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Systematic review finds predictive models for dysphagia risk in older adults show variable performance

Systematic review finds predictive models for dysphagia risk in older adults show variable performan…
Photo by Sasun Bughdaryan / Unsplash
Key Takeaway
Note: Predictive models for dysphagia risk show promise but require more validation before clinical use.

This systematic review and meta-analysis evaluated the performance of predictive models for dysphagia risk in older adults. The analysis included 17 studies identified from 7,113 records, though specific study settings, interventions, and comparators were not reported. The primary outcome was model performance measured by Area Under the Curve (AUC).

The pooled AUC across studies was 0.82 (95% CI: 0.77–0.88), with individual study AUCs ranging from 0.682 to 0.926. Common predictors identified across models included advanced age, smoking history, reduced self-care ability, polypharmacy, frailty, malnutrition, cognitive impairment, and poor oral health. No safety or tolerability data were reported.

Key limitations significantly constrain interpretation. All included studies showed a high overall risk of bias, and the authors noted methodological flaws throughout the evidence base. Only two studies performed external validation, indicating insufficient testing of model generalizability. The review concludes that predictive modeling for dysphagia in older adults remains in an early stage of development.

For clinical practice, this evidence suggests current predictive models show variable discrimination but lack proven reliability. The high risk of bias and limited external validation mean these tools should not yet be relied upon for clinical decision-making. Further rigorous development and validation are needed before considering implementation.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedApr 2026
View Original Abstract ↓
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. 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. 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. 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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