Sustained Lung Inflations During Neonatal Resuscitation at Birth: A Meta-analysis
Bibliographic record
Abstract
CONTEXT: The International Liaison Committee on Resuscitation prioritized review of sustained inflation (SI) of the lung at birth. OBJECTIVE: To complete a systematic review and meta-analysis comparing strategies using 1 or more SI ≥1 second with intermittent inflations <1 second for newborns at birth. DATA SOURCES: Medline, Embase, and Evidence-Based Medicine Reviews were searched from January 1, 1946, to July 20, 2020. STUDY SELECTION: Studies were selected by pairs of independent reviewers in 2 stages. DATA EXTRACTION: Reviewers extracted data, appraised risk of bias, and assessed certainty of evidence for each outcome. RESULTS: Ten trials enrolling 1502 preterm newborns were included. Five studies included newborns who did not receive assisted ventilation at the outset. There were no differences between SI and control groups for death before discharge or key morbidities. For death within the first 2 days, comparing SI with the controls, risk ratio was 2.42 (95% confidence interval = 1.15-5.09). In subgroup analysis of preterm infants ≤28 + 0 weeks' gestation, for death before discharge, risk ratio was 1.38 (95% confidence interval = 1.00-1.91). Together, these findings suggest the potential for harm of SI. LIMITATIONS: The certainty of evidence was very low for death in the delivery room and low for all other outcomes. CONCLUSIONS: In this systematic review, we did not find benefit in using 1 or more SI >5 seconds for preterm infants at birth. SI(s) may increase death before discharge among the subgroup born ≤28 + 0 weeks' gestation. There is insufficient evidence to determine the likely effect of SI(s) on other key morbidities.
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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) | 0.021 | 0.041 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".