title: Performance of Fasting Plasma Glucose and Postprandial Urine Glucose in Screening for Diabetes in Chinese High-risk Population.
abstract: BACKGROUND
  The conventional approaches to diabetes screening are potentially limited by poor compliance and laboratory demand. This study aimed to evaluate the performance of fasting plasma glucose (FPG) and postprandial urine glucose (PUG) in screening for diabetes in Chinese high-risk population.
  
  
  METHODS
  Nine hundred and nine subjects with high-risk factors of diabetes underwent oral glucose tolerance test after an overnight fast. FPG, hemoglobin A1c, 2-h plasma glucose (2 h-PG), and 2 h-PUG were evaluated. Diabetes and prediabetes were defined by the American Diabetes Association criteria. The area under the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic accuracy of 2 h-PUG, and the optimal cut-off determined to provide the largest Youden index. Spearman correlation was used for relationship analysis.
  
  
  RESULTS
  Among 909 subjects, 33.4% (304/909) of subjects had prediabetes, and 17.2% (156/909) had diabetes. The 2 h-PUG was positively related to FPG and 2 h-PG (r = 0.428 and 0.551, respectively, both P < 0.001). For estimation of 2 h-PG ≥ 7.8 mmol/L and 2 h-PG ≥ 11.1 mmol/L using 2 h-PUG, the area under the ROC curve were 0.772 (95% confidence interval [CI ]: 0.738-0.806) and 0.885 (95% CI: 0.850-0.921), respectively. The corresponding optimal cut-offs for 2 h-PUG were 5.6 mmol/L and 7.5 mmol/L, respectively. Compared with FPG alone, FPG combined with 2 h-PUG had a higher sensitivity for detecting glucose abnormalities (84.1% vs. 73.7%, P < 0.001) and diabetes (82.7% vs. 48.1%, P < 0.001).
  
  
  CONCLUSIONS
  FPG combined with 2 h-PUG substantially improves the sensitivity in detecting prediabetes and diabetes relative to FPG alone, and may represent an efficient layperson-oriented diabetes screening method.
authors.forename: Bing-Quan
authors.initials: BQ
authors.lastname: Yang
authors.forename: Yang
authors.initials: Y
authors.lastname: Lu
authors.forename: Jia-Jia
authors.initials: JJ
authors.lastname: He
authors.forename: Tong-Zhi
authors.initials: TZ
authors.lastname: Wu
authors.forename: Zuo-Ling
authors.initials: ZL
authors.lastname: Xie
authors.forename: Cheng-Hao
authors.initials: CH
authors.lastname: Lei
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhou
authors.forename: Jing
authors.initials: J
authors.lastname: Han
authors.forename: Mei-Qi
authors.initials: MQ
authors.lastname: Bian
authors.forename: Hong
authors.initials: H
authors.lastname: You
authors.forename: De-Xian
authors.initials: DX
authors.lastname: Mei
authors.affiliation: Department of Endocrinology, Zhongda Hospital, Institute of Diabetes, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China, .
authors.forename: Zi-Lin
authors.initials: ZL
authors.lastname: Sun
mesh_terms: D000368:Aged; D044466:Asian People; D001786:Blood Glucose / Q000378:metabolism*; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis* / Q000652:urine; D005215:Fasting / Q000097:blood*; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D019518:Postprandial Period / Q000502:physiology
chemical_list: D001786:Blood Glucose