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Merit: A Machine Learning-enhanced Mortality Risk Calculator For Infant Heart Transplantation
Rohit Ganduboina, MBBS1, Michele Dell'Aquilla, MD1, Marcus Haw, MD2, Osama El Tayeb, MD2, Sandeep Sainathan, MD2.
1Northwell Health Cardiovascular Institute, New Hyde Park, NY, USA, 2Corewell Health, Helen Devos Children's Hospital/ Michigan State University, Grand Rapids, MI, USA.
Objective(s):Infant heart transplantation remains among the highest-risk procedures in congenital cardiac surgery, yet no dedicated pretransplant tool exists to quantify individualized mortality risk at the time of donor offer evaluation.
Methods:Infants (<1year) undergoing isolated orthotopic heart transplantation in UNOS (1987-2024; N=3,600) were analyzed. Clinically prespecified pretransplant variables underwent multivariable logistic regression with LASSO penalization to derive the MERIT predictor backbone. Primary models estimated 30-day and 1-year mortality, with exploratory morbidity models. Internal validation included 1,000-bootstrap correction, temporal stress testing, calibration, decision curve analysis, and XGBoost benchmarking. Final model outputs were deployed into an interactive web-based calculator (MERIT).
Results:Thirty-day and 1-year mortality were 7.9% (285 deaths) and 17.0% (613 deaths) respectively. Bootstrap optimism profiles were similar between standard and penalized models, supporting stability of retained predictors. MERIT demonstrated good discrimination for 30-day mortality (apparent AUC-0.75; optimism-corrected AUC-0.74) and moderate discrimination for 1-year mortality (apparent AUC-0.69; optimism-corrected AUC-0.68). Calibration remained strong with slopes of 1.05 and 1.04, respectively. Clinically derived MERIT strata demonstrated progressive separation in observed 30-day mortality from 2.1% in low-risk infants to 19.0% in very-high-risk infants. Decision curve analysis showed sustained positive net clinical benefit across broad threshold probabilities (Figure 1).
Conclusions:MERIT score demonstrated favorable discrimination, calibration, and clinical utility, supporting its potential role as a practical decision-support adjunct for donor acceptance, perioperative planning, and family counseling in infant heart transplantation.
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