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Updated: May 13, 2026

Adapting Human Videofluoroscopic Swallow Study Methods to Detect and Characterize Dysphagia in Murine Disease Models
Published on: March 1, 2015
Predictive models for dysphagia in older adults: a systematic review and meta-analysis
Shujun Fan1, Bingbing Chen1, Chuan Yin1
1Nursing Department, Fuyang Normal University Second Affiliated Hospital, Fuyang, Anhui, China.
Introduction:
Dysphagia is a common condition among older adults, closely linked to aging and neurodegenerative diseases. It can lead to malnutrition, frailty, and aspiration pneumonia, thereby impairing quality of life and clinical outcomes. Although various interventions may improve swallowing function, early identification of high-risk individuals remains challenging. Existing predictive models show inconsistent performance and lack systematic evaluation. This study aimed to systematically review and assess predictive models for dysphagia risk in older adults.
Methods:
A comprehensive search was conducted across CNKI, the Chinese Science and Technology Journal Database, the Chinese Biomedical Literature Database, Wanfang Data, PubMed, Web of Science, and the Cochrane Library, covering studies published up to September 15, 2025.
Results:
Of 7,113 records identified, 17 met inclusion criteria, with only two performing external validation. Reported AUCs ranged from 0.682 to 0.926, and all studies showed a high overall risk of bias. The pooled AUC from the meta-analysis was 0.82 (95% CI: 0.77-0.88). Common predictors included advanced age, smoking history, reduced self-care ability, polypharmacy, frailty, malnutrition, cognitive impairment, and poor oral health.
Discussion:
Overall, predictive modeling for dysphagia in older adults remains in an early stage, limited by methodological flaws and insufficient external validation. Future research should follow PROBAST standards and conduct large, multicenter validations to improve model reliability and clinical utility.
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