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<p>Portable, scalable, and accessible artificial intelligence (AI)-enabled smartwatch technology shows promise as a cardiovascular risk stratification strategy in the general adult population. The challenges of lifelong care in congenital heart disease (CHD)—inclusive of regional and socioeconomic disparities worldwide—underscore the need for similar solutions tailored to this population. Herein, we present the first noise-adapted single-lead ECG model for predicting left ventricular systolic dysfunction (left ventricular ejection fraction [LVEF] ≤ 40%) in pediatric and CHD patients. The internal cohort was comprised of 70,226 patients. External test groups included Children’s Hospital of Philadelphia (CHOP; 42,984 patients) and Toronto General Hospital (TGH; 284 repaired tetralogy of Fallot patients). Our model had strong performance across a broad range of CHD lesions, races, ages, and healthcare systems. Our findings support the potential of AI-enabled wearables to expand global access to CHD care. Prospective studies utilizing wearable ECG devices in pediatric and CHD patients are warranted.</p>

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Single lead electrocardiographic detection of left ventricular systolic dysfunction in pediatric and congenital heart disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Joshua Mayourian,
  • Ivor B. Asztalos,
  • William La Cava,
  • Ryan L. Kobayashi,
  • Sunil J. Ghelani,
  • Victoria L. Vetter,
  • Rachel M. Wald,
  • Anne Marie Valente,
  • Tal Geva,
  • John K. Triedman

摘要

Portable, scalable, and accessible artificial intelligence (AI)-enabled smartwatch technology shows promise as a cardiovascular risk stratification strategy in the general adult population. The challenges of lifelong care in congenital heart disease (CHD)—inclusive of regional and socioeconomic disparities worldwide—underscore the need for similar solutions tailored to this population. Herein, we present the first noise-adapted single-lead ECG model for predicting left ventricular systolic dysfunction (left ventricular ejection fraction [LVEF] ≤ 40%) in pediatric and CHD patients. The internal cohort was comprised of 70,226 patients. External test groups included Children’s Hospital of Philadelphia (CHOP; 42,984 patients) and Toronto General Hospital (TGH; 284 repaired tetralogy of Fallot patients). Our model had strong performance across a broad range of CHD lesions, races, ages, and healthcare systems. Our findings support the potential of AI-enabled wearables to expand global access to CHD care. Prospective studies utilizing wearable ECG devices in pediatric and CHD patients are warranted.