WEDNESDAY, Dec. 2 (HealthDay News) -- Researchers from Cornell University have developed a new risk-scoring model and simple self-assessment survey that can identify people who should be medically screened for diabetes, according to a study reported in the Dec. 1 Annals of Internal Medicine.

Heejung Bang, Ph.D., of the Weill Cornell Medical College in New York City, and colleagues used National Health and Nutrition Examination Survey (NHANES) data (1999 to 2004) to develop a model for ascertaining diabetes risk among undiagnosed subjects. The model was validated using 2005 to 2006 NHANES data, along with data from the Atherosclerosis Risk in Communities Study (ARIC) and the Cardiovascular Health Study (CHS). To arrive at the risk-scoring algorithm, undiagnosed diabetes was determined based on fasting plasma glucose levels, and associated with characteristics of the study subjects.

The researchers found that the characteristics associated with undiagnosed diabetes included family history of diabetes, history of hypertension, obesity, age, sex, and physical activity. In the NHANES (and ARIC/CHS) data sets, the simple six-question survey instrument had a sensitivity of 79 percent, (72 percent for ARIC/CHS), a specificity of 67 percent (62 percent), a positive predictive value of 10 percent (10 percent), and a positive likelihood ratio of 2.39 (1.89), which were better results than with other risk-scoring methods from the U.S. Centers for Disease Control and Prevention, the American Diabetes Association, the U.S. Preventive Services Task Force, and others.

"This easy-to-implement diabetes screening score seems to demonstrate improvements over existing methods. Studies are needed to evaluate it in diverse populations in real-world settings," the authors write.

One author reported a financial relationship with Merck.

Abstract
Full Text (subscription or payment may be required)