Related Experiment Video
Updated: Sep 22, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
Published on: July 22, 2025
Are MELD and MELDNa Still Reliable Tools to Predict Mortality on the Liver Transplant Waiting List?
Marta Tejedor1, Nazia Selzner2, Marina Berenguer3,4,5
1Department of Gastroenterology and Hepatology, Hospital Universitario Infanta Elena (Valdemoro), Madrid, Spain.
Abstract:
Liver transplantation is the only curative treatment for end-stage liver disease. Unfortunately, the scarcity of donor organs and the increasing pool of potential recipients limit access to this life-saving procedure. Allocation should account for medical and ethical factors, ensuring equal access to transplantation regardless of recipient's gender, race, religion, or income. Based on their short-term prognosis prediction, model for end-stage liver disease (MELD) and MELD sodium (MELDNa) have been widely used to prioritize patients on the waiting list for liver transplantation resulting in a significant decrease in waiting list mortality/removal. Recent concern has been raised regarding the prognostic accuracy of MELD and MELDNa due, in part, to changes in recipients' profile such as body mass index, comorbidities, and general condition, including nutritional status and cause of liver disease, among others. This review aims to provide a comprehensive view of the current state of MELD and MELDNa advantages and limitations and promising alternatives. Finally, it will explore future options to increase the donor pool and improve donor-recipient matching.
More Related Videos
09:23Author Spotlight: Enhancing Transplantation Research Through MicroCT Angiography in Murine Models
Published on: September 22, 2023
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018