Lori Vales1, Yumiko Kanei, Paul Schweitzer. 1. Division of Cardiology, Department of Medicine, The Heart Institute at Beth Israel Medical Center, New York, NY 10003, USA. lvalesmd@gmail.com
Abstract
BACKGROUND: In acute inferior ST-segment elevation myocardial infarction (STEMI), multiple electrocardiographic algorithms have been proposed to predict the culprit artery. Our purpose is to review these and compare them to ST depression in lead aVR to predict culprit artery in inferior STEMI. METHODS: In 106 patients with acute inferior STEMI who underwent emergent coronary angiography, we correlated electrocardiographic and angiographic findings pertaining to the culprit artery. We then reviewed the algorithms proposed by Fiol et al and Tierala et al, and applied them and our own from Kanei et al using ST depression in aVR for predicting the left circumflex artery (LCx) as the culprit, to the population. Finally, we compared the sensitivities and specificities of the respective algorithms for predicting the culprit artery. RESULTS: The sensitivity and specificity of ST depression in lead aVR to predict LCx as the culprit were 53% and 86%, respectively, and 86% and 55%, respectively for predicting the right coronary artery (RCA) as the culprit. When their algorithms were applied to our population, the sensitivities and specificities of Fiol et al and Tierala et al were slightly higher. CONCLUSION: Compared to other proposed algorithms, ST depression in aVR is a simple method with satisfactory sensitivity and specificity to predict the culprit artery in inferior STEMI.
BACKGROUND: In acute inferior ST-segment elevation myocardial infarction (STEMI), multiple electrocardiographic algorithms have been proposed to predict the culprit artery. Our purpose is to review these and compare them to ST depression in lead aVR to predict culprit artery in inferior STEMI. METHODS: In 106 patients with acute inferior STEMI who underwent emergent coronary angiography, we correlated electrocardiographic and angiographic findings pertaining to the culprit artery. We then reviewed the algorithms proposed by Fiol et al and Tierala et al, and applied them and our own from Kanei et al using ST depression in aVR for predicting the left circumflex artery (LCx) as the culprit, to the population. Finally, we compared the sensitivities and specificities of the respective algorithms for predicting the culprit artery. RESULTS: The sensitivity and specificity of ST depression in lead aVR to predict LCx as the culprit were 53% and 86%, respectively, and 86% and 55%, respectively for predicting the right coronary artery (RCA) as the culprit. When their algorithms were applied to our population, the sensitivities and specificities of Fiol et al and Tierala et al were slightly higher. CONCLUSION: Compared to other proposed algorithms, ST depression in aVR is a simple method with satisfactory sensitivity and specificity to predict the culprit artery in inferior STEMI.