Evidence map›Paper›PMID 42051704›Full record

ArticleFrontiers in medicine2026

Construction and validation of a risk prediction model for oral frailty in elderly patients with chronic heart failure.

Xue Song, Rong Chai, Jing Ye, Xiaohua Chen, Yuzhu Lin, Chen Xu

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Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xue SongMianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.
Rong ChaiMianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.
Jing YeMianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.
Xiaohua ChenMianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.
Yuzhu LinMianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.
Chen XuMianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 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.

Indexed as

chronic heart failureelderlynomogramoral frailtyrisk assessment model

Identifiers

PMID42051704
PMCPMC13110992

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.