Clinical implications of the metabolic syndrome and hyperuricemia

A cluster of risk factors for cardiovascular disease (CVD) and type 2 diabetes mellitus, which occur together more often than by chance alone, have become known as the metabolic syndrome. These factors include high blood pressure, raised blood glucose, elevated triglyceride levels, decreased highdensity lipoprotein cholesterol and obesity. The metabolic syndrome has been proposed as a means to identify people with increased risk of CVD and diabetes and to guide clinical management decisions. It has been shown to predict CVD morbidity, CVD mortality, type 2 diabetes and all-cause mortality in a number of populations. However, it does not enhance risk prediction, being outperformed by traditional cardiovascular risk prediction algorithms. The association of the metabolic syndrome with the risk of CVD was much less than that of low-density lipoprotein cholesterol, and most published reports indicate that the metabolic syndrome does not predict cardiovascular events or disease progression any better than its components. The metabolic syndrome is also not an absolute risk indicator, because it does not contain many of the factors that determine absolute risk; for example, age, cigarette smoking and low-density lipoprotein cholesterol levels. As described in the National Cholesterol Education Program Adult Treatment Panel in 2001, metabolic syndrome played a role only in the guidance of the therapeutic goal of cholesterol. In this issue of JCMA, Lin et al. report their study designed to evaluate the use of several simple indicators in identifying postmenopausal women with insulin resistance estimated by HOMA-IR. The investigators sought to provide clues for clinicians to identify postmenopausal women who are susceptible to diabetes and CVD. They recruited 262 naturally postmenopausal women without frank diabetes, and HOMA-IR values were calculated to estimate insulin resistance, which was defined as the upper quartile of the HOMA-IR values, and the diagnostic power was examined by constructing receiver operating characteristic curves. They found that 45% of patients with insulin resistance had silent diabetes, and the odds ratio was 6.09 compared to those without insulin resistance. As expected, uric acid, body mass index, waist circumference, alanine aminotransferase, triglycerides and high-density lipoprotein cholesterol were important determinants of HOMA-IR in these women. Lin et al. also found that using uric acid levels with 5.0 mg/dl as a cut-off point, they could diagnose insulin resistance with 75.4% sensitivity and 73.1% specificity. This issue picks up right individuals who are major target