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[Summary of the best evidence for early rehabilitation of ICU-acquired swallowing dysfunction].

2025· other· zh· W4415648863 on OpenAlexaboutno aff
Qianqian Peng, Ruixiang Sun, Xiaopan Xu, Ke Fang, Haijiao Jiang, Xiancui Zhang

Bibliographic record

VenuePubMed · 2025
Typeother
Languagezh
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationContext (archaeology)SwallowingDysphagiaBest evidenceEvidence-based practice

Abstract

fetched live from OpenAlex

OBJECTIVE: To systematically search and integrate the best evidence for early rehabilitation of ICU-acquired swallowing dysfunction (ICU-ASD) using evidence-based medicine methods, providing high-quality evidence-based support for intensive care unit (ICU) healthcare professionals in implementing early rehabilitation assessment and intervention strategies for ICU-ASD. METHODS: The systematic search was conducted according to the "6S" pyramid evidence model. Multiple authoritative databases and resources were comprehensively searched, including: National Guideline Clearinghouse (NGC), National Institute for Health and Care Excellence (NICE), Canadian Medical Association Clinical Practice Guidelines Library (CMACPGL), New Zealand Guidelines Group (NZGG), Guidelines International Network (GIN), Registered Nurses' Association of Ontario (RNAO), Scottish Intercollegiate Guidelines Network (SIGN), PubMed/Medline, Cochrane Library, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, JBI Evidence-Based Health Care Database, Physiotherapy Evidence Database (PEDro), Chinese Medical Pulse Guidelines Website, SinoMed, CNKI, Wanfang Data, UpToDate, BMJ Best Practice, and professional association websites. The search encompassed guidelines, expert consensus statements, original studies [including cohort studies, quasi-experimental studies, and randomized controlled trials (RCT)], systematic reviews, and evidence summaries related to the prevention and management of ICU-ASD. The search period was limited from the inception of each database to November 30, 2024. The best evidence for early rehabilitation of ICU-ASD was summarized. The quality assessment of the literature and the extraction and synthesis of evidence were independently performed by two researchers with expertise in evidence-based medicine methodology. RESULTS: A total of 16 articles were included, consisting of 1 clinical decision-making study, 1 cohort study, 2 guidelines, 2 RCTs, 6 systematic reviews, 1 evidence summary, 2 expert consensuses, and 1 expert opinion. Following quality assessment, all 16 articles were incorporated into the analysis. For the early rehabilitation of ICU-ASD, five major themes were ultimately identified and 25 best evidence items were summarized, focusing on: multidisciplinary collaboration, swallowing screening and assessment, rehabilitation interventions, dietary and nutritional management, and oral hygiene. CONCLUSIONS: The evidence summary provides individualized rehabilitation strategies for ICU-ASD patients, but their implementation still needs to be adapted to China's clinical practice context and patient preferences.

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)0.011
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.055
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0210.014
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.041
GPT teacher head0.269
Teacher spread0.229 · 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 designSystematic review
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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