Face mask versus nasal prong or nasopharyngeal tube for neonatal resuscitation in the delivery room: a systematic review and meta-analysis
Bibliographic record
Abstract
Importance The current neonatal resuscitation guidelines recommend positive pressure ventilation via face mask or nasal prongs at birth. Using a nasal interface may have the potential to improve outcomes for newborn infants. Objective To determine whether nasal prong/nasopharyngeal tube versus face mask during positive pressure ventilation of infants born <37 weeks’ gestation in the delivery room reduces in-hospital mortality and morbidity. Data sources MEDLINE (through PubMed), Google Scholar and EMBASE, Clinical Trials.gov and the Cochrane Central Register of Controlled Trials through August 2019. Study selection Randomised controlled trials comparing nasal prong/nasopharyngeal tube versus face mask during positive pressure ventilation of infants born <37 weeks’ gestation in the delivery room. Data analysis Risk of bias was assessed using the Covidence Collaboration Tool, results were pooled into a meta-analysis using a random effects model. Main outcome In-hospital mortality. Results Five RCTs enrolling 873 infants were combined into a meta-analysis. There was no statistical difference in in-hospital mortality (risk ratio (RR 0.98, 95% CI 0.63 to 1.52, p=0.92, I2=11%), rate of chest compressions in the delivery room (RR 0.37, 95% CI 0.10 to 1.33, p=0.13, I2=28%), rate of intraventricular haemorrhage (RR 1.54, 95% CI 0.88 to 2.70, p=0.13, I2=0%) or delivery room intubations in infants ventilated with a nasal prong/tube (RR 0.63, 95% CI 0.39,1.02, p=0.06, I2=52%). Conclusion In infants born <37 weeks’ gestation, in-hospital mortality and morbidity were similar following positive pressure ventilation during initial stabilisation with a nasal prong/tube or a face mask.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.037 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".