025-09245-y","journal":{"identity":"digestive-diseases-and-sciences","isVorOnly":false,"title":"Digestive Diseases and Sciences"},"publishedOn":"2025-07-26 15:57:35","publishedOnDateReadable":"July 26th, 2025"},"versionCreatedAt":"2025-05-26 02:08:37","video":"","vorDoi":"10.1007/s10620-025-09245-y","vorDoiUrl":"https://doi.org/10.1007/s10620-025-09245-y","workflowStages":[]},"version":"v1","identity":"rs-6694877","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6694877","identity":"rs-6694877","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}