Effect of lung-protective ventilation with lower tidal volumes on clinical outcomes among patients undergoing surgery: a meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: In anesthetized patients undergoing surgery, the role of lung-protective ventilation with lower tidal volumes is unclear. We performed a meta-analysis of randomized controlled trials (RCTs) to evaluate the effect of this ventilation strategy on postoperative outcomes. METHODS: We searched electronic databases from inception through September 2014. We included RCTs that compared protective ventilation with lower tidal volumes and conventional ventilation with higher tidal volumes in anesthetized adults undergoing surgery. We pooled outcomes using a random-effects model. The primary outcome measures were lung injury and pulmonary infection. RESULTS: We included 19 trials (n=1348). Compared with patients in the control group, those who received lung-protective ventilation had a decreased risk of lung injury (risk ratio [RR] 0.36, 95% confidence interval [CI] 0.17 to 0.78; I2=0%) and pulmonary infection (RR 0.46, 95% CI 0.26 to 0.83; I2=8%), and higher levels of arterial partial pressure of carbon dioxide (standardized mean difference 0.47, 95% CI 0.18 to 0.75; I2=65%). No significant differences were observed between the patient groups in atelectasis, mortality, length of hospital stay, length of stay in the intensive care unit or the ratio of arterial partial pressure of oxygen to fraction of inspired oxygen. INTERPRETATION: Anesthetized patients who received ventilation with lower tidal volumes during surgery had a lower risk of lung injury and pulmonary infection than those given conventional ventilation with higher tidal volumes. Implementation of a lung-protective ventilation strategy with lower tidal volumes may lower the incidence of these outcomes.
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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 | 0.021 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.054 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".