BACKGROUND/AIMS: The aim was to determine which of three sets of metabolic syndrome (MetS) criteria (International Diabetes Federation [IDF], National Cholesterol Education Program Adult Treatment Panel III [ATP III], and European Group for the Study of Insulin Resistance [EGIR]) best predicts the coronary artery calcification (CAC) score in a cross-sectional study. This has not been evaluated in previous studies. METHODS: A total of 24,060 subjects were screened for CAC by multi-detector computed tomography. The presence of CAC was defined as a CAC score > 0. The odds ratio for the presence of CAC was analyzed for three different sets of MetS criteria and according to number of MetS components. RESULTS: CAC was observed in 12.6% (3,037) of the subjects. Patients with MetS, as defined by the IDF, ATP III, and EGIR criteria, had a CAC rate of 23.0%, 25.1%, and 29.5%, respectively (p < 0.001). Comparisons of C statistics for multivariate regression models revealed no significant difference among the three sets of criteria. After adjustment for risk factors, the ATP III criteria produced a slightly higher odds ratio for CAC compared with the other criteria, but this difference was not significant. The risk factor-adjusted odds ratio for the presence of CAC increased from 1 to 1.679 as the number of MetS components defined by ATP III increased from 0 to > or = 3 (p for trend < 0.001). CONCLUSIONS: The presence of MetS was associated with the presence of CAC. There was no significant difference among the three sets of MetS criteria in terms of the ability to predict CAC. An increase in the number of MetS components was associated with an increased odds of CAC.
Adult ; Asymptomatic Diseases ; Biological Markers/blood ; Calcium/*analysis ; Coronary Angiography/methods ; Coronary Artery Disease/blood/*epidemiology/radiography ; Coronary Vessels/*chemistry/radiography ; Cross-Sectional Studies ; Female ; Humans ; Male ; Metabolic Syndrome X/blood/diagnosis/*epidemiology ; Middle Aged ; Multidetector Computed Tomography ; Multivariate Analysis ; Odds Ratio ; Predictive Value of Tests ; Prevalence ; Republic of Korea/epidemiology ; Risk Assessment ; Risk Factors ; Vascular Calcification/blood/*epidemiology/metabolism/radiography

BACKGROUND/AIMS: Although increased serum uric acid (SUA) concentrations are commonly encountered in patients with risk factors for coronary artery disease (CAD), the clinical value of SUA has not been established. METHODS: The study group comprised 687 consecutive patients with suspected CAD who had undergone coronary angiography. CAD was defined as stenosis > or = 50% of the luminal diameter. CAD severity was expressed as 1-, 2-, or 3-vessel disease. Metabolic syndrome (MS) was defined according to National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) criteria, and aortofemoral pulse wave velocity (PWV) was obtained by arterial catheterization invasively. RESULTS: In total, 395 patients had CAD. SUA was higher in patients with CAD as compared to those without CAD (5.5 +/- 1.0 vs. 5.2 +/- 1.0 mg/dL, p = 0.004). In addition, SUA was significantly associated with the severity of CAD (p = 0.002). However, after adjusting for significant confounding factors including age, diabetes, smoking, cholesterol, MS, and PWV, SUA was not an independent risk factor for CAD (p = 0.151). Based on a subgroup analysis, SUA was more closely associated with CAD in women than in men, and in the highest quartile (> or = 6.4 mg/dL) than in the first quartile (< 4.8 mg/dL); however, these results were not significant (p = 0.062, p = 0.075, respectively). In a multivariate regression analysis, the most important determinant of SUA was MS (i.e., insulin resistance syndrome), which is strongly associated with CAD. CONCLUSIONS: In patients with suspected CAD, SUA was not an independent risk factor for CAD and may be merely a marker of insulin resistance.
Aged ; Biological Markers/blood ; Coronary Angiography ; Coronary Artery Disease/*blood/*epidemiology/radiography ; Female ; Humans ; Insulin Resistance ; Logistic Models ; Male ; Middle Aged ; Multivariate Analysis ; Risk Factors ; *Severity of Illness Index ; Uric Acid/*blood