Echocardiographic Parameters of Epicardial Fat Deposition and Its Relation to Severity of Coronary Artery Disease by SYNTAX Score in Zagazig University Hospitals

Background:The thickness of epicardial adipose tissue (EAT) has the potential to act as a novel indicator of cardiac and visceral adiposity and its function in myocardial infarction (MI) diagnosis and therapy.Objective: The main aim of the current study was to determine the EAT thickness by echocardiography in chest pain cases, which was suspected to had ischemic heart disease (IHD). We planned to determine EAT association with coronary artery disease (CAD) severity estimated by SYNTAX score and to examine the echocardiographic EAT usage for determining cardiovascular risk in IHD patients.Patients and Methods: A case control study was conducted on 148 cases with chest pain suspected to have IHD and referred to Cardiology Department Cath lab for doing coronary angiography (CA). All patients underwent physical examination, lead surface ECG, echocardiographic evaluation, EAT thicknessassessment, laboratory investigations and CA. Participants were divided into 2 groups; Group I included 74 ischemic patients who underwent elective CA for evaluation of CAD and Group II included 74 subjects with chest pain referred for CA which reveals normal epicardial coronaries. Results: There was a positive correlation among SYNTAXscore and age of patients in group I, body mass index (BMI) and waist circumference (WC). There was a positive correlation between SYNTAX score and triglycerides, total cholesterol and LDL in group I while HDL shows significant negative correlation with SYNTAXscore. There was a positive correlation between SYNTAX score and EAT, IAS and RVFW. EAT was a significant predictor for CAD severity regarding SYNTAXscore. Conclusions: The EAT thickness is useful for early detection of individuals with complicated CAD. EAT thickness was significantly correlated with CAD severity. Echocardiography assessment of EAT can be simply predict CAD severity and help in patient’s risk stratification.