Surfactant therapy for acute respiratory failure in children: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Exogenous surfactant is used to treat acute respiratory failure in children, although the benefits and harms in this setting are not clear. The objective of the present systematic review is to assess the effect of exogenous pulmonary surfactant on all-cause mortality in children mechanically ventilated for acute respiratory failure. METHODS: We searched the MEDLINE, EMBASE, CINAHL and Ovid Healthstar databases, the bibliographies of included trials and review articles, conference proceedings and trial registries. We included prospective, randomized, controlled trials of pulmonary surfactant that enrolled intubated and mechanically ventilated children with acute respiratory failure. We excluded trials that exclusively enrolled neonates or patients with asthma. Two reviewers independently rated trials for inclusion, extracted data and assessed the methodologic quality. We quantitatively pooled the results of trials, where suitable, using a random effects model. RESULTS: Six trials randomizing 314 patients were included. Surfactant use reduced mortality (relative risk = 0.7, 95% confidence interval = 0.4 to 0.97, P = 0.04), was associated with increased ventilator-free days (weighted mean difference = 2.5 days, 95% confidence interval = 0.3 to 4.6 days, P = 0.02) and reduced the duration of ventilation (weighted mean difference = 2.3 days, 95% confidence interval = 0.1 to 4.4 days, P = 0.04). CONCLUSION: Surfactant use decreased mortality, was associated with more ventilator-free days and reduced the duration of ventilation. No serious adverse events were reported.
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".