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Record W4414491415 · doi:10.1136/bmjopen-2025-098814

Consequences in critically ill patients with prolonged mechanical ventilation after diaphragmatic stimulation techniques: a systematic review and meta-analysis

2025· article· en· W4414491415 on OpenAlexaboutno aff
Siqi Tong, Yi Yang, Yang Li, Ling Liu, Wei Chou Chang

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsCritically illMechanical ventilationDiaphragmatic breathingMechanical ventilatorVentilation (architecture)Critical illness

Abstract

fetched live from OpenAlex

OBJECTIVE: Prolonged mechanical ventilation (MV) may lead to poor outcomes. This systematic review and meta-analysis aimed to investigate the effects of diaphragmatic stimulation on the duration of MV (DMV), the intensive care unit (ICU) length of stay (ILOS), the proportion of patients successfully weaned and maximum inspiratory pressure (MIP) in patients with prolonged MV. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Cochrane library, Embase, Pubmed and Web of Science up to December 2024. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials (RCTs) and cohort studies evaluating the outcomes of patients with prolonged MV after diaphragmatic stimulation were included up to December 2024. DATA EXTRACTION AND SYNTHESIS: All articles were independently assessed by two reviewers, and a third reviewer was consulted to resolve different evaluations. Newcastle-Ottawa Scale (NOS) and the Cochrane Collaboration tool in RevMan V.5.3 software (The Cochrane Collaboration, 2014) were applied to assess the quality of cohort studies or RCTs. The meta-analysis was carried out with RevMan V.5.3 software, applying a random-effects model and presenting results with 95% CIs. Heterogeneity was examined using the Higgins I² statistic, and subgroup analyses were carried out to investigate possible contributors to heterogeneity. Sensitivity analyses were further conducted in Stata 18.0 (StataCorp LP, College Station, TX, USA). Potential publication bias was assessed through funnel plots combined with Egger's regression test. For each outcome, the certainty of evidence was appraised according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE). RESULTS: Ten studies involving 802 patients (349 received diaphragmatic stimulation) were included. The meta-analysis indicated that patients receiving diaphragmatic stimulation had shorter DMV (mean differences (MD) -5.69 d, 95% CI -10.99 to -0.39, p=0.04) and ILOS (MD -5.48 d, 95% CI -10.72 to -0.24, p=0.04). The proportion of patients successfully weaned was larger in patients with diaphragmatic stimulation (risk ratios (RR) 1.25, 95% CI 1.01 to 1.53, p=0.04). The MIP increased compared with the control group. CONCLUSIONS: The promising results suggest that diaphragmatic stimulation has the potential to shorten DMV and ILOS and accelerate weaning from ventilator. PROSPERO REGISTRATION NUMBER: CRD42024599512.

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)0.013
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.034
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.042
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.057
GPT teacher head0.394
Teacher spread0.337 · 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 designMeta-analysis
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

Citations5
Published2025
Admission routes1
Has abstractyes

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