Model to Predict Oral Frailty Based on a Questionnaire: A Cross-Sectional Study

Abstract

A statistical model to predict oral frailty based on information obtained from questionnaires might help to estimate its prevalence and clarify its determinants. In this study, we aimed to develop and validate a predictive model to assess oral frailty thorough a secondary data analysis of a previous cross-sectional study on oral frailty conducted on 843 patients aged ≥ 65 years. The data were split into training and testing sets (a 70/30 split) using random sampling. The training set was used to develop a multivariate stepwise logistic regression model. The model was evaluated on the testing set and its performance was assessed using a receiver operating characteristic (ROC) curve. The final model in the training set consisted of age, number of teeth present, difficulty eating tough foods compared with six months ago, and recent history of choking on tea or soup. The model showed good accuracy in the testing set, with an area of 0.860 (95% confidence interval: 0.806–0.915) under the ROC curve. These results suggested that the prediction model was useful in estimating the prevalence of oral frailty and identifying the associated factors.