Value of convex-type ST-segment elevation and abnormal Q waves for electrocardiographic-based identification of left

Maky Furuki1, Hiroya Kawai, Tetsuari Onishi

  • 1Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.

Insights

Convex ST-segment elevation and abnormal Q waves on electrocardiograms may indicate left ventricular remodeling in hypertrophic cardiomyopathy patients. These findings aid in detecting disease progression, improving patient monitoring and outcomes.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Electrocardiography

Background:

  • Hypertrophic cardiomyopathy (HCM) presents variable and unpredictable clinical courses.
  • High morbidity and mortality necessitate effective screening and patient evaluation.
  • Left ventricular remodeling is a key factor in HCM progression.

Purpose of the Study:

  • To investigate the association between specific electrocardiographic (ECG) findings and left ventricular (LV) remodeling in HCM.
  • To identify ECG markers predictive of LV enlargement and wall motion abnormalities.
  • To propose ECG findings as indicators of LV remodeling in HCM patients.

Main Methods:

  • Analysis of 12-lead electrocardiograms (ECGs) and standard echocardiograms in 110 HCM patients.
  • Categorization of ST-segment elevation into concave, straight, and convex patterns.
  • Follow-up evaluation after a mean interval of 20.3 months.

Main Results:

  • ST-segment elevation observed in 43.6% and abnormal Q waves in 18.1% of ECGs.
  • Left ventricular enlargement detected in 12.7% and wall motion abnormalities in 21.8% of echocardiograms.
  • Convex ST-segment elevation and/or abnormal Q waves showed a significant correlation (62% sensitivity, 85% specificity) with LV enlargement/wall motion abnormalities.

Conclusions:

  • Convex ST-segment elevation and abnormal Q waves are valuable indicators of LV remodeling in HCM.
  • These ECG findings can aid in the early detection of disease progression.
  • The study highlights the utility of specific ECG patterns for non-invasive assessment of HCM.

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