ABSTRACT
Surprisingly, it is estimated that about half of type 2 diabetics remain undetected. The possible causes may be partly attributable to people with normal fasting plasma glucose [FPG] but abnormal postprandial hyperglycemia. We attempted to develop an effective predictive model by using the metabolic syndrome [MeS] components as parameters to identify such persons. All participants received a standard 75-g oral glucose tolerance test, which showed that 106 had normal glucose tolerance, 61 had impaired glucose tolerance, and 6 had diabetes-an-isolated postchallenge hyperglycemia. We tested five models, which included various MeS components. Model 0: FPC; Model 1 [clinical history model]: family history [FH], FPC, age and sex; Model 2 [MeS model]: Model 1 plus triglycerides, high-density lipoprotein cholesterol, body mass index, systolic blood pressure and diastolic blood pressure; Model 3: Model 2 plus fasting plasma insulin [FPI]; Model 4: Model 3 plus homeostasis model assessment of insulin resistance. A receiver-operating characteristic [ROC] curve was used to determine the predictive discrimination of these models. The area under the ROC curve of the Model 0 was significantly larger than the area under the diagonal reference line. All the other 4 models had a larger area under the ROC curve than Model O. Considering the simplicity and lower cost of Model 2, it would be the best model to use. Nevertheless, Model 3 had the largest area under the ROC curve. We demonstrated that Model 2 and 3 have a significantly better predictive discrimination to identify persons with normal FPC at high risk for glucose intolerance