Predicting glucose intolerance with normal fasting plasma glucose by the components of the metabolic syndrome.

Abstract:

BACKGROUND: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. SUBJECTS AND METHODS: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-on-isolated postchallenge hyperglycemia. We tested five models, which included various MeS components. Model 0: FPG; Model 1 (clinical history model): family history (FH), FPG, 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. RESULTS: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 0. 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. CONCLUSION:We demonstrated that Model 2 and 3 have a significantly better predictive discrimination to identify persons with normal FPG at high risk for glucose intolerance.

journal_name

Ann Saudi Med

journal_title

Annals of Saudi medicine

authors

Pei D,Lin JD,Wu DA,Hsieh CH,Hung YJ,Kuo SW,Kuo KL,Wu CZ,Li JC

doi

10.5144/0256-4947.2007.339

subject

Has Abstract

pub_date

2007-09-01 00:00:00

pages

339-46

issue

5

eissn

0256-4947

issn

0975-4466

pii

07-069

journal_volume

27

pub_type

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