BACKGROUND: Rapid identification of a proximal occlusion site of a major coronary artery is of paramount importance in the care of myocardial infarction (MI). It is increasingly recognized that routine electrocardiogram (ECG) can be used for that purpose, provided that expert interpretation is available. Computer-based signal analysis has potential to enhance early ECG interpretation but its performance must be validated against manual algorithms. We therefore set out to develop a computer-assisted model to detect proximal occlusion of the left anterior descending coronary artery (LAD) in patients with suspected acute coronary syndrome (ACS). METHODS: Based on manual anatomical interpretation of the ECG, obtained from 216 consecutive patients who were admitted due to suspected ACS, an automatic computerized ECG model to detect LAD occlusion was constructed. Agreement between manual evaluation of the ECG by two cardiologists and a computerized ECG algorithm to detect occlusion of the LAD and the site of occlusion was determined. RESULTS: Using an expert electrocardiographer's anatomical interpretation as the gold standard, the computer model recognized patients fulfilling ECG criteria for any occlusion of the LAD with a specificity of 99% and a sensitivity of 67% (kappa= 0.71). However, proximal LAD occlusion was detected with 100% specificity and 86% sensitivity (kappa= 0.72). The computer program detected a distal occlusion in the LAD with a specificity of 99% and a sensitivity of 40% (kappa= 0.72). CONCLUSIONS: Computerized anatomical interpretation of the ECG is feasible and allows detection of a proximal LAD occlusion with excellent accuracy.
BACKGROUND: Rapid identification of a proximal occlusion site of a major coronary artery is of paramount importance in the care of myocardial infarction (MI). It is increasingly recognized that routine electrocardiogram (ECG) can be used for that purpose, provided that expert interpretation is available. Computer-based signal analysis has potential to enhance early ECG interpretation but its performance must be validated against manual algorithms. We therefore set out to develop a computer-assisted model to detect proximal occlusion of the left anterior descending coronary artery (LAD) in patients with suspected acute coronary syndrome (ACS). METHODS: Based on manual anatomical interpretation of the ECG, obtained from 216 consecutive patients who were admitted due to suspected ACS, an automatic computerized ECG model to detect LAD occlusion was constructed. Agreement between manual evaluation of the ECG by two cardiologists and a computerized ECG algorithm to detect occlusion of the LAD and the site of occlusion was determined. RESULTS: Using an expert electrocardiographer's anatomical interpretation as the gold standard, the computer model recognized patients fulfilling ECG criteria for any occlusion of the LAD with a specificity of 99% and a sensitivity of 67% (kappa= 0.71). However, proximal LAD occlusion was detected with 100% specificity and 86% sensitivity (kappa= 0.72). The computer program detected a distal occlusion in the LAD with a specificity of 99% and a sensitivity of 40% (kappa= 0.72). CONCLUSIONS: Computerized anatomical interpretation of the ECG is feasible and allows detection of a proximal LAD occlusion with excellent accuracy.
Authors: Markku J Eskola; Kjell C Nikus; Liisa-Maria Voipio-Pulkki; Heini Huhtala; Tiina Parviainen; Juha Lund; Tuomo Ilva; Pekka Porela Journal: Am J Cardiol Date: 2005-10-14 Impact factor: 2.778
Authors: M Kosuge; K Kimura; T Ishikawa; T Endo; T Shigemasa; M Sugiyama; O Tochikubo; S Umemura Journal: Clin Cardiol Date: 2001-01 Impact factor: 2.882
Authors: Juhana Karha; Sabina A Murphy; Ajay J Kirtane; James A de Lemos; Julian M Aroesty; Christopher P Cannon; Elliott M Antman; Eugene Braunwald; C Michael Gibson Journal: Am J Cardiol Date: 2003-10-15 Impact factor: 2.778