Using machine learning to estimate survival curves for patients receiving an increased risk for disease transmission heart, liver, or lung versus waiting for a standard organ.

ABSTRACT:

Introduction

Over 19% of deceased organ donors are labeled increased risk for disease transmission (IRD) for viral blood-borne disease transmission. Many potential organ recipients need to decide between accepting an IRD organ offer and waiting for a non-IRD organ.

Methods

Using machine learning and simulation, we built transplant and waitlist survival models and compared the survival for patients accepting IRD organ offers or waiting for non-IRD organs for the heart, liver, and lung. The simulation consisted of generating 20 000 different scenarios of a recipient either receiving an IRD organ or waiting and receiving a non-IRD organ.

Results

In the simulations, the 5-year survival probabilities of heart, liver, and lung recipients who accepted IRD organ offers increa

SUBMITTER: Mark E 

PROVIDER: S-EPMC9285951 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature