Browsing by Author "Hudson, David"

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    An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study
    (2024) 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.
    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/.
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    Prevention and control of risk factors in metabolic and alcohol-associated steatotic liver disease
    (2024) Desalegn, Hailemichael; Farias Siel, Renata Francisca; Hudson, David; Idalsoaga Ferrer, Francisco Javier; Cabrera, Daniel; Díaz Piga, Luis Antonio; Arab Verdugo, Juan Pablo
    Steatotic liver disease (SLD), including metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (ALD), is the primary cause of illness and mortality. In particular, MASLD affects more than 30% of the global population, while ALD accounts for 5.1% of all diseases and injuries worldwide. The SLD spectrum includes a variety of clinical conditions, from mild fatty liver and inflammation to different stages of liver fibrosis. Additionally, both conditions (MASLD and ALD) can be complicated by hepatocellular carcinoma (HCC), while around one-third of ALD patients can also develop at least one alcohol associated hepatitis (AH) episode. Both of these diseases are also associated with multiple extrahepatic complications, such as cardiovascular disease, chronic kidney disease, and malignancies. In MASLD, the rapid rise in global obesity and type 2 diabetes mellitus (T2DM) prevalence due to Westernized lifestyles has led to an increase in the prevalence of MASLD. Thus, the prevention and control of cardiometabolic risk factors (CMRFs) are the cornerstone of its treatment. Hypertension and atherogenic dyslipidemia are also important CMRFs associated with MASLD. Susceptible individuals with MASLD are adversely affected by even a small amount of alcohol consumption (though there is no agreed definition of a small amount), increasing the risk of severe outcomes and a faster progression of liver disease. This review explores factors that play a role in the development of SLD, especially focusing on the management of CMRFs and levels of alcohol use to prevent liver disease progression.