Better matching donated hearts to children waiting for transplant
Improving Pediatric Donor Heart Utilization with Predictive Analytics
Using computer learning to help doctors quickly decide if a donated heart is a good match for a child on the transplant list.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Virginia NIH-funded |
| Lab location | 1 site (Charlottesville, United States) |
| Project ID | NIH-11196223 on NIH RePORTER |
What this research studies
If your child is on a heart transplant list, this work builds computer models that predict how a particular donated heart would affect their survival after transplant and how long they might wait for another offer if the heart is declined. Researchers will train the models on every US pediatric heart offer from 2010–2020—about 30,000 offers—to learn which donor and candidate factors matter most. The tools are designed to be used at the time a heart is offered, giving clinicians quick, evidence-based probabilities to guide acceptance or refusal decisions. The project aims to help more usable hearts reach the right children faster while maintaining safe post-transplant outcomes.
Who could benefit from this research
Good fit: Children listed for heart transplant—especially those with end-stage heart failure or complex congenital heart defects—are the patients this work aims to help.
Not a fit: Adults, children not listed for transplant, or patients outside the United States are unlikely to directly benefit from this project.
Why it matters
Potential benefit: If successful, this could help more donated hearts be used for children in need and reduce deaths while waiting for transplant.
How similar studies have performed: Related machine-learning tools have shown promise in adult organ allocation and risk prediction, but a national pediatric-specific tool like this is largely new.
Where this research is happening
Charlottesville, United States
- University of Virginia — Charlottesville, United States (Active)
Researchers
- Principal investigator: Mcculloch, Michael a. — University of Virginia
- Study coordinator: Mcculloch, Michael a.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.