Abstract
BACKGROUND: Current risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM) relies primarily on the HCM Risk-SCD score, but its predictive accuracy remains suboptimal. OBJECTIVES: This study aimed to develop and validate a comprehensive risk prediction model integrating cardiac magnetic resonance (CMR) parameters with clinical and biomarker variables. METHODS: We analyzed 576 consecutive HCM patients from a tertiary referral center. The primary endpoint was sudden death or appropriate implantable cardioverter-defibrillator therapy. We developed four prediction models: (1) Traditional (HCM Risk-SCD alone), (2) Clinical (traditional + clinical variables), (3) CMR (traditional + CMR parameters), and (4) Comprehensive (integrating all variables). Model performance was assessed using C-index and time-dependent receiver operating characteristic (ROC) analysis. RESULTS: During median follow-up of 3 years, 58 patients (10.1%) experienced the primary endpoint. The comprehensive model demonstrated superior performance (C-index 0.607) compared to traditional (0.565), clinical (0.598), and CMR (0.607) models. In multivariable analysis, CMR ejection fraction (HR: 0.94, 95% CI: 0.91-0.97, P < 0.001) and left ventricular diastolic pressure (HR: 0.94, 95% CI: 0.89-0.98, P = 0.010) were independent predictors. Time-dependent ROC analysis showed maintained predictive accuracy over 3 years (AUC 0.78-0.85). Risk stratification using the comprehensive model effectively discriminated low, intermediate, and high-risk groups (log-rank P < 0.001). CONCLUSIONS: Integration of CMR parameters with clinical variables significantly improves SCD risk prediction in HCM compared to traditional risk stratification. The comprehensive model provides enhanced accuracy for identifying high-risk patients who may benefit from primary prevention implantable cardioverter-defibrillator therapy.