HCMR (NHLBI): multidimensionele risicovoorspelling beter dan SCD-gefocuste richtlijnen bij hypertrofische cardiomyopathie

Importance: Current risk prediction guidelines for hypertrophic cardiomyopathy predict only sudden cardiac death and are imperfect, leading to avoidable deaths and unnecessary implantable cardioverter defibrillators. Objective: To combine prospectively collected clinical history, imaging, genetic, and biomarker data to improve risk prediction of adverse events in hypertrophic cardiomyopathy. Design, Setting, and Participants: A total of 2,750 patients with hypertrophic cardiomyopathy were prospectively enrolled in the registry-based study from 44 sites in North America and Europe with expertise in hypertrophic cardiomyopathy and cardiac magnetic resonance (CMR) imaging. Participants were enrolled from April 1, 2014, to April 7, 2017. Mean follow-up exceeded 7 years. Exposures: Patients underwent a health history questionnaire, blood sampling for biomarkers and genotyping, and contrast-enhanced CMR. Main Outcomes and Measures: The predefined composite adjudicated primary end point was time to first event for hypertrophic cardiomyopathy–related deaths; nonfatal sustained ventricular arrhythmias requiring cardioversion or defibrillation; and left ventricular assist device implant or heart transplant. A secondary end point was a composite of sudden cardiac death and nonfatal VA events. The elastic-net method identified the most important predictors. Cox proportional hazards regression assessed associations with time to the first end point. Results: Of the 2,750 prospectively enrolled patients, 2,698 (98%) had analyzable data; 1,919 (71%) were male, mean age 50 years. The integrated multidimensional model outperformed traditional risk prediction restricted to sudden cardiac death, identifying patients at risk for HF events, heart transplant, and ventricular arrhythmias that were previously under-recognized. Conclusions: A multidimensional risk prediction model combining clinical, imaging, genetic and biomarker data provides more comprehensive risk stratification in hypertrophic cardiomyopathy than the current SCD-focused frameworks.