Risk models for sudden cardiac death in cardiomyopathies: clinical, methodological and ethical challenges

Area of Science:

• Cardiology
• Genetics
• Biomarkers

Background:

• Sudden cardiac death (SCD) is a critical concern in inherited cardiomyopathies.
• Preventing SCD via implantable cardioverter-defibrillators necessitates precise risk stratification.
• Current risk prediction is shifting from phenotype-based to individualized strategies.

Purpose of the Study:

• To critically evaluate existing SCD risk prediction models for cardiomyopathies.
• To explore methodological concepts and limitations in current risk stratification tools.
• To discuss the future of risk prediction for reducing mortality.

Main Methods:

• Review of available SCD risk prediction models across cardiomyopathy subtypes (HCM, ARVC).
• Evaluation of phenotype-based, genotype-based, and multimodal approaches.
• Analysis of methodological challenges including data sparsity and validation.

Main Results:

• Validated tools exist for hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular cardiomyopathy (ARVC).
• Emerging gene-specific models show promise but require further validation.
• Limitations include data sparsity, endpoint heterogeneity, and lack of external validation.

Conclusions:

• Current risk models are not widely implemented in routine care.
• Fixed risk thresholds pose challenges when competing risks are not considered.
• Future models must be dynamic, longitudinal, multimodal, and patient-centered for effective mortality reduction.