Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation.

Journal: Pediatric transplantation
Published Date: Jun 1, 2025

Abstract

BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital heart disease. Listing center organ offer acceptance practices have been identified as a factor influencing waitlist outcomes. We utilized machine learning (ML) to identify factors associated with waitlist mortality, combining variables associated with institutional offer acceptance practices as well as candidate-specific risk factors.

Authors

  • Firezer Haregu
    Pediatric Cardiology, University of Virginia Children's Hospital, Charlottesville, Virginia, USA.
  • R Jerome Dixon
    Data Science, University of Virginia, Charlottesville, Virginia, USA.
  • Michael McCulloch
    Pediatric Cardiology, University of Virginia Children's Hospital, Charlottesville, Virginia, USA.
  • Michael Porter
    Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.

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