Impact of Physician Training Level on Neonatal Tracheal Intubation Success Rates and Adverse Events: A Report from National Emergency Airway Registry for Neonates (NEAR4NEOS)
Bibliographic record
Abstract
INTRODUCTION: Neonatal tracheal intubation (TI) outcomes have been assessed by role, but training level may impact TI success and safety. Effect of physician training level (PTL) on the first-attempt success, adverse TI-associated events (TIAEs), and oxygen desaturation was assessed. METHODS: Prospective cohort study in 11 international NEAR4NEOS sites between October 2014 and December 2017. Primary TIs performed by pediatric/neonatal physicians were included. Univariable analysis evaluated association between PTL, patient/practice characteristics, and outcomes. Multivariable analysis with generalized estimating equation assessed for independent association between PTL and outcomes (first-attempt success, TIAEs, and oxygen desaturation ≥20%; attending as reference). RESULTS: Of 2,608 primary TIs, 1,298 were first attempted by pediatric/neonatal physicians. PTL was associated with patient age, weight, comorbidities, TI indication, difficult airway history, premedication, and device. First-attempt success rate differed across PTL (resident 23%, fellow 53%, and attending 60%; p < 0.001). There was no statistically significant difference in TIAEs (resident 22%, fellow 20%, and attending 25%; p = 0.34). Desaturation occurred more frequently with residents (60%), compared to fellows and attendings (46 and 53%; p < 0.001). In multivariable analysis, adjusted odds ratio of the first-attempt success was 0.18 (95% CI: 0.11-0.30) for residents and 0.80 (95% CI: 0.51-1.24) for fellows. PTL was not independently associated with adjusted odds of TIAEs or severe oxygen desaturation. CONCLUSION: Higher PTL was associated with increased first-attempt success but not TIAE/oxygen desaturation. Identifying strategies to decrease adverse events during neonatal TI remains critical.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".