title: Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan.
abstract: BACKGROUND
  This study aimed to construct a prediction model to identify subjects with high glycated hemoglobin (HbA1c) levels by incorporating anthropometric, lifestyle, clinical, and biochemical information in a large cross-sectional ethnic Chinese population in Taiwan from a health checkup center.
  
  
  METHODS
  The prediction model was derived from multivariate logistic regression, and we evaluated the performance of the model in identifying the cases with high HbA1c levels (> = 7.0%). In total 17,773 participants (age > = 30 years) were recruited and 323 participants (1.8%) had high HbA1c levels. The study population was divided randomly into two parts, with 80% as the derivation data and 20% as the validation data.
  
  
  RESULTS
  The point-based clinical model, including age (maximal 8 points), sex (1 point), family history (3 points), body mass index (2 points), waist circumference (4 points), and systolic blood pressure (3 points) reached an area under the receiver operating characteristic curve (AUC) of 0.723 (95% confidence interval, 0.677- 0.769) in the validation data. Adding biochemical measures such as triglycerides and HDL cholesterol improved the prediction power (AUC, 0.770 [0.723 - 0.817], P = < 0.001 compared with the clinical model). A cutoff point of 7 had a sensitivity of 0.76 to 0.96 and a specificity of 0.39 to 0.63 for the prediction model.
  
  
  CONCLUSIONS
  A prediction model was constructed for the prevalent risk of high HbA1c, which could be useful in identifying high risk subjects for diabetes among ethnic Chinese in Taiwan.
authors.affiliation: Institute of Preventive Medicine, School of Preventive Medicine, National Taiwan University, Taipei, Taiwan.
authors.forename: Kuo-Liong
authors.initials: KL
authors.lastname: Chien
authors.forename: Hung-Ju
authors.initials: HJ
authors.lastname: Lin
authors.forename: Bai-Chin
authors.initials: BC
authors.lastname: Lee
authors.forename: Hsiu-Ching
authors.initials: HC
authors.lastname: Hsu
authors.forename: Ming-Fong
authors.initials: MF
authors.lastname: Chen
mesh_terms: D000328:Adult; D000368:Aged; D044466:Asian People / Q000706:statistics & numerical data*; D003924:Diabetes Mellitus, Type 2 / Q000208:ethnology* / Q000378:metabolism*; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism*; D006801:Humans; D006943:Hyperglycemia / Q000208:ethnology* / Q000378:metabolism*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D015995:Prevalence; D012307:Risk Factors; D013624:Taiwan / Q000453:epidemiology
chemical_list: D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human