Exploring the Current Status of Risk Stratification in Hypertrophic Cardiomyopathy: From Risk Models to Promising...

Area of Science:

• Cardiology
• Medical Imaging
• Genetics

Background:

• Sudden cardiac death (SCD) prediction in hypertrophic cardiomyopathy (HCM) is critical.
• Current risk models may not suit all HCM phenotypes, especially those with extreme hypertrophy.
• Defibrillator implantation carries long-term risks, necessitating accurate risk stratification.

Purpose of the Study:

• To review current and emerging strategies for improving SCD risk prediction in HCM.
• To highlight the limitations of existing risk assessment tools.
• To explore novel approaches for more accurate risk stratification.

Main Methods:

• Review of existing literature on SCD risk factors in HCM.
• Analysis of the role of cardiac magnetic resonance imaging (CMR) in assessing myocardial fibrosis.
• Exploration of electrophysiological studies (EPS) and artificial intelligence (AI) in risk prediction.

Main Results:

• Traditional risk factors (hypertrophy, syncope, family history) have limitations.
• Myocardial fibrosis on CMR is an increasingly recognized predictor of SCD.
• Integrating advanced imaging, genetics, and AI shows promise for refined risk assessment.

Conclusions:

• Optimizing SCD risk prediction in HCM requires moving beyond traditional factors.
• Cardiac MRI and electrophysiological studies offer valuable insights.
• Future research integrating novel imaging, genetics, and AI algorithms is essential for improved patient management.