Tu1515 Endoscopic Ultrasound (EUS) for Measurement of Aortic Intima-Media Thickness: A Marker for Presence of Coronary Artery Disease

Abstract

Tu1515 Endoscopic Ultrasound (EUS) for Measurement of Aortic IntimaMedia Thickness: A Marker for Presence of Coronary Artery Disease Seyed Amir Mirbagheri*, Mohammad R. Ostovaneh, Elham Mortazavi Department of Internal Medicine, Gastroenterology, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran Background: Previous studies highlighted the superior independent and incremental value of measures of vascular function like aortic distensibility for predicting atherosclerosis and identification of high risk individuals. Despite the controversies, some consensus statements suggest the use of carotid intimamedia thickness for further clarification of coronary artery disease (CAD) risk assessment. There are studies that evaluated the relationship between Aortic intima-media thickness measured by transesophageal echocardiography and CAD. Endoscopic Ultra-Sound (EUS) technique can serve as a highly accurate technique for measuring the Aortic Intima-Media Thickness (AIMT). To our best knowledge, there is no study to measure the AIMT with EUS and evaluate its relationship with CAD .Aim: to evaluate the relationship between EUS-measured AIMT and presence of coronary artery disease in patients who underwent coronary angiography (CAG). Methods: Two hundred and fifty eight patients who previously underwent CAG and needed to perform EUS for a gastrointestinal reason involved in the study. After obtaining demographic data, AIMT was measured at the aortic arch level with a radial EUS (frequency 10 MHz) for all patients. The endosonologist was blind in regard of CAG result. The patients were then subgrouped into normal individuals without CAD and those with CAD, based on cardiologist-reported CAG and the AIMT was compared between two groups. Results: In patients with normal CAG, the AIMT was 1.49 0.53 mm (CI 0.84-1.14), while it was 1.89 0.53 (CI 1.23-2.55) in presence of CAD(p 0.001). The AIMT increased with age (correlation coefficient 0.557, P 0.001). When compared to normal 20 to 30 years old individuals without CAD risk factors, patients with CAD in CAG had significantly higher AIMT (1.89 0.53 compared to 1.47 .47, P 0.01). On the other hand, AIMT did not differ in normal 20 to 30 years old patients without CAD risk factors compared to the remaining individuals with normal CAG (1.47 0.53 vs 1.63 0.55, P 0.151). When adjusting for age and presence of diabetes mellitus and hyperlipidemia in a logistic regression model, the regression coefficient for AIMT for predicting the presence of CAD in CAG as outcome variable was 0.581 (P 0.001) and subsequently odds ratio was 1.79. Conclusion: AIMT is significantly different in presence or absence of CAD. Even though, it increases with age but adjustment for age revealed its pure effect to predict presence of CAD. AIMT could be used as an independent predictor for presence of CAD. EUS is one of the most accurate techniques to measure AIMT. Evaluation of AIMT in patients who are candidates for EUS for any reason may be useful for detecting the subclinical CAD and optimizing patient management.