Development and validation of a risk prediction model for oral frailty among Chinese older adults with type 2 diabetes mellitus

To investigate the prevalence and associated factors of oral frailty in older adults with type 2 diabetes, establish a nomogram prediction model, develop an assessment tool for early screening and prevention of oral frailty in this population, and provide scientific basis for the formulation of personalized oral health management strategies. A convenience sampling method was used to select 533 older adults with type 2 diabetes mellitus who visited two tertiary-level general hospitals in Sichuan Province and one tertiary-level general hospital in Hebei Province from April 2024 to June 2025 as the study subjects. They were randomly divided into a training set and a validation set in a 7:3 ratio. A risk prediction model was constructed through analysis, and a nomogram was drawn. The Hosmer-Lemeshow (H-L) test and receiver operating characteristic (ROC) curve were used to evaluate the model’s goodness of fit and predictive performance, respectively. The constructed model was validated through 1,000 bootstrap sampling iterations to assess its predictive efficacy. A total of 533 older adults with type 2 diabetes were included in the final analysis. Among them, 246 patients (46.15%) exhibited symptoms of oral frailty. Multivariate logistic regression analysis revealed that age, type of chronic disease, duration of diabetes, HbA1c level, periodontitis, number of natural teeth, difficulty chewing hard foods, and swallowing disorders were associated with the risk of oral frailty in older adults with type 2 diabetes (all P < 0.05); The area under the ROC curve (AUC) of the predictive model was 0.847( 95%CI: 0.808–0.886), a sensitivity of 72.3%, a specificity of 83.5%, and a maximum Youden index of 0.558. Internal validation showed that the area under the ROC curve for the validation set was 0.831(95%CI:0.768–0.894), with a sensitivity of 82.2% and specificity of 72.4%. The Hosmer-Leme-show test yielded χ² = 13.548, P = 0.094 (both > 0.05). The calibration curve showed good agreement between the nomogram model and actual observed values. The ROC and DCA decision curves indicated that the nomogram model has good predictive performance and clinical utility. The nomogram model developed in this study provides convenience for clinical assessment of the risk of oral frailty in older adults with type 2 diabetes, and helps doctors identify high-risk groups.