Cross-Sectional Validation of Diabetes Risk Scores for Predicting Diabetes, Metabolic Syndrome, and Chronic Kidney Disease in Taiwanese

OBJECTIVE - To validate the performance of current diabetes risk scores (DRSs) based on simple clinical information in detecting type 2 diabetes, metabolic syndrome (MetSyn), and chronic kidney disease (CKD). RESEARCH DESIGN AND METHODS - The performance of 10 DRSs was evaluated in a cross-sectional population screening of 2,759 Taiwanese subjects. RESULTS - All DRSs significantly correlated with measures of insulin resistance, estimated glomerular filtration rate, and urine albumin excretion. The prevalence of screening-detected diabetes (SDM), MetSyn, and CKD increased with higher DRSs. For prediction of SDM, the Cambridge DRS by Griffin et al. and the Finnish DRS outperformed other DRSs in terms of discriminative power and model fit. For prediction of MetSyn and CKD, the Atherosclerosis Risk in Community Study score by Schmidt et al. outperformed other DRSs. CONCLUSIONS - Risk scores based on simple clinical information are useful to identify individuals at high risk for diabetes, MetSyn, and CKD in different ethnic populations.