Yonel Z, Kocher T, Chapple I L C et al. Development and External Validation of a Multivariable Prediction Model to Identify Nondiabetic Hyperglycemia and Undiagnosed Type 2 Diabetes: Diabetes Risk Assessment in Dentistry Score (DDS). J Dent Res 2022; DOI: 10.1177/00220345221129807. Online ahead of print.

A validated prediction model involving dental variables can identify undiagnosed diabetes.

The aim of this study was to develop and externally validate a score for use in dental settings to identify those at risk of undiagnosed nondiabetic hyperglycemia (NDH) or type 2 diabetes (T2D). The Studies of Health in Pomerania (SHIP) project comprises two representative population-based cohort studies conducted in Northeast Germany. SHIP-TREND-0, 2008 to 2012 had 3,339 eligible participants, with 329 having undiagnosed NDH or T2D. External validation of the model and score employed an independent data set comprising 2,359 participants with 357 events. The final model included age, sex, body mass index, smoking status, first-degree relative with diabetes, presence of a dental prosthesis, presence of mobile teeth, history of periodontal treatment, and probing pocket depths ≥5 mm as well as prespecified interaction terms. In SHIP-TREND-0, the model area under the curve (AUC) was 0.72, calibration in the large was -0.025. The point score AUC was 0.69, with sensitivity of 77.0, specificity of 51.5, negative predictive value of 94.5, and positive predictive value of 17.0. External validation of the point score gave an AUC of 0.69, sensitivity of 79.2, specificity of 49.9, negative predictive value 91.5 and positive predictive value of 25.9.