Association between Dysphagia and Frailty in Older Adults: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Increasing bodies of epidemiological evidence indicate potential associations between dysphagia and the risk of frailty in older adults. We hypothesized that older adults with symptoms of dysphagia might have a higher prevalence of frailty or prefrailty than those without dysphagia. METHODS: We systematically searched the PubMed, Embase, and Cochrane Library databases for relevant studies published through 20 April 2022. Cross-sectional and longitudinal studies that examined the associations between dysphagia and the existence of frailty or prefrailty in community-dwelling, facility-dwelling, or hospitalized adults aged 50 years or older were synthesized. The Newcastle-Ottawa Scale was used to evaluate study quality. RESULTS: The meta-analysis comprised 12 cohorts, including 5,503,543 non-frailty participants and 735,303 cases of frailty or prefrailty. Random-effect meta-analysis demonstrated a significant association between dysphagia and the risk of frailty and prefrailty (OR, 3.24; 95% CI, 2.51-4.20). In addition, we observed consistent results across the subgroups and heterogeneity assessments. CONCLUSIONS: We propose including dysphagia assessment as a critical factor in the cumulative deficit model for identifying frailty in older adults. Understanding dysphagia and the potential role of nutritional supplements in older adults may lead to improved strategies for preventing, delaying, or mitigating frailty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.022 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".