The Pediatric Pulmonary Hypertension International Risk Score: A Prediction Model for Outcomes Using Machine Learning

Abstract

BACKGROUND: Risk prediction is fundamental to pulmonary hypertension (PH) guideline-based care, yet pediatric-specific risk prediction models remain limited, relying primarily on single predictors, expert opinion, or application of adult models to children. The authors developed and externally validated a data-driven 1-year risk prediction model for pediatric PH. METHODS: Pediatric patients with PH (n=345; World Symposium on Pulmonary Hypertension groups 1 and 3) enrolled in the Pediatric Pulmonary Hypertension Network Registry (2014–2020; 50.4% male; median age, 4.9 years [interquartile range, 1.9–10.3]) were split into training (80%) and test cohorts (20%). The Dutch National Registry for Pulmonary Hypertension in Childhood (n=155 [1993–2020]) and the Spanish Registry of Pediatric Pulmonary Hypertension (n=327 [2009–2023]) were used for external validation. From 176 variables, BorutaSHAP feature selection with random forest identified 16 predictors for a 1-year outcome of time to death, transplant, Potts shunt, or atrial septostomy, modeled using extreme gradient boosting. Performance was assessed with the area under the receiver operating characteristic curve, confusion matrices, calibration, and Kaplan-Meier event-free survival. RESULTS: The final model achieved an area under the receiver operating characteristic curve of 0.90 (0.79–0.97) and 99% (96%–99%) negative predictive value in testing, dividing participants into 3 groups with strong outcome discrimination. External validation showed an area under the receiver operating characteristic curve of 0.76 (Dutch National Registry for Pulmonary Hypertension in Childhood, 0.70–0.81) and 0.77 (Spanish Registry of Pediatric Pulmonary Hypertension, 0.73–0.82) with negative predictive values of 93% (93%–97%) and 96% (93%–97%), respectively. Kaplan-Meier analysis significantly differentiated outcomes by risk group. CONCLUSIONS: This multicenter, validated model provides good 1-year risk prediction in pediatric PH across World Symposium on Pulmonary Hypertension groups 1 and 3, providing a robust tool for clinical risk stratification to guide therapy and addressing a gap in pediatric PH care.