ArticleBMC oral health2025
Development and validation of risk-predicting model for oral frailty in older adults patients with stroke.
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 4 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Association between oral frailty and physical frailty among older adults: a meta-analysis.BMC oral health · 2026Pooled it
- Risk prediction models for oral frailty in older adults: a scoping review.Frontiers in medicine · 2026Pooled it
- Factors associated with oral frailty in older adults: a systematic review and meta-analysis.Frontiers in public health · 2025Pooled it
- Systematic review and meta-analysis of oral frailty prevalence among older hospitalized patients.Frontiers in public health · 2025Pooled it
- Bibliometric Analysis of Research Trends and Knowledge Structure in Oral Frailty.Gerodontology · 2026Review
- Article
- Diagnostic Prediction Models for Oral Frailty in Older Adults: A Systematic Review and Critical Appraisal.Patient preference and adherence · 2026Review
- Development and validation of a nomogram prediction model for oral frailty in community-dwelling older adults.Frontiers in public health · 2026Article
- Construction and validation of a risk prediction model for vitamin D deficiency in patients with type 2 diabetes mellitus.Frontiers in nutrition · 2026Article
- Construction and validation of a risk prediction model for oral frailty in rural hypertensive patients.Frontiers in public health · 2026Article
- Machine learning for oral frailty factors in hospitalized schizophrenia patients: two-stage feature selection and SHAP analysis.Frontiers in psychiatry · 2026Article
- A risk prediction model for oral frailty in elderly patients with COPD was constructed based on the health ecology model.BMC oral health · 2025Article
- Oral frailty trajectories and influencing factors in older adults with stroke: a longitudinal study.BMC nursing · 2025Article
- Oral health literacy and oral frailty: a parallel mediation model of self-efficacy and health-related quality of life among older adult stroke patients.Frontiers in public health · 2025Article
- Construction and validation of a risk prediction model for oral frailty in elderly patients with esophageal cancer.Frontiers in oncology · 2025Article
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Authors and funding
5 authors.
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Abstract
objectiveThis study aimed to construct a nomogram predicting oral frailty risk in Older adults patients with stroke.
designA cross-sectional study.
methodsWe selected 664 hospitalised older adults patients with stroke in a tertiary hospital from January 2023 to March 2024. Among them, 451 cases from January to December 2023 formed the modelling group, and 213 cases from January to March 2024 served as the validation group. Univariate and multivariate logistic regression analyses identified independent risk factors for oral frailty. A nomogram was developed and visualised using columnar charts. The model's predictive performance was assessed using the receiver operating characteristic curve and the Hosmer-Lemeshow test.
findingsThe prevalence of oral frailty was 47.7% in the modelling group and 47.9% in the validation groups, respectively. Age (OR = 10.351), frailty (OR = 9.171), number of comorbidities (OR = 11.301), nutritional risk (OR = 17.419), NIHSS (OR = 13.234), oral health evaluation index (OR = 0.316), Barthel index (OR = 0.247) were identified as significant independent risk factors. The areas under the receiver operating characteristic curve for the modelling and validation groups were 0.945 and 0.915, respectively.
conclusionA high prevalence of oral frailty was observed among Older adults patients with stroke with diverse risk factors. The nomogram provides an effective screening tool for identifying patients at high risk of oral frailty early in their hospital stay. The risk-prediction model showed good predictive efficacy and clinical utility.This study introduces a nomogram to predict oral frailty and identify associated risk factors in Older adults patients with stroke early on. It supports personalised care and precision medicine approaches in clinical practice.
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