Automated discrimination of proximal right coronary artery occlusion from middle-to-distal right coronary artery occlusion and left circumflex occlusion in ST-elevation myocardial infarction.

BACKGROUND: Classifying the location of an occlusion in the culprit artery during ST-elevation myocardial infarction (STEMI) is important for risk stratification to optimize treatment. We developed a new logistic regression (LR) algorithm for 3-group classification of occlusion location as proximal right coronary artery (RCA), middle-to-distal RCA or left circumflex (LCx) coronary artery with inferior myocardial infarction. We compared the performance of the new LR algorithm with the recently introduced decision tree classifier of Fiol et al (Ann Noninvasive Electrocardiol. 2004;4:383-388) in the classification of the same 3 categories. METHODS: The new algorithm was developed on a set of electrocardiograms from an emergency department setting (n = 64) and tested on a different set from a prehospital setting (n = 68). All patients met the current STEMI criteria with angiographic confirmation of culprit artery and occlusion location. Using LR, 4 ST-segment deviation features were chosen by forward stepwise selection. Final LR coefficients were obtained by averaging more than 200 bootstrap iterations on the training set. In addition, a separate 4-feature classifier was designed adding ST features of V4R and V8, only available in the training set. RESULTS: The LR algorithm classified proximal RCA occlusion vs combined LCx occlusion and middle-to-distal RCA occlusion, with a sensitivity of 76% and specificity of 81% as compared with 71% and 62% for the Fiol classifier. The difference in specificity was statistically significant. The LR classifier trained with additional ST features of V4R and V8, but still limited to 4, improved the overall agreement in the training set from 65% to 70%. CONCLUSION: Discrimination of proximal RCA lesion location from LCx or middle-to-distal RCA using the new LR classifier shows improvement over decision tree-type classification criteria. Automated identification of proximal RCA occlusion could speed up the risk stratification of patients with STEMI. The addition of leads V4R and V8 should further improve the automated classification of the occlusion site in RCA and LCx.

Automated discrimination of proximal right coronary artery occlusion from middle-to-distal right coronary artery occlusion and left circumflex occlusion in ST-elevation myocardial infarction.

BACKGROUND: Classifying the location of an occlusion in the culprit artery during ST-elevation myocardial infarction (STEMI) is important for risk stratification to optimize treatment. We developed a new logistic regression (LR) algorithm for 3-group classification of occlusion location as proximal right coronary artery (RCA), middle-to-distal RCA or left circumflex (LCx) coronary artery with inferior myocardial infarction. We compared the performance of the new LR algorithm with the recently introduced decision tree classifier of Fiol et al (Ann Noninvasive Electrocardiol. 2004;4:383-388) in the classification of the same 3 categories. METHODS: The new algorithm was developed on a set of electrocardiograms from an emergency department setting (n = 64) and tested on a different set from a prehospital setting (n = 68). All patients met the current STEMI criteria with angiographic confirmation of culprit artery and occlusion location. Using LR, 4 ST-segment deviation features were chosen by forward stepwise selection. Final LR coefficients were obtained by averaging more than 200 bootstrap iterations on the training set. In addition, a separate 4-feature classifier was designed adding ST features of V4R and V8, only available in the training set. RESULTS: The LR algorithm classified proximal RCA occlusion vs combined LCx occlusion and middle-to-distal RCA occlusion, with a sensitivity of 76% and specificity of 81% as compared with 71% and 62% for the Fiol classifier. The difference in specificity was statistically significant. The LR classifier trained with additional ST features of V4R and V8, but still limited to 4, improved the overall agreement in the training set from 65% to 70%. CONCLUSION: Discrimination of proximal RCA lesion location from LCx or middle-to-distal RCA using the new LR classifier shows improvement over decision tree­type classification criteria. Automated identification of proximal RCA occlusion could speed up the risk stratification of patients with STEMI. The addition of leads V4R and V8 should further improve the automated classification of the occlusion site in RCA and LCx.

Conduction Disorders in the Setting of Acute STEMI.

ST-elevation myocardial (STEMI) is frequently associated with conduction disorders. Regional myocardial ischemia or injury may affect the cardiac conduction system at various locations, and neural reflexes or changes in the balance of the autonomous nervous system may be involved. Sinoatrial and atrioventricular blocks are more frequent in inferior than anterior STEMI, while new left anterior fascicular block and right bundle branch block indicate proximal occlusion of the left anterior descending coronary artery. New left bundle branch block is associated with multi-vessel disease. Most conduction disorders associated with STEMI are reversible with reperfusion therapy, but they may still impair prognosis because they indicate a large area at risk, extensive myocardial infarction or severe coronary artery disease. Acute STEMI recognition is possible in patients with a fascicular or right bundle branch block, but future studies need to define the cut-off values for ST depression in the leads V1-V3 in inferolateral MI and for ST elevation in the same leads in anterior STEMI. In the left bundle branch block, concordant ST elevation is a specific sign of acute coronary artery occlusion, but the ECG feature has low sensitivity.