Association of Positive End-Expiratory Pressure and Lung Recruitment Selection Strategies with Mortality in Acute Respiratory Distress Syndrome: A Systematic Review and Network Meta-analysis
Bibliographic record
Abstract
Abstract Rationale The most beneficial positive end-expiratory pressure (PEEP) selection strategy in patients with acute respiratory distress syndrome (ARDS) is unknown, and current practice is variable. Objectives To compare the relative effects of different PEEP selection strategies on mortality in adults with moderate to severe ARDS. Methods We conducted a network meta-analysis using a Bayesian framework. Certainty of evidence was evaluated using grading of recommendations assessment, development and evaluation methodology. Measurements and Main Results We included 18 randomized trials (4,646 participants). Compared with a lower PEEP strategy, the posterior probability of mortality benefit from a higher PEEP without lung recruitment maneuver (LRM) strategy was 99% (risk ratio [RR], 0.77; 95% credible interval [CrI], 0.60–0.96, high certainty), the posterior probability of benefit of the esophageal pressure–guided strategy was 87% (RR, 0.77; 95% CrI, 0.48–1.22, moderate certainty), the posterior probability of benefit of a higher PEEP with brief LRM strategy was 96% (RR, 0.83; 95% CrI, 0.67–1.02, moderate certainty), and the posterior probability of increased mortality from a higher PEEP with prolonged LRM strategy was 77% (RR, 1.06; 95% CrI, 0.89–1.22, low certainty). Compared with a higher PEEP without LRM strategy, the posterior probability of increased mortality from a higher PEEP with prolonged LRM strategy was 99% (RR, 1.37; 95% CrI, 1.04–1.81, moderate certainty). Conclusions In patients with moderate to severe ARDS, higher PEEP without LRM is associated with a lower risk of death than lower PEEP. A higher PEEP with prolonged LRM strategy is associated with increased risk of death when compared with higher PEEP without LRM.
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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 | 0.025 | 0.067 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".