1. Pediatric donor heart acceptance practices in the United States: What is really being considered?
- Author
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McCulloch, M. A., Alonzi, L. P., White, S. C., Haregu, F., and Porter, M. D.
- Subjects
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HEART transplantation , *HEART , *RANDOM forest algorithms , *LOGISTIC regression analysis , *BEHAVIORAL economics - Abstract
Background: Recent studies demonstrate high offer decline and organ non‐utilization rates are associated with increased pediatric heart transplant waitlist mortality. We sought to determine which donor, candidate, and offer specific variables most importantly influenced these decisions using only data available at the time of each offer. Methods: Retrospective review of pediatric (<18 years) heart donor offers made to pediatric candidates in the United States between 2010 and 2020. In addition to standard donor, candidate, and offer data available in UNOS, we extracted objective and qualitative valvar and myocardial function data from all available donor echocardiogram reports. Results: During the study period, 5625 pediatric donor hearts produced 30 156 offers to 4905 unique candidates, of which 88.7% of all offers were declined and 39.2% of organs were not utilized by pediatric waitlisted candidates. Of the 60.8% utilized hearts, 89.7% had a 'cumulatively' normal echocardiogram at the time of offer acceptance; 62.9% of hearts not utilized for a pediatric candidate also had a cumulatively normal final echocardiogram. Random forest and logistic regression modeling demonstrated good predictive performance (AUROC ≥0.83) of likelihood to accept when utilizing donor, candidate, and offer specific variables. SHAP variable importance scores demonstrated number of prior offer declines and candidate institution's prior year acceptance rates as the two most important variables influencing offer decisions. Conclusions: Behavioral economics appear to play a significant role in pediatric heart transplant candidate institutions' acceptance practices, even when considering the arguably healthier pediatric donor population. Removal of prior institution's decisions from DonorNet may help increase donor utilization. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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