Identifying High‐Quality Non‐Instrumental Dysphagia Screening Tools for Detection of Adult Dysphagia Case in Acute‐Care Settings: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: As patients nowadays tend to have multiple diseases and complex medical histories, our aim was to identify high-quality, non-instrumental dysphagia screening tools used for the detection of adult dysphagia cases in all disease categories in acute-care settings. METHOD: A literature search was conducted in five databases from each database's earliest inception to 31 July 2021 and guided by five keywords: 'dysphagia', 'deglutition', 'screening', 'test' and 'measure'. Without limiting the search in any specific disease category, reviewers assessed original studies and identified tools if they had been validated against instrumental evaluations and if they had been designed as a pass-fail procedure to screen whether dysphagia is absent or present. We further excluded any tool if it was (1) for pediatric focus, or (2) a patient self-report questionnaire. All final tool candidates underwent a methodological quality appraisal using the Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). RESULT: Out of 195 studies with 165 tools identified, 20 tool candidates underwent QUADAS-2 review. We found six high-quality, non-instrumental screening tools for detecting adult dysphagia cases in acute-care settings, including the Yale Swallow Protocol, Gugging Swallowing Screen, Toronto Bedside Swallowing Screening Test (both English and Portuguese versions), Sapienza Global Bedside Evaluation of Swallowing and Two-Step Thickened Water Test. These high-quality tools were developed primarily for patients with stroke. Only Yale Swallow Protocol was originally tested for heterogeneous populations with stroke, multiple sclerosis, traumatic brain injury, oesophageal surgery, neurosurgery and head-and-neck cancer. CONCLUSIONS: The results highlight the gap in the unavailability of high-quality dysphagia screening tool in several emerged high-risk populations including elderly inpatients, or patients following endotracheal extubation. Further research is needed to determine whether these six tools can be effectively applied across different high-risk populations in acute-care settings to screen for cases finding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".