Electrocardiography Diagnostic performance in the assessment of significant coronary artery disease and its anatomical site in comparison with coronary angiography among Nigerians: A pilot study

Abstract

Introduction: Coronary angiography (CAG) is a useful diagnostic tool in patients with suspected CAD especially in patients that are at high risk. CAG is the gold standard for diagnosis of significant coronary stenosis. However, it can be associated with certain risks. The use of noninvasive assessment tools for predicting CAD is considered because it offers safety, patient convenience, and faster performance. The aim of the study was to assess the predictive value of 12-lead electrocardiogram (ECG) in patients with suspected coronary artery disease (CAD). Methods: 59 consecutive patients aged 40 to 98 years with new onset of chest pain that were referred to the cardiac catheterization laboratory of Bayelsa Specialist Hospital, Yenagoa October 2017 and November, 2018. At admission, a resting standard 12-lead ECG was recorded and the ECG changes were interpreted by the cardiologist. The ECG was recorded as normal or abnormal depending on regional changes in ST segment (ischemic-appearing ST depression or elevation), T-wave inversion (≥ 1 mm) and Q-wave appearance (≥ 0.04 s or ≥ 25% of R-wave amplitude). The III, aVF and II leads were used to detect RCA involvement; V2 or V3 and aVL to detect LCx involvement, and V2 or V3, V1, and V4 were used to detect LAD involvement. ECGs were taken at a paper speed of 25 mm/s and calibration of 10 mm. Results: ECG correctly detected significant stenosis in 21 out of 59 patients with an overall sensitivity per patient of 59.5% and specificity per patient of 59.1%. ECG had the highest sensitivity with LAD involvement LAD (37.3%) and RCA (25.8%), respectively. ECG had a probability of indicating coronary vessel disease in persons with the disease (positive predictive value) 71%, whereas, negative ECG findings were less likely to indicate the absence of disease (a negative predictive value = 46.4%. Similarly, ECG correctly classifying patients as having LAD, RCA, and LCx diseases (66.7%, 70%, and 66.7% respectively) as compared to its ability to correctly classify persons without the respective vessel disease (33.3%, 55.6%, and 55.6%). Among the patients, 59.3% were correctly identified Conclusions: ECG has low sensitivity and specificity for predicting coronary artery stenosis with accuracy ranged 59.5% and 59.1% based on coronary artery analysis.