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Record W4415234696 · doi:10.3389/fneur.2025.1690372

Barriers to and facilitators of implementing obstructive sleep apnea screening in stroke patients: a scoping review protocol

2025· review· en· W4415234696 on OpenAlexaboutno aff
Jiali Zhao, Wenhui Xiao, Fang Ding, Zhen Fang, Liang Guo, Shuhui Lou

Bibliographic record

VenueFrontiers in Neurology · 2025
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
FundersZhejiang Chinese Medical University
KeywordsObstructive sleep apneaProtocol (science)Stroke (engine)MEDLINESleep apnea

Abstract

fetched live from OpenAlex

Introduction: Obstructive sleep apnea (OSA) is a highly prevalent but frequently undiagnosed sleep disorder among stroke patients. It is associated with increased risks of stroke recurrence, reduced rehabilitation effectiveness, and elevated mortality. Despite guideline recommendations for routine OSA screening in stroke care, implementation remains inconsistent in clinical practice. As a modifiable sleep-related risk factor with significant implications for neurological outcomes, better integration of OSA screening in post-stroke care is urgently needed. Thus, this scoping review protocol outlines a systematic approach to identifying barriers to and facilitators of OSA screening in stroke populations. Methods and analysis: This scoping review will follow the methodological framework provided by the Joanna Briggs Institute (JBI) and will be reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The search will be performed on CNKI, WanFang, SinoMed, PubMed, Embase, Web of Science, the Cochrane Library, CINAHL, ProQuest Dissertations, OpenGrey, and Google Scholar. Targeted searches of international organization websites will also be conducted. No restrictions will be imposed based on study design or year of publication. Data will be synthesized using the content analysis approach and mapped onto the Ottawa Model of Research Use (OMRU), including domains such as evidence-based innovation, potential adopters, practice environment, implementation process, and adoption outcomes. Discussion: The findings are expected to inform future research and support the integration of sleep disorder screening into stroke care pathways. Ultimately, the review will improve stroke outcomes by addressing sleep health as a critical but often overlooked component of post-stroke management. Scoping review registration: Open science framework (osf.io/tb7z8).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.086
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.086
Threshold uncertainty score0.457

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0860.067
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0120.016
Bibliometrics0.0140.010
Science and technology studies0.0050.005
Scholarly communication0.0070.007
Open science0.0060.007
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0720.011

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 head0.020
GPT teacher head0.371
Teacher spread0.350 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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