ME4_OA_Ashok 4

Background: Traditional risk factors for coronary artery diseases are not very specific in identifying coronary artery disease (CAD). LDL cholesterol is a proven risk factor for developing coronary artery disease (CAD). However Indian populations with established CAD often have lipid levels within normal range. Oxidized LDL is seen as a sensitive marker for CAD, so it might be a better predictor of coronary atherosclerosis than standard lipid profile and traditional risk factors. Objectives: The proposed study was therefore designed to analyze the levels of oxidized LDL level in Indian patients undergoing coronary angiography and to study its value in predicting the occurrence and extent of CAD in this patient population. Methods: This cross-sectional study included patients undergoing diagnostic coronary angiography and on the basis of presence or absence of CAD, was grouped as normal or CAD group. Conventional risk factors (i.e. age, sex, diabetes mellitus, hypertension, smoking, total cholesterol and HDL cholesterol) were analyzed in all subjects as per institutional protocol. Levels of ox-LDL were measured in a monoclonal antibody 4E6 based competition ELISA. Results: A total of 211 patients were included in the study of which 151 had disease on angiography (angiographically proven coronary artery disease) and 60 subjects had normal coronary angiogram (free of coronary artery disease). There was no significant difference in traditional lipid parameters and traditional risk factors between patients with and without CAD, and a significant difference was noted with respect to oxidized LDL in subjects with CAD (104.6±7.9 U/l) compared to subjects without CAD (79.4±3.9U/l, p<0.001). On ROC analysis at cutoff value 84 U/l, sensitivity and specificity of oxidized LDL was 97.4% and 90% respectively for detection of CAD. Conclusion: we conclude, that plasma oxidized-LDL is a very sensitive marker of CAD in Indian population even in near normal lipid profile or patients treated with statin and addition of oxidizedLDL to the established risk factors may improve CAD risk prediction.