Mimics Innovation Awards Finalist 2021: Nicholas A. Szugye

To create a predictive model that accurately assesses size matching in pediatric heart transplantation by measuring donor total cardiac volume (TCV), based on anthropometric and chest X-ray cardiac measurements.

The pediatric heart transplant community uses weight-based donor-to-recipient size matching almost exclusively, despite no evidence to validate weight as a reliable surrogate of cardiac size. Donor size mismatch is the second most common reason for the refusal of donor hearts in current practice (>30% of all refusals).

N. Szugye and their team sought to establish a predictive model for donor TCV on the basis of anthropomorphic and chest X-ray (CXR) cardiac measures.

Szugye’s predictive model that takes into account weight, height, sex, age, AND a 1-view anteroposterior chest X-ray proves to be a reliable and consistent method to improve size matching. Therefore, TCV can be accurately predicted from readily available anthropometrics and CXR heart width. This simple method of TCV estimation can provide a reliable and consistent method to assess donor TCV. In future studies, TCV-based size matching can be used to set more accurate donor size criteria and assess the correlation of TCV with patient outcomes.