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

Dee Pei, Jiunn Dann Lin, Du An Wu, Chang Hsun Hsieh, Yi Jen Hung, Shi Wen Kuo, Ko Lin Kuo, Chung Ze Wu, Jer Chuan Li

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)339-346
Number of pages8
JournalAnnals of Saudi Medicine
Volume27
Issue number5
Publication statusPublished - Sep 2007
Externally publishedYes

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Glucose Intolerance
Fasting
ROC Curve
Glucose
Blood Pressure
Hyperglycemia
Glucose Tolerance Test
HDL Cholesterol
Insulin Resistance
Triglycerides
Body Mass Index
Homeostasis
Insulin
Costs and Cost Analysis

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Pei, D., Lin, J. D., Wu, D. A., Hsieh, C. H., Hung, Y. J., Kuo, S. W., ... Li, J. C. (2007). Predicting glucose intolerance with normal fasting plasma glucose by the components of the metabolism syndrome. Annals of Saudi Medicine, 27(5), 339-346.

Predicting glucose intolerance with normal fasting plasma glucose by the components of the metabolism syndrome. / Pei, Dee; Lin, Jiunn Dann; Wu, Du An; Hsieh, Chang Hsun; Hung, Yi Jen; Kuo, Shi Wen; Kuo, Ko Lin; Wu, Chung Ze; Li, Jer Chuan.

In: Annals of Saudi Medicine, Vol. 27, No. 5, 09.2007, p. 339-346.

Research output: Contribution to journalArticle

Pei, D, Lin, JD, Wu, DA, Hsieh, CH, Hung, YJ, Kuo, SW, Kuo, KL, Wu, CZ & Li, JC 2007, 'Predicting glucose intolerance with normal fasting plasma glucose by the components of the metabolism syndrome', Annals of Saudi Medicine, vol. 27, no. 5, pp. 339-346.
Pei, Dee ; Lin, Jiunn Dann ; Wu, Du An ; Hsieh, Chang Hsun ; Hung, Yi Jen ; Kuo, Shi Wen ; Kuo, Ko Lin ; Wu, Chung Ze ; Li, Jer Chuan. / Predicting glucose intolerance with normal fasting plasma glucose by the components of the metabolism syndrome. In: Annals of Saudi Medicine. 2007 ; Vol. 27, No. 5. pp. 339-346.
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