Comparative Analysis of Islet Auto-Transplantation Outcome Classification Systems: Evaluating Concordance, Feasibility, and a Data-Driven Approach.

ABSTRACT: A standardized approach to assessing islet autotransplantation outcomes is crucial for evaluating graft function and guiding clinical decisions. This study compares the performance of existing classification systems-Milan, Minneapolis, Chicago, Leicester, Igls, and a novel Data-Driven approach-by evaluating their ability to differentiate transplant outcomes using metabolic and insulin secretion parameters. Our analysis shows strong concordance among Milan, Minneapolis, Chicago, and Igls, primarily due to minor variations in C-peptide thresholds. The Leicester and Data-Driven systems, however, exhibit greater divergence, with the Leicester system simplifying assessment by excluding severe hypoglycemic events and HbA1c, and the Data-Driven approach offering a more dynamic framework without p

SUBMITTER: Catarinella D 

PROVIDER: S-EPMC12313549 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature