Nasal mask ventilator-delivered versus face maskT-piece resuscitator positive pressure ventilation during resuscitation of preterm neonates: a cohort study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the clinical impact of nasal mask ventilator-delivered positive pressure ventilation (PPV) versus face mask manual T-piece resuscitator PPV during resuscitation of preterm neonates. DESIGN: weeks of gestational age (GA) who received PPV ≤10 min after birth, before and after changing the approach during resuscitation from face mask manual T-piece resuscitator PPV (epoch 1, April 2018-April 2020) to nasal mask ventilator-delivered PPV (epoch 2, May 2020-February 2022). The association between birth epoch and the primary outcome of emergent intubation (EI) during resuscitation was examined by multivariable logistic regression and inverse probability of treatment weighting models. Additional outcomes compared between epochs were rates of advanced resuscitation, and early (≤7 days) and late (>7 days) prematurity-related morbidities. RESULTS: Of 545 eligible births, 336 (62%) received PPV; 176 (58%) in epoch 1 and 160 (66%) in epoch 2. Neonates in epoch 1 had lower GA (26.7 (25.9-27.9) vs 27.4 (26.0-28.1) weeks; p=0.02) but similar birth weight (900 (730-1060) vs 880 (740-1085) g; p=0.53). Neonates in epoch 2 had lower rates of EI (16% vs 44%; p<0.001) and less use of post-resuscitation invasive ventilation (22% vs 59%; p<0.001). After accounting for confounders, nasal mask ventilator-delivered PPV remained associated with lower odds of EI (adjusted OR 0.23 (95% CI 0.13 to 0.42)). Secondary outcomes were similar between groups. CONCLUSION: Nasal mask ventilator-delivered PPV may reduce EI during resuscitation of preterm neonates. Our observations support a large trial of nasal mask ventilator-delivered PPV in this context.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".