Comparative analysis of outcomes in high KDPI spectrum kidney transplants using unsupervised machine learning algorithm.

Journal: PloS one
Published Date: Aug 26, 2025

Abstract

BACKGROUND: The Kidney Donor Profile Index (KDPI) is a continuous metric used to estimate the risk of allograft failure for kidneys from deceased donors. Lower KDPI scores are associated with longer post-transplant kidney function. This study aims to evaluate the outcomes of kidney transplantation using high-KDPI kidneys (98-100%) compared to those with moderately high KDPI scores (85-97%), employing a novel case-matching approach using machine learning.

Authors

  • Mahmoudreza Moein
    Division of Transplant Services, Department of Surgery, SUNY Upstate Medical University, Syracuse, New York, United States of America.
  • Alireza Golkarieh
    PhD Student in Computer Science and Informatics, Department of Computer Science and Engineering, Oakland University, Rochester, MI, USA.
  • Isabella Vlassis
    Division of Transplant Services, Department of Surgery, SUNY Upstate Medical University, Syracuse, New York, United States of America.
  • Reza Saidi
  • Michael Lioudis
    Division of Nephrology, Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, United States of America.

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