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

Sudden cardiac death (SCD) remains a devastating but potentially preventable outcome in inherited cardiomyopathies. Although its absolute incidence is low, the possibility of preventing SCD through implantable cardioverter-defibrillators renders accurate arrhythmic risk stratification a central clinical priority. Risk prediction is evolving from phenotype-based stratification towards individualized approaches integrating genotype, imaging biomarkers, and clinical variables. This review critically evaluates available SCD risk prediction models across cardiomyopathy subtypes, including well-validated tools for hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular cardiomyopathy (ARVC), as well as emerging gene-specific models. We explore key methodological concepts and highlight limitations, such as data sparsity, endpoint heterogeneity, overfitting, and the lack of robust external validation. The application of fixed risk thresholds across diverse patient populations poses ethical and clinical challenges, particularly when competing risks such as heart failure or non-cardiac death are not adequately considered. Synthesis of aggregate data and graphical illustrations show how risk trajectories and mortality drivers differ by genotype and disease stage. Despite recent progress, most models are not yet embedded in routine care. Future advances will require dynamic, longitudinal, and multimodal models, designed for transparency, patient-centred decision making, and real-world implementation to meaningfully reduce mortality in cardiomyopathies.