title: Identification of insulin resistance in subjects with normal glucose tolerance.
abstract: BACKGROUND
  Decreased insulin action (insulin resistance) is crucial in the pathogenesis of type 2 diabetes. Decreased insulin action can even be found in normoglycaemic patients, and they still bear increased risks for cardiovascular disease. In this study, we built models using data from metabolic syndrome (Mets) components and the oral glucose tolerance test (OGTT) to detect insulin resistance in subjects with normal glucose tolerance (NGT).
  
  
  METHODS
  In total, 292 participants with NGT were enrolled. Both an insulin suppression test (IST) and a 75-g OGTT were administered. The steady-state plasma glucose (SSPG) level derived from the IST was the measurement of insulin action. Participants in the highest tertile were defined as insulin-resistant. Five models were built: (i) Model 0: body mass index (BMI); (ii) Model 1: BMI, systolic and diastolic blood pressure, triglyceride; (iii) Model 2: Model 1 + fasting plasma insulin (FPI); (iv) Model 3: Model 2 + plasma glucose level at 120 minutes of the OGTT; and (v) Model 4: Model 3 + plasma insulin level at 120 min of the OGTT.
  
  
  RESULTS
  The area under the receiver operating characteristic curve (aROC curve) was observed to determine the predictive power of these models. BMI demonstrated the greatest aROC curve (71.6%) of Mets components. The aROC curves of Models 2, 3, and 4 were all substantially greater than that of BMI (77.1%, 80.1%, and 85.1%, respectively).
  
  
  CONCLUSIONS
  A prediction equation using Mets components and FPI can be used to predict insulin resistance in a Chinese population with NGT. Further research is required to test the utility of the equation in other populations and its prediction of cardiovascular disease or diabetes mellitus.
authors.affiliation: Division of Endocrinology, Department of Internal Medicine, Shuang Ho Hospital, School of Medicine, Taipei Medical University, Taipei, Taiwan.
authors.forename: Jiunn Diann
authors.initials: JD
authors.lastname: Lin
authors.forename: Jin Biou
authors.initials: JB
authors.lastname: Chang
authors.forename: Chung Ze
authors.initials: CZ
authors.lastname: Wu
authors.forename: Dee
authors.initials: D
authors.lastname: Pei
authors.forename: Chang Hsun
authors.initials: CH
authors.lastname: Hsieh
authors.forename: An Tsz
authors.initials: AT
authors.lastname: Hsieh
authors.forename: Yen Lin
authors.initials: YL
authors.lastname: Chen
authors.forename: Chun Hsien
authors.initials: CH
authors.lastname: Hsu
authors.forename: Chuan Chieh
authors.initials: CC
authors.lastname: Liu
mesh_terms: D000328:Adult; D001786:Blood Glucose; D003430:Cross-Sectional Studies; D005260:Female; D005947:Glucose / Q000378:metabolism*; D005951:Glucose Tolerance Test; D006801:Humans; D007333:Insulin Resistance; D008297:Male; D024821:Metabolic Syndrome / Q000378:metabolism; D008875:Middle Aged; D015233:Models, Statistical
chemical_list: D001786:Blood Glucose; D005947:Glucose