Journal
DIABETES CARE
Volume 36, Issue 12, Pages 3944-3952Publisher
AMER DIABETES ASSOC
DOI: 10.2337/dc13-0593
Keywords
-
Categories
Funding
- Chinese Medical Association Foundation
- Chinese Diabetes Society
- National Key Technologies R&D Program of China [2009BAI80B02]
- National High-Tech R&D Program of China (863 Program) [2012AA02A509]
Ask authors/readers for more resources
OBJECTIVETo develop a New Chinese Diabetes Risk Score for screening undiagnosed type 2 diabetes in China.RESEARCH DESIGN AND METHODSData from the China National Diabetes and Metabolic Disorders Study conducted from June 2007 to May 2008 comprising 16,525 men and 25,284 women aged 20-74 years were analyzed. Undiagnosed type 2 diabetes was detected based on fasting plasma glucose 7.0 mmol/L or 2-h plasma glucose 11.1 mmol/L in people without a prior history of diabetes. -Coefficients derived from a multiple logistic regression model predicting the presence of undiagnosed type 2 diabetes were used to calculate the New Chinese Diabetes Risk Score. The performance of the New Chinese Diabetes Risk Score was externally validated in two studies in Qingdao: one is prospective with follow-up from 2006 to 2009 (validation 1) and another cross-sectional conducted in 2009 (validation 2).RESULTSThe New Chinese Diabetes Risk Score includes age, sex, waist circumference, BMI, systolic blood pressure, and family history of diabetes. The score ranges from 0 to 51. The area under the receiver operating curve of the score for undiagnosed type 2 diabetes was 0.748 (0.739-0.756) in the exploratory population, 0.725 (0.683-0.767) in validation 1, and 0.702 (0.680-0.724) in validation 2. At the optimal cutoff value of 25, the sensitivity and specificity of the score for predicting undiagnosed type 2 diabetes were 92.3 and 35.5%, respectively, in validation 1 and 86.8 and 38.8% in validation 2.CONCLUSIONSThe New Chinese Diabetes Risk Score based on nonlaboratory data appears to be a reliable screening tool to detect undiagnosed type 2 diabetes in Chinese population.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available