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Record W4297324014 · doi:10.3233/nre-228024

Which screening tool should be used for identifying aspiration risk associated with dysphagia in acute stroke? A Cochrane Review summary with commentary

2022· review· en· W4297324014 on OpenAlexaboutno aff
Carlotte Kiekens, Carlo Tognonato

Bibliographic record

VenueNeurorehabilitation · 2022
Typereview
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsDysphagiaMedicineStroke (engine)SwallowingAspiration pneumoniaIntensive care medicineRehabilitationAcute strokePhysical therapyPneumoniaCochrane LibraryPediatricsSurgeryMeta-analysisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Dysphagia is a common impairment in patients with acute stroke and is associated with an increased risk of complications such as aspiration pneumonia, malnutrition and dehydration, as well as with poor outcome and higher mortality. Therefore, immediate screening for aspiration risk is recommended, using a bedside swallow screening tool. OBJECTIVE: To determine the diagnostic accuracy and the sensitivity and specificity of bedside screening tests for detecting risk of aspiration associated with dysphagia in people with acute stroke. METHODS: A summary of the Cochrane Review by Boaden et al. 2021, with comments from a rehabilitation perspective. RESULTS: The review included 25 studies with 3953 participants and 37 screening tests. No single study demonstrated 100% sensitivity and specificity with low risk of bias for all domains. The best performing swallow screening tools were the Bedside Aspiration test (combined water swallow and instrumental tool), the Gugging Swallowing Screen (GUSS, water plus other consistencies) and the Toronto Bedside Swallowing Screening Test (TOR-BSST, water only). However, these tests were based on single studies with small sample sizes. It was not possible to explore the influence of sources of heterogeneity. CONCLUSIONS: No single swallow screening tool with high accuracy as well as good quality evidence could be identified, but recommendations for further high-quality research are offered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.164
GPT teacher head0.470
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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