Development and validation of a screening model for diabetes mellitus in patients with periodontitis in dental settings

OBJECTIVES: To identify predictors in patient profiles and to develop, internally validate, and calibrate a screening model for diabetes mellitus (DM) in patients with periodontitis in dental settings MATERIALS AND METHODS: The study included 204 adult patients with periodontitis. Patients’ socio-demographic characteristics, general health status, and periodontal status were recorded as potential predictors. The diabetic status was considered the outcome, classified into no DM, prediabetes (pre-DM), or DM. Multinomial logistic regression analysis was used to develop the model. The performance and clinical values of the model were determined. RESULTS: Seventeen percent and 47% of patients were diagnosed with DM and pre-DM, respectively. Patients’ age, BMI, European background, cholesterol levels, previous periodontal treatment, percentage of the number of teeth with mobility, and with gingival recession were significantly associated with the diabetic status of the patients. The model showed a reasonable calibration and moderate to good discrimination with area under the curve (AUC) values of 0.67 to 0.80. The added predictive values for ruling in the risk of DM and pre-DM were 0.42 and 0.11, respectively, and those for ruling it out were 0.05 and 0.17, respectively. CONCLUSIONS: Predictors in patient profiles for screening of DM and pre-DM in patients with periodontitis were identified. The calibration, discrimination, and clinical values of the model were acceptable. CLINICAL RELEVANCE: The model may well assist clinicians in screening of diabetic status of patients with periodontitis. The model can be used as a reliable screening tool for DM and pre-DM in patients with periodontitis in dental settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00784-020-03281-w) contains supplementary material, which is available to authorized users.