Key result
Integrating CMR with clinical variables improves sudden cardiac death risk prediction over traditional HCM scores.
Why the study?
Current risk stratification for sudden cardiac death in HCM relies primarily on the HCM Risk-SCD score, but its predictive accuracy remains suboptimal.
Does a comprehensive risk prediction model integrating CMR and clinical parameters improve sudden cardiac death risk stratification in patients with hypertrophic cardiomyopathy compared to the traditional HCM Risk-SCD score?
Cohort (n=576)
No
Does a comprehensive risk prediction model integrating CMR and clinical parameters improve sudden cardiac death risk stratification in patients with hypertrophic cardiomyopathy compared to the traditional HCM Risk-SCD score?
Integrating CMR parameters with clinical variables significantly improves sudden cardiac death risk prediction in hypertrophic cardiomyopathy compared to the traditional guideline-recommended HCM Risk-SCD score.
May refine SCD risk stratification in HCM; extends traditional scores but remains hypothesis-generating pending external validation.
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.
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Ding et al. (2026) conducted a cohort in hypertrophic cardiomyopathy (n=576). Integration of cardiac magnetic resonance parameters with clinical variables improved sudden cardiac death risk prediction in hypertrophic cardiomyopathy, with a C-index of 0.607 and 58 events recorded.
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