Non-invasive ventilation versus invasive weaning in critically ill adults: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Extubation to non-invasive ventilation (NIV) has been investigated as a strategy to wean critically ill adults from invasive ventilation and reduce ventilator-related complications. METHODS: We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, proceedings of four conferences and bibliographies (to June 2020) for randomised and quasi-randomised trials that compared extubation with immediate application of NIV to continued invasive weaning in intubated adults and reported mortality (primary outcome) or other outcomes. Two reviewers independently screened citations, assessed trial quality and abstracted data. RESULTS: We identified 28 trials, of moderate-to-good quality, involving 2066 patients, 44.6% with chronic obstructive pulmonary disease (COPD). Non-invasive weaning significantly reduced mortality (risk ratio (RR) 0.57, 95% CI 0.44 to 0.74; high quality), weaning failures (RR 0.59, 95% CI 0.43 to 0.81; high quality), pneumonia (RR 0.30, 95% CI 0.22 to 0.41; high quality), intensive care unit (ICU) (mean difference (MD) -4.62 days, 95% CI -5.91 to -3.34) and hospital stay (MD -6.29 days, 95% CI -8.90 to -3.68). Non-invasive weaning also significantly reduced the total duration of ventilation, duration of invasive ventilation and duration of ventilation related to weaning (MD -0.57, 95% CI -1.08 to -0.07) and tracheostomy rate. Mortality, pneumonia, reintubation and ICU stay were significantly lower in trials enrolling COPD (vs mixed) populations. CONCLUSION: Non-invasive weaning significantly reduced mortality, pneumonia and the duration of ventilation related to weaning, particularly in patients with COPD. Beneficial effects are less clear (or more careful patient selection is required) in non-COPD patients. PROSPERO REGISTRATION NUMBER: CRD42020201402.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.034 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".