Abstract
BACKGROUND: Robust risk assessment is crucial for the growing repaired tetralogy of Fallot population at risk of major adverse clinical outcomes; however, current tools are hindered by lack of validation. This study aims to develop and validate a risk prediction model for death in the repaired tetralogy of Fallot population. METHODS AND RESULTS: Patients with repaired tetralogy of Fallot enrolled in the INDICATOR (International Multicenter Tetralogy of Fallot Registry) cohort with clinical, arrhythmia, cardiac magnetic resonance, and outcome data were included. Patients from London, Amsterdam, and Boston sites were placed in the development cohort; patients from the Toronto site were used for external validation. Multivariable Cox regression was used to evaluate factors associated with time from cardiac magnetic resonance until the primary outcome: all-cause death. Of 1552 eligible patients (n=1221 in development, n=331 in validation; median age at cardiac magnetic resonance 23.4 [interquartile range, 15.6-35.6] years; median follow up 9.5 years), 102 (6.6%) experienced the primary outcome. The multivariable Cox model performed similarly during development (concordance index, 0.83 [95% CI, 0.78-0.88]) and external validation (concordance index, 0.80 [95% CI, 0.71-0.90]) and identified older age at cardiac magnetic resonance, obesity, type of tetralogy of Fallot repair, higher right ventricular end-systolic volume index, and lower biventricular global function index as independent predictors of death. A risk-scoring algorithm dividing patients into low-risk (score ≤4) versus high-risk (score >4) groups was validated to effectively discriminate risk of death (15-year survival of 95% versus 74%, respectively; P<0.001). CONCLUSIONS: This externally validated mortality risk prediction algorithm can help identify vulnerable patients with repaired tetralogy of Fallot who may benefit from targeted interventions.