Related Experiment Video
Updated: Jan 16, 2026
Functional Human Liver Preservation and Recovery by Means of Subnormothermic Machine Perfusion
Published on: April 27, 2015
Refining the Liver Donor Risk Index With Machine Perfusion: A Bayesian Approach
Tomohiro Tanaka1,2, Daniel Sewell3
1Department of Internal Medicine, Division of Gastroenterology and Hepatology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.
Introduction:
The Donor Risk Index (DRI) is a widely used liver transplant allograft risk model but does not account for the increasing adoption of machine perfusion (MP).
Methods:
Using Bayesian updating, we incorporated MP into the DRI framework (DRI-MP). A Bayesian proportional hazards model with informative priors derived from the original DRI was applied to Organ Procurement and Transplantation Network data from January 2022 to June 2024. Model performance was assessed using Harrell Concordance-statistic, calibration plots, and Brier scores.
Results:
DRI-MP, defined as DRI × 0.7 for MP cases, improved 90-day graft survival discrimination (Harrell Concordance-statistic: = 0.546 vs 0.535, P = 0.040), while maintaining robust calibration.
Discussion:
The Bayesian-updated DRI-MP modestly improves donor risk discrimination, reflecting contemporary transplant practice and providing an implementable tool with continuity from the original DRI.
