Intra‐operative ventilation strategies and their impact on clinical outcomes: a systematic review and network meta‐analysis of randomised trials
Bibliographic record
Abstract
INTRODUCTION: Postoperative pulmonary complications are common and associated with significant morbidity and mortality; however, the optimal intra-operative ventilation strategy to prevent postoperative pulmonary complications remains unclear. The aim of this study was to evaluate the effect of intra-operative ventilation strategy, including tidal volumes, positive end-expiratory pressure (PEEP) and use of recruitment manoeuvres on the incidence of postoperative pulmonary complications in adults having non-cardiothoracic surgery. METHODS: Relevant databases were searched to identify randomised controlled trials that directly compared intra-operative ventilation strategies among surgical patients who were followed up for > 24 hours postoperatively and reported at least one outcome of interest. RESULTS: A total of 51 randomised controlled trials were included. Compared with a high tidal volume/zero PEEP strategy, low tidal volume strategies likely reduced the risk of postoperative pulmonary complications when combined with: high PEEP (risk ratio (RR) 0.44, 95%CI 0.22-0.87); high PEEP with recruitment manoeuvres (RR 0.60, 95%CI 0.49-0.75); personalised PEEP with recruitment manoeuvres (RR 0.53, 95%CI 0.42-0.69); low PEEP (RR 0.63, 95%CI 0.50-0.78); and low PEEP with recruitment manoeuvres (RR 0.65, 95%CI 0.46-0.93) (all moderate certainty evidence). Compared with a low tidal volume/low PEEP strategy, a low tidal volume strategy with personalised PEEP likely reduces the risk of postoperative pulmonary complications (RR 0.85, 95%CI 0.73-0.99, moderate certainty). DISCUSSION: Among patients undergoing non-cardiothoracic surgery, the use of intra-operative low tidal volume ventilation with a range of acceptable PEEP levels likely reduced the risk of postoperative pulmonary complications compared with high tidal volumes and zero PEEP. This study highlights the need for implementation research at both the provider and system levels to improve intra-operative adherence to lung protective ventilation strategies.
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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 | 0.020 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".