Chacko, Kristina R.

Introduction: Although the role of cardiometabolic risk factors (CMRF) has been characterized in steatotic liver disease, their role in the severity of alcohol-associated hepatitis (AH) remains unclear. We aimed to evaluate the impact of CMRF on mortality. Methods: Multinational prospective cohort study (2015–2024) including hospitalized patients with severe AH across 32 centers in 14 countries. Diagnosis of AH was made using the NIAAA criteria. Analyses included adjusted competing-risk models by age, sex, ethnicity, history of cirrhosis, CMRF, corticosteroid use, MELD, and ACLF grade, with liver transplantation as a competing risk. Results: 936 participants were included; mean age 48±11.2 years, and 88.9% were male. At least one CMRF was present in 46.6%; median body mass index (BMI) was 24.2 kg/m 2 [IQR: 22.8–28.2], prevalence of diabetes 17.6%, hypertension 16.5%, and dyslipidemia 5.8%. Median MELD was 24.4 [19.3–31.4], 86.7% had severe AH, and 180-day survival was 72.9%. Survival did not differ by CMRF status (log-rank p =0.453). In adjusted competing-risk models, higher age (sHR 1.02; 95%CI:1.01–1.04), greater alcohol intake (per g/day; sHR 1.001; 95%CI:1.000–1.002), MELD (sHR 1.04; 95%CI:1.01–1.06), and ACLF grade 2–3 (sHR 2.34 and 4.34) predicted mortality. However, no individual CMRF independently increased mortality. A prespecified non-linear BMI analysis showed modestly lower mortality between 25–40 kg/m², with a higher risk above 40 kg/m². Conclusion: Among patients with severe AH, metabolic dysfunction was not associated with increased mortality. Although a higher BMI was associated with slightly lower mortality in AH, this may reflect better nutritional status rather than a true protective effect.

Background: Severe alcohol-associated hepatitis (sAH) is a well-characterized disease with high short-term mortality. However, there is limited research on those with a “less severe condition” (moderate AH). This study aims to characterize in-depth patients with moderate AH (mAH), including the performance of mortality scoring systems, key prognostic factors, and survival over time. Methods: A multicenter retrospective cohort study (2009–2019) included patients with mAH (MELD score ≤20 at admission). Cox regression and receiver operating characteristic curves with AUC were used for analysis. Results: We included 1845 patients with AH (20 centers, 8 countries) between 2009 and 2019. mAH was defined as a MELD score ≤20 at admission. Twenty-four percent met the criteria for an mAH episode. Patients with mAH tend to be older and have a higher proportion of females, with a median MELD of 17 (15–19), Maddrey discriminant function (mDF) of 33 (22–40), the trajectory of serum bilirubin of 0.83 (0.60–1.21), and neutrophil-to-lymphocyte ratio (NLR) of 5 (2.96–8.60). The primary causes of death in mAH included multiple organ failure (34.1%) and infections (16.6%). The cumulative survival rates at 30, 90, and 180 days were 94.3%, 90.4%, and 88.2%, respectively. In multivariable analysis, age was the only significant predictor of 30-day mortality (HR 1.49, 95% CI: 1.27–1.76, p <0.001). Mortality prediction models showed poor performance, with AUC for MELD (0.671), mDF (0.726), trajectory of serum bilirubin (0.733), and NLR (0.697). Conclusions: Patients with moderate AH exhibited a mortality of 11.8% at 6 months, primarily driven by multiple organ failure and infections. These patients also exhibit a different clinical profile compared to those with sAH. Tailored models and therapeutic strategies are needed to improve long-term outcomes in mAH.

Background and Aims: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an enhanced prognostic model. Approach and Results: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled patients with AH per National Institute for Alcohol Abuse and Alcoholism criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day postadmission mortality, 3 artificial intelligence algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) informed an ensemble model, subsequently refined through Bayesian updating, integrating the derivation cohort’s average 90-day mortality with each center’s approximate mortality rate to produce posttest probabilities. The ALCoholic Hepatitis Artificial INtelligence Ensemble score integrated age, gender, cirrhosis, and 9 laboratory values, with center-specific mortality rates. Mortality was 18.7% (30 d) and 27.9% (90 d) in the derivation cohort versus 21.7% and 32.5% in the validation cohort. Validation cohort 30 and 90-day AUCs were 0.811 (0.779–0.844) and 0.799 (0.769–0.830), significantly surpassing legacy models like Maddrey’s Discriminant Function, Model for End-Stage Liver Disease variations, age-serum bilirubin-international normalized ratio-serum Creatinine score, Glasgow, and modified Glasgow Scores (p < 0.001). ALCoholic Hepatitis Artificial INtelligence Ensemble score also showcased superior calibration against MELD and its variants. Steroid use improved 30-day survival for those with an ALCoholic Hepatitis Artificial INtelligence Ensemble score > 0.20 in both derivation and validation cohorts. Conclusions: Harnessing artificial intelligence within a global consortium, we pioneered a scoring system excelling over traditional models for 30 and 90-day AH mortality predictions. Beneficial for clinical trials, steroid therapy, and transplant indications, it’s accessible at: https://aihepatology.shinyapps.io/ALCHAIN/.