title: A Chinese diabetes risk score for screening of undiagnosed diabetes and abnormal glucose tolerance.
abstract: BACKGROUND
  This study is aimed at developing and evaluating a diabetes risk score (DRS) to predict incident diabetes and screen for undiagnosed diabetes and abnormal glucose tolerance in the Chinese population.
  
  
  METHODS
  Three DRS instruments were respectively developed and validated based on the data collected from a 10-year longitudinal health checkup-based population of 1,851 individuals without diabetes at baseline. The efficiency on glucose abnormality screening was evaluated based on the testing of a cross-sectional sample of 699 individuals without known diabetes.
  
  
  RESULTS
  The DRS consisting of age, hypertension, history of high blood glucose, body mass index, fasting plasma glucose, serum triglycerides, and serum high-density lipoprotein-cholesterol had the best prediction properties (area under curve [AUC] = 0.734 [95% confidence interval 0.702-0.766] and 0.759 [0.686-0.831] in exploratory and validation cohorts, respectively). The DRS had a sensitivity of 64.5% and 72.9%, respectively, and a specificity of 71.6% and 63.9%, respectively, with an optimal cutoff of 4. AUCs were 0.828 (0.797-0.860) and 0.909 (0.884-0.933) for detecting abnormal glucose tolerance and diabetes, respectively, through cross-sectional screening. Performance of the oral glucose tolerance test (OGTT) in selected subjects with DRS ≥ 4 led to the identification of 76.2% cases of abnormal glucose tolerance and 100% cases of diabetes, while avoiding an OGTT in 52.8% of the study group.
  
  
  CONCLUSIONS
  The DRS instrument including age, hypertension, history of high blood glucose, body mass index, fasting plasma glucose, triglycerides, and high-density lipoprotein-cholesterol is practical and effective in predicting incident diabetes and screening glucose abnormality in the Chinese population.
authors.affiliation: Department of Endocrinology, Chinese PLA General Hospital, Beijing, China.
authors.forename: Min
authors.initials: M
authors.lastname: Liu
authors.forename: Changyu
authors.initials: C
authors.lastname: Pan
authors.forename: Mengmeng
authors.initials: M
authors.lastname: Jin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002681:China / Q000453:epidemiology; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology; D005260:Female; D018149:Glucose Intolerance / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology; D005951:Glucose Tolerance Test; D006306:Health Surveys; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D012307:Risk Factors; D012680:Sensitivity and Specificity