A Review of Oxygen Use During Chest Compressions in Newborns—A Meta-Analysis of Animal Data
Bibliographic record
Abstract
Background: International consensus statements for resuscitation of newborn infants recommend provision of 100% oxygen once chest compressions are required. However, 100% oxygen exacerbates reperfusion injury and reduces cerebral perfusion in newborn babies. Objective: We aimed to establish whether resuscitation with air during chest compression is feasible and safe in newborn infants compared with 100% oxygen. Methods: Systematic search of PubMed, Google Scholar and CINAHL for articles examining variable oxygen concentrations during chest compressions in term newborns. Results: Overall, no human studies but eight animal studies (n=323 animals) comparing various oxygen concentrations during chest compression were identified. The pooled analysis showed no difference in mortality rates for animals resuscitated with air versus 100% oxygen (risk ratio 1.04 [0.35, 3.08], I2=0%, p=0.94). ROSC was also similar between groups with a mean difference of -3.8 [-29.7 – 22] sec, I2=0%, p=0.77. No difference in oxygen damage or adverse events were identified between groups. Conclusions: Air had similar time to ROSC and mortality as 100% oxygen during neonatal chest compression. A large randomized controlled clinical trial comparing air vs. 100% oxygen during neonatal chest compression is warranted.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".