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ECG Identifying the Culprit Coronary Artery

Yuan's General Hospital · 2015
ClinicalTrials.gov · Datasets · License: Public Domain · 2015
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Acute myocardial infarction (AMI) usually occurs suddenly and is associated with considerably high mortality rate. The infarct-related artery in inferior wall AMI is usually located at right coronary artery (RCA), less often at left circumflex coronary artery (LCX). Inferior wall AMI occlusive site before the first right ventricular branch of RCA was more frequently associated with right ventricular infarction, which had higher incidence of bradyarrhythmia, shock, and in-hospital death. Early recognition of the site of infarct-related artery especially combination with right ventricular infarction and respond promptly may result in a significant reduction in in-hospital mortality and morbidity. There were several non-invasive methods to predict the culprit site, which including: radioneuclear imaging study, echocardiography or electrocardiogram. Among these methods, electrocardiogram is one of the most simple and convenient tool. Several algorisms have investigated but these algorisms included using leads III, II, I, aVL, V1, V2, V3, V5 and V6, which can only differentiate RCA and LCX lesions but cannot assure whether the culprit site is located at proximal or distal RCA. Thus, the aim of this study is designing a method which is simple and useful in identifying the culprit sites in inferior wall acute myocardial infarction (AMI). According to the medical record, patients with inferior wall AMI who have no previous history of MI (or the first AMI attack) will be enrolled. These patients are divided into 3 groups from coronary angiography, depending upon the culprit lesion (1) before (proximal) or (2) after (distal) the right ventricular branch of RCA and (3) LCX. A two-step study strategy will be performed to analyze which electrocardiographic variables are capable of discriminating the culprit site of coronary artery. Using the area under the receiver operating characteristic (ROC) curve analysis, we plan to determine which one of the above variables is the most p
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