Getting ahead of sudden cardiac arrest in pediatric hypertrophic cardiomyopathy

Shuenn-Nan Chiu1,2, Wei-Chieh Tseng1,2, Jyh-Ming Jimmy Juang2,3

  • 1Department of Pediatrics, National Taiwan University, Taipei, Taiwan.

Insights

Sudden cardiac arrest (SCA) in pediatric hypertrophic cardiomyopathy (HCM) is a major challenge. New approaches aim to detect vulnerable individuals before disease onset, improving prevention strategies for children with HCM.

Area of Science:

  • Cardiology
  • Pediatric Electrophysiology
  • Genetic Cardiology

Background:

  • Sudden cardiac arrest (SCA) is a devastating complication of pediatric hypertrophic cardiomyopathy (HCM).
  • Current risk stratification and prevention strategies for pediatric HCM are limited, often relying on established disease phenotypes.
  • Many pediatric patients present with SCA as the first clinical manifestation of HCM.

Purpose of the Study:

  • To review current evidence on pediatric HCM, focusing on epidemiology, arrhythmogenic mechanisms, and limitations of existing risk models.
  • To explore emerging insights into electrical vulnerability preceding structural disease in pediatric HCM.
  • To propose a shift towards upstream detection of vulnerable individuals using advanced screening strategies.

Main Methods:

  • MEDLINE-based literature search using keywords: HCM, SCA, pediatric.
  • Synthesis of current evidence on pediatric HCM epidemiology, characteristics, and arrhythmogenic mechanisms.
  • Review of limitations in current risk stratification and prevention strategies.

Main Results:

  • Existing risk stratification models for pediatric HCM have limitations, particularly for patients without a clear phenotype.
  • Electrical vulnerability may precede overt structural disease in pediatric HCM.
  • Electrocardiography-based screening strategies are evolving.

Conclusions:

  • There is a critical need for improved strategies to prevent sudden cardiac death (SCD) in pediatric HCM.
  • A paradigm shift from post-diagnosis risk prediction to upstream detection of vulnerable individuals is proposed.
  • Integrating clinical expertise with advanced technologies like artificial intelligence and enhanced electrocardiography may facilitate earlier identification and prevention.
Abstract

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