Abstract
OBJECTIVE: To investigate the prevalence of oral frailty among hospitalized elderly patients with chronic heart failure (CHF), identify its associated risk factors, and construct and validate a risk assessment model to provide scientific evidence for early identification and intervention. METHODS: A convenience sample of 343 hospitalized elderly patients with chronic heart failure was recruited from a tertiary general hospital in Mianyang, China, between May and November 2025. Data were collected using a general information questionnaire, the Oral Frailty Index-8 (OFI-8), Frailty Phenotype (FP), Mini Nutritional Assessment-Short Form (MNA-SF), heart function-related clinical indicators, the Geriatric Oral Health Self-Efficacy Scale, the Geriatric Oral Health Assessment Index (GOHAI), and the Geriatric Depression Scale-Short Form (GDS-SF). Logistic regression analysis was performed to identify factors associated with oral frailty. A visualized nomogram prediction model was developed using R software. Model discrimination and calibration were evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and Bootstrap resampling. Decision curve analysis (DCA) was conducted to assess the clinical applicability of the model. RESULTS: A total of 350 questionnaires were distributed, and 343 valid questionnaires were returned, yielding an effective response rate of 98.0%. Among the 343 patients, 176 cases of oral frailty were identified, with a prevalence of 51.3%. Logistic regression analysis showed that advanced age, smoking, physical frailty, malnutrition, polypharmacy, and oral health-related self-efficacy were significant predictors of oral frailty (all p < 0.05). The prediction model demonstrated good discrimination, with an AUC of 0.857. The Hosmer-Lemeshow test indicated good model fit (χ(2) = 4.696, p = 0.790). After Bootstrap internal validation, the corrected concordance index (C-index) was 0.845, and the calibration curve showed good agreement between predicted and observed outcomes. Decision curve analysis indicated that the model provided a high net clinical benefit. CONCLUSION: The risk assessment model for oral frailty in elderly patients with chronic heart failure developed in this study demonstrates good discrimination and calibration. It may serve as a reliable tool for clinicians to identify and screen individuals at high risk of oral frailty at an early stage, thereby facilitating targeted prevention and intervention strategies.