Neonatal Intubation Practice and Outcomes: An International Registry Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Neonatal tracheal intubation is a critical but potentially dangerous procedure. We sought to characterize intubation practice and outcomes in the NICU and delivery room (DR) settings and to identify potentially modifiable factors to improve neonatal intubation safety. METHODS: We developed the National Emergency Airway Registry for Neonates and collected standardized data for patients, providers, practices, and outcomes of neonatal intubation. Safety outcomes included adverse tracheal intubation–associated events (TIAEs) and severe oxygen desaturation (≥20% decline in oxygen saturation). We examined the relationship between intubation characteristics and adverse events with univariable tests and multivariable logistic regression. RESULTS: We captured 2009 NICU intubations and 598 DR intubations from 10 centers. Pediatric residents attempted 15% of NICU and 2% of DR intubations. In the NICU, the first attempt success rate was 49%, adverse TIAE rate was 18%, and severe desaturation rate was 48%. In the DR, 46% of intubations were successful on the first attempt, with 17% TIAE rate and 31% severe desaturation rate. Site-specific TIAE rates ranged from 9% to 50% (P < .001), and severe desaturation rates ranged from 29% to 69% (P = .001). Practices independently associated with reduced TIAEs in the NICU included video laryngoscope (adjusted odds ratio 0.46, 95% confidence interval 0.28–0.73) and paralytic premedication (adjusted odds ratio 0.38, 95% confidence interval 0.25–0.57). CONCLUSIONS: We implemented a novel multisite neonatal intubation registry and identified potentially modifiable factors associated with adverse events. Our results will inform future interventional studies to improve neonatal intubation safety.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".