title: Tooth loss, pocket depth, and HbA1c information collected in a dental care setting may improve the identification of undiagnosed diabetes.
abstract: METHODS
  A total of 506 adults participated in this study. The study population was recruited from a pool of new patients presenting to the Columbia University College of Dental Medicine over a 12-month period (April 2009 to March 2010). New patients were screened to determine potential eligibility for participation based on 2 criteria: age and knowledge of their diabetes status. Non-Hispanic white adults were required to be 40 years old or older and Hispanic or non-white adults were required to be 30 years or older. Additionally, all potential participants had to respond that a health care provider had never told them that they had diabetes or prediabetes. This screening yielded 601 individuals. From this group, 535 were selected based on having 1 of 4 self-reported risk factors (hypertension, high cholesterol, overweight, or a family history of diabetes). These 535 adults continued with a periodontal examination and an HbA1c test. Five hundred six participants returned for a follow-up visit to collect blood for a fasting plasma glucose (FPG) test.
  
  
  METHODS
  HbA1c test, and dentate and periodontal status.
  
  
  METHODS
  FPG level.
  
  
  RESULTS
  Among the 535 individuals participating in the study, 161 were determined potentially to be prediabetic (FPG was 100-125 mg/dL) and 21 potentially to be diabetic (FPG ≥ 126 mg/dL). Receiver operating characteristics (ROCs) via logistic regression was used to assess model performance and calculate key findings. The area under the curve of a multivariate regression model that included oral health status indicators and all 4 self-reported risk factors had a predicted value of 0.68 (confidence interval [CI]: 0.63, 0.73) for abnormal FPG (≥100 mg/dL). A model with just the percentage of periodontal pockets ≥5 mm and the number of missing teeth had a predicted value of 0.65 (CI: 0.60, 0.70). When the test results from HbA1C were added to the simpler model, the predictive value improved to 0.79 (CI: 0.75, 0.83). The authors also determined that the presence of 4 or more missing teeth or having pocket depth of 5 mm or more involving more than 25% of the sites identified 73% of the true cases (ie, abnormal FPG).
  
  
  CONCLUSIONS
  Dental care professionals have the potential to identify patients at risk for diabetes and refer them to a physician for follow-up evaluation.
authors.affiliation: Centers for Disease Control and Prevention, National Center for Health Statistics, 3311 Toledo Road, Room 4416, Hyattsville, MD 20782, USA. bfd1@cdc.gov
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Dye
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Genco