Comparison of computer ST criteria for diagnosis of severe coronary artery disease

P M Ribisl1, J Liu, I Mousa

  • 1Cardiology Department, Long Beach Veterans Affairs Medical Center, California.

Insights

Computer-scored ST depression during exercise tests effectively predicts coronary artery disease severity. Horizontal or downsloping ST depression is the strongest indicator of severe disease, aiding in accurate diagnosis.

Area of Science:

  • Cardiology
  • Exercise Physiology
  • Medical Diagnostics

Background:

  • Coronary artery disease (CAD) diagnosis relies on accurate assessment of disease severity.
  • Exercise testing is a common method for evaluating CAD.
  • Computerized electrocardiogram (ECG) analysis offers potential for objective ST-segment evaluation.

Purpose of the Study:

  • To compare the efficacy of different computer-scored ST-segment criteria in predicting the extent and severity of coronary artery disease.
  • To identify the most powerful computer-derived predictor of severe CAD during exercise testing.

Main Methods:

  • A cohort of 230 male veterans underwent both coronary angiography and treadmill exercise testing.
  • Computerized analysis of ST-segment criteria from exercise ECGs was performed.
  • Discriminant function analysis was used to identify predictors of severe CAD.

Main Results:

  • Significant differences in computer-scored ST criteria were found across increasing CAD severity, with three-vessel/left main disease showing distinct responses.
  • Horizontal or downsloping ST depression at the J junction during or after exercise was the most potent predictor of severe CAD.
  • A 0.075 mV threshold for ST depression demonstrated 50% sensitivity and 71% specificity for severe disease, improved to 57% sensitivity with exercise capacity.

Conclusions:

  • Computerized ECG measurements during exercise testing can accurately predict CAD severity.
  • Horizontal or downsloping ST-segment depression is a key marker for identifying severe coronary artery disease, mirroring traditional visual interpretation.

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