preprint
An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study
Fecha
2024Registro en:
10.1097/HEP.0000000000000883
1527-3350
0270-9139
WOS:001235952000001
Autor
Dunn, Winston
Li, Yanming
Singal, Ashwani K.
Simonetto, Douglas A.
Díaz Piga, Luis Antonio
Idalsoaga Ferrer, Francisco Javier
Ayares, Gustavo
Arnold Alvaréz, Jorge Ignacio
Ayala-Valverde, Maria
Perez, Diego
Gomez, Jaime
Escarate, Rodrigo
Fuentes López, Eduardo
Ramirez-Cadiz, Carolina
Morales-Arraez, Dalia
Zhang, Wei
Qian, Steve
Ahn, Joseph C.
Buryska, Seth
Mehta, Heer
Dunn, Nicholas
Waleed, Muhammad
Stefanescu, Horia
Bumbu, Andreea
Horhat, Adelina
Attar, Bashar
Agrawal, Rohit
Cabezas, Joaquin
Echavaria, Victor
Cuyas, Berta
Poca, Maria
Soriano, German
Sarin, Shiv K.
Maiwall, Rakhi
Jalal, Prasun K.
Higuera-de-la-Tijera, Fatima
Kulkarni, Anand V.
Rao, P. Nagaraja
Guerra-Salazar, Patricia
Skladany, Lubomir
Kubanek, Natalia
Prado, Veronica
Clemente-Sanchez, Ana
Rincon, Diego
Haider, Tehseen
Chacko, Kristina R.
Romero, Gustavo A.
Pollarsky, Florencia D.
Restrepo, Juan C.
Toro, Luis G.
Yaquich, Pamela
Mendizabal, Manuel
Garrido, Maria L.
Marciano, Sebastian
Dirchwolf, Melisa
Vargas, Victor
Jimenez, Cesar
Hudson, David
Garcia-Tsao, Guadalupe
Ortiz, Guillermo
Abraldes, Juan G.
Kamath, Patrick S.
Arrese, Marco
Shah, Vijay H.
Bataller, Ramon
Arab, Juan P.
Institución
Resumen
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/.