BACKGROUND: Metabolic syndrome (MS) was reported to be associated with coronary artery disease (CAD). The aim of the present study was to assess the association between MS and CAD angiographic severity and to search the predictive value of MS and its individual components for CAD. METHODS: 428 patients who underwent elective coronary angiography at the Cardiology Department were included in the study. MS was defined according to National Cholesterol Education Program (NCEP) Adult Treatment Panel III criteria. CAD severity was determined by Gensini scors. RESULTS: The proportion of CAD (+) who had MS was significantly higher compared to CAD (-) (63.6% vs. 48.6%, p = 0.020). Gensini score and number of MS components were positively correlated (r = 0.144, p = 0.019). The adjusted predictive abilities for angiographic CAD of MS and its individual components showed that high FBG and high TG are predictive factors for CAD in binary logistic regression analysis (OR = 2.238, 95% CI 1.111 - 4.508, p = 0.024 vs. OR = 2.200, 95% CI 1.078 - 4.492, p = 0.030). The OR for CAD risk of different phenotypes in high FBG and/or HTG shows that this combination increased the OR significantly to 2.307. Among the quartets, the cluster with high BP and low HDL-C was the highest risk (OR = 4.879). However, the combination including all components of MS was a significant contributor to CAD risk. CONCLUSIONS: The MS score correlates with the angiographic severity of CAD. The predictive ability for CAD was stronger with high FBG and high TG and associated low HDL-C and high BP, which seem to act synergistically as risk factors for CAD. Therefore, to prevent or decrease this risk of CAD, clinicians should screen for individual abnormalities of MS, mainly elevated blood glucose level and TG.
BACKGROUND:Metabolic syndrome (MS) was reported to be associated with coronary artery disease (CAD). The aim of the present study was to assess the association between MS and CAD angiographic severity and to search the predictive value of MS and its individual components for CAD. METHODS: 428 patients who underwent elective coronary angiography at the Cardiology Department were included in the study. MS was defined according to National Cholesterol Education Program (NCEP) Adult Treatment Panel III criteria. CAD severity was determined by Gensini scors. RESULTS: The proportion of CAD (+) who had MS was significantly higher compared to CAD (-) (63.6% vs. 48.6%, p = 0.020). Gensini score and number of MS components were positively correlated (r = 0.144, p = 0.019). The adjusted predictive abilities for angiographic CAD of MS and its individual components showed that high FBG and high TG are predictive factors for CAD in binary logistic regression analysis (OR = 2.238, 95% CI 1.111 - 4.508, p = 0.024 vs. OR = 2.200, 95% CI 1.078 - 4.492, p = 0.030). The OR for CAD risk of different phenotypes in high FBG and/or HTG shows that this combination increased the OR significantly to 2.307. Among the quartets, the cluster with high BP and low HDL-C was the highest risk (OR = 4.879). However, the combination including all components of MS was a significant contributor to CAD risk. CONCLUSIONS: The MS score correlates with the angiographic severity of CAD. The predictive ability for CAD was stronger with high FBG and high TG and associated low HDL-C and high BP, which seem to act synergistically as risk factors for CAD. Therefore, to prevent or decrease this risk of CAD, clinicians should screen for individual abnormalities of MS, mainly elevated blood glucose level and TG.