Computerized classification of proximal occlusion in the left anterior descending coronary artery

J Electrocardiol. 2010 Nov-Dec;43(6):634-9. doi: 10.1016/j.jelectrocard.2010.07.012.

Abstract

Proximal occlusion within the left anterior descending (LAD) coronary artery in patients with acute myocardial infarction leads to higher mortality than does nonproximal occlusion. We evaluated an automated program to detect proximal LAD occlusion. All patients with suspected acute coronary syndrome (n = 7,710) presenting consecutively to the emergency department of a local hospital with a coronary angiogram–confirmed flow-limiting lesion and notation of occlusion site were included in the study (n = 711). Electrocardiograms (ECGs) that met ST-segment elevation myocardial infarction (STEMI) criteria were included in the training set (n = 183). Paired angiographic location of proximal LAD and ECGs with ST elevation in the anterolateral region were used for the computer program development (n = 36). The test set was based on ECG criteria for anterolateral STEMI only without angiographic reports (n = 162). Tested against 2 expert cardiologists' agreed reading of proximal LAD occlusion, the algorithm has a sensitivity of 95% and a specificity of 82%. The algorithm is designed to have high sensitivity rather than high specificity for the purpose of not missing any proximal LAD in the STEMI population. Our preliminary evaluation suggests that the algorithm can detect proximal LAD occlusion as an additional interpretation to STEMI detection with similar accuracy as cardiologist readers.

Publication types

  • Evaluation Study

MeSH terms

  • Aged
  • California / epidemiology
  • Coronary Stenosis / diagnosis*
  • Coronary Stenosis / epidemiology*
  • Diagnosis, Computer-Assisted / methods*
  • Diagnosis, Computer-Assisted / statistics & numerical data
  • Electrocardiography / methods*
  • Electrocardiography / statistics & numerical data
  • Female
  • Humans
  • Male
  • Middle Aged
  • Observer Variation
  • Prevalence
  • Reproducibility of Results
  • Sensitivity and Specificity