Prevalence and characteristics of normal electrocardiograms in hypertrophic cardiomyopathy

Arda Guler1, Busra Kuru Gorgulu1, Ozgur Surgit1

  • 1Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Cardiology, Istanbul, Türkiye.

Insights

A normal electrocardiogram (ECG) is rare in hypertrophic cardiomyopathy (HCM), occurring in only 1.6% of patients. Despite this, a normal ECG does not rule out HCM, highlighting its importance in diagnosis.

Area of Science:

  • Cardiology
  • Genetics
  • Medical Diagnostics

Background:

  • Hypertrophic cardiomyopathy (HCM) is a genetic heart condition causing left ventricular hypertrophy (LVH).
  • While most HCM patients have abnormal ECGs, a subset presents with normal results, potentially delaying diagnosis.
  • This study investigates the prevalence and characteristics of HCM patients with normal ECGs.

Purpose of the Study:

  • To determine the prevalence of normal ECGs in diagnosed HCM patients.
  • To identify clinical characteristics associated with normal ECGs in HCM.
  • To explore the relationship between ECG findings and disease severity indicators.

Main Methods:

  • Retrospective analysis of 682 HCM patients meeting European Society of Cardiology (ESC) criteria.
  • Exclusion of patients with secondary causes of LVH or infiltrative cardiomyopathies.
  • Definition of abnormal ECG based on specific criteria including arrhythmias, conduction blocks, and voltage criteria.

Main Results:

  • Only 1.6% of HCM patients (11/682) had completely normal ECGs.
  • Normal ECGs correlated with lower NT-proBNP, reduced pulmonary artery pressure, and better right ventricular function.
  • Increased ECG abnormalities correlated with greater wall thickness, higher NT-proBNP, and increased sudden cardiac death risk.

Conclusions:

  • A normal ECG is uncommon in HCM but does not exclude the diagnosis.
  • The ECG remains a crucial, accessible tool for screening and early HCM detection.
  • ECG findings correlate with disease severity, aiding in risk stratification.
Abstract

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