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/.

Objective: To review pregnancy outcomes and the safety of jet ventilation use in the gravid patient undergoing surgical airway intervention. Methods: A multi-institutional retrospective review of medical records was performed to identify women who underwent low-frequency jet ventilation during pregnancy for surgical treatment of airway stenosis. Postoperative complications were noted, and patients were interviewed regarding pregnancy outcomes. Results: Six women were included in this series. No immediate complications relating to anesthesia or surgical intervention were noted in five of the six women. One patient with a well-known history of uncontrolled seizures experienced seizure activity postoperatively. One patient returned to the operating room at a later date for debridement of tracheal crusts. Five mothers delivered via cesarean section and one via spontaneous vaginal delivery. The mean gestation age was 37.3 weeks. One of the six infants delivered prematurely and three were delivered at low birth weight. Three of the six infants required elevated care immediately post-delivery but, at present, all are in good health. Conclusion: Low-frequency jet ventilation and surgical management of airway stenosis should be recognized as a safe treatment option in the gravid patient. Surgical intervention should not be delayed in patients with severe symptoms, particularly given the potential risk associated with prolonged corticosteroid use. Level of evidence: 4