Interventions for oropharyngeal dysphagia in acute and critical care: a systematic review and meta-analysis
Bibliographic record
Abstract
To determine the effectiveness of dysphagia interventions compared to standard care in improving oral intake and reducing aspiration for adults in acute and critical care. We searched electronic literature for randomised and quasi-randomised trials and bibliography lists of included studies to March 2020. Study screening, data extraction, risk of bias and quality assessments were conducted independently by two reviewers. Meta-analysis used fixed effects modelling. The systematic review protocol is registered and published. We identified 22 studies (19 stroke, 2 intensive care stroke and 1 general intensive care) testing 9 interventions and representing 1700 patients. Swallowing treatment showed no evidence of a difference in the time to return to oral intake ( n = 33, MD (days) − 4.5, 95% CI − 10.6 to 1.6, 1 study, P = 0.15) (very low certainty) or in aspiration following treatment ( n = 113, RR 0.79, 95% CI 0.44 to 1.45, 4 studies, I 2 = 0%, P = 0.45) (low certainty). Swallowing treatment showed evidence of a reduced risk of pneumonia ( n = 719, RR 0.71, 95% CI 0.56 to 0.89, 8 studies, I 2 = 15%, P = 0.004) (low certainty) but no evidence of a difference in swallowing quality of life scores ( n = 239, MD − 11.38, 95% CI − 23.83 to 1.08, I 2 = 78%, P = 0.07) (very low certainty). There is limited evidence for the effectiveness of swallowing treatments in the acute and critical care setting. Clinical trials consistently measuring patient-centred outcomes are needed.
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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 | 0.021 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.049 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".