Citations

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/.

AbstractIntroductionThere are concerns regarding the effectiveness and safety of SARS‐CoV‐2 vaccine in inflammatory Bowel Disease (IBD) patients. This systematic review and meta‐analysis comprehensively summarises the available literature regarding the safety and effectiveness of SARS‐CoV‐2 vaccine in IBD.MethodsThree independent reviewers performed a comprehensive review of all original articles describing the response of SARS‐CoV‐2 vaccines in patients with IBD. Primary outcomes were (1) pooled seroconversion rate SARS‐CoV‐2 vaccination in IBD patients (2) comparison of breakthrough COVID‐19 infection rate SARS‐CoV‐2 vaccination in IBD patients with control cohort and (3) pooled adverse event rate of SARS‐CoV‐2 vaccine. All outcomes were evaluated for one and two doses of SARS‐CoV‐2 vaccine. Meta‐regression was performed. Probability of publication bias was assessed using funnel plots and with Egger’s test.ResultsTwenty‐one studies yielded a pooled seroconversion rate of 73.7% and 96.8% in IBD patients after one and two doses of SARS‐CoV‐2 vaccine respectively. Sub‐group analysis revealed non‐statistically significant differences between different immunosuppressive regimens for seroconversion. Meta‐regression revealed that the vaccine type and study location independently influenced seroconversion rates. There was no statistically significant difference in breakthrough infection in IBD patients as compared to control after vaccination.ConclusionIn summary, the systematic review and meta‐analysis suggest that SARS‐CoV‐2 vaccine is safe and effective in IBD patients.