Browsing by Author "Hudson, David"

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    Advancements in MELD Score and Its Impact on Hepatology
    (Thieme Medical Publishers, Inc., 2024) Hudson, David; Valentin Cortez, Francisco Javier; Hurtado Díaz de León, Ivonne; Malhi, Gurpreet; Rivas, Angélica; Afzaal, Tamoor; Rad, Mahsa Rahmany; Díaz Piga, Luis Antonio; Khan, Mohammad Qasim; Arab Verdugo, Juan Pablo
    There continues to be an ongoing need for fair and equitable organ allocation. The Model for End-Stage Liver Disease (MELD) score has evolved as a calculated framework to evaluate and allocate patients for liver transplantation objectively. The original MELD score has undergone multiple modifications as it is continuously scrutinized for its accuracy in objectively representing the clinical context of patients with liver disease. Several refinements and iterations of the score have been developed, including the widely accepted MELD-Na score. In addition, the most recent updated iteration, MELD 3.0, has been created. The MELD 3.0 calculator incorporates new variables such as patient sex and serum albumin levels and assigns new weights for serum sodium, bilirubin, international normalized ratio, and creatinine levels. It is anticipated that the use of MELD 3.0 scores will reduce overall waitlist mortality and enhance access for female liver transplant candidates. However, despite the emergence of the MELD score as one of the most objective measures for fair organ allocation, various countries and healthcare systems employ alternative methods for stratification and organ allocation. This review article will highlight the origins of the MELD score, its iterations, the current MELD 3.0, and future directions for managing liver transplantation organ allocation.
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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.
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    The Cannabinoid System as a Potential Novel Target for Alcohol‐Associated Liver Disease: A Propensity‐Matched Cohort Study
    (2025) Fakhoury, Butros; Jahagirdar, Vinay; Rama, Kaanthi; Hudson, David; Wang, Wei; Diaz Piga, Luis Antonio; Arab Verdugo, Juan Pablo
    Background: Alcohol-associated liver disease (ALD) is a leading cause of liver-related morbidity and mortality, yet effectivetherapeutic options remain limited. Preclinical data suggest that modulation of the hepatic endocannabinoid system, particularlyvia cannabidiol (CBD), may reduce alcohol-induced liver injury. Due to CBD's limited clinical use, we sought to evaluate the as-sociation between cannabis use and ALD risk among patients with alcohol use disorder (AUD).Methods: Using the TriNetX US Collaborative Network, we identified adult patients with AUD between 2010 and 2022. Threecohorts were constructed: cannabis use disorder (CUD), cannabis users without cannabis abuse or dependence (CU) and non-cannabis users (non- CU). Outcomes included ALD, hepatic decompensation and composite all-cause mortality over 3 years.Incidence and hazard ratios were calculated using Kaplan–Meier analysis and Cox regression.Results: After matching, 33 114 patients were included in each of the CUD and non- CU groups. Compared to non- CU, CUD wasassociated with a lower risk of ALD (HR 0.60, 95% CI 0.53–0.67; p < 0.001), hepatic decompensation (HR 0.83, 95% CI 0.73–0.95;p =0.005) and all-cause mortality (HR 0.86, 95% CI 0.80–0.94; p < 0.001) among individuals with AUD. Although CU was asso-ciated with lower risks of ALD, its risks of hepatic decompensation and all-cause mortality were similar to those of the non- CUcohort with AUD.