title: Development and validation of a patient self-assessment score for diabetes risk.
abstract: BACKGROUND
  National guidelines disagree on who should be screened for undiagnosed diabetes. No existing diabetes risk score is highly generalizable or widely followed.
  
  
  OBJECTIVE
  To develop a new diabetes screening score and compare it with other available screening instruments (Centers for Disease Control and Prevention, American Diabetes Association, and U.S. Preventive Services Task Force guidelines; 2 American Diabetes Association risk questionnaires; and the Rotterdam model).
  
  
  METHODS
  Cross-sectional data.
  
  
  METHODS
  NHANES (National Health and Nutrition Examination Survey) 1999 to 2004 for model development and 2005 to 2006, plus a combined cohort of 2 community studies, ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study), for validation.
  
  
  METHODS
  U.S. adults aged 20 years or older.
  
  
  METHODS
  A risk-scoring algorithm for undiagnosed diabetes, defined as fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater without known diabetes, was developed in the development data set. Logistic regression was used to determine which participant characteristics were independently associated with undiagnosed diabetes. The new algorithm and other methods were evaluated by standard diagnostic and feasibility measures.
  
  
  RESULTS
  Age, sex, family history of diabetes, history of hypertension, obesity, and physical activity were associated with undiagnosed diabetes. In NHANES (ARIC/CHS), the cut-point of 5 or more points selected 35% (40%) of persons for diabetes screening and yielded a sensitivity of 79% (72%), specificity of 67% (62%), positive predictive value of 10% (10%), and positive likelihood ratio of 2.39 (1.89). In contrast, the comparison scores yielded a sensitivity of 44% to 100%, specificity of 10% to 73%, positive predictive value of 5% to 8%, and positive likelihood ratio of 1.11 to 1.98.
  
  
  CONCLUSIONS
  Data during pregnancy were not available.
  
  
  CONCLUSIONS
  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.
  
  
  BACKGROUND
  Clinical and Translational Science Center at Weill Cornell Medical College.
authors: Weill Medical College of Cornell University, Columbia University College of Physicians and Surgeons, and FOJP Service Corporation, New York, NY 10065, USA. heb2013@med.cornell.edu
authors: Heejung
authors: H
authors: Bang
authors: Alison M
authors: AM
authors: Edwards
authors: Andrew S
authors: AS
authors: Bomback
authors: Christie M
authors: CM
authors: Ballantyne
authors: David
authors: D
authors: Brillon
authors: Mark A
authors: MA
authors: Callahan
authors: Steven M
authors: SM
authors: Teutsch
authors: Alvin I
authors: AI
authors: Mushlin
authors: Lisa M
authors: LM
authors: Kern
mesh_terms: D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000378:metabolism; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis*; D006801:Humans; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D009749:Nutrition Surveys; D012307:Risk Factors; D011795:Surveys and Questionnaires; D055815:Young Adult
chemical_list: D001786:Blood Glucose