Ischemic Heart Disease (IHD) is one of the most common causes of death and disability in most countries and atherosclerosis is one of the main etiologies of IHD (
1). Despite extensive diagnostic and therapeutic advances, still one-third of patients with Myocardial infarction (MI) die. Thus, prevention of the risk factors and prompt treatment in high-risk individuals is of high priority in health care systems (
2). Various factors such as age, sex, smoking, hyperlipidemia and hypertension are considered as risk factors for cardiovascular diseases (
1,
3-
6).
One of the best methods to detect cardiac ischemia is evaluating the patients with electrocardiography (ECG). Twelve-lead ECG is widely used for detecting the extent of the conflict and also tracking patients after cardiac infarction. Some protests, such as a Q wave in the electrocardiogram or a bundle branch block are shown to be associated with more severe myocardial damage (
7,
8). Failure to achieve probability of normal ventricular function is very high when the electrocardiogram is normal; however, when there are abnormalities in the electrocardiogram, accurate assessment of ventricular function is more difficult than the normal state. Hence, different classification systems have been presented to electrocardiograms that have the ability to assess myocardial damage, the extent of infarction and ventricular function (
9-
12). The simplified Sylvester QRS Score (SSS) measures the size of the infarction in a scoring system from 31 points corresponding to 3% of the left ventricular mass. The higher the SSS goes, prognosis of the patients decline (
13-
15). Research has shown that the existing classification and scoring such as SSS for myocardial damage by ECG has the ability to predict prognosis as well as short and long-term outcomes of patients after MI (
14-
17).