Indications and outcomes of neonatal intubation: A single-center, prospective study in a middle-income country
Bibliographic record
Abstract
BACKGROUND: This study assessed the success rate and associated complications of hospital-wide neonatal endotracheal intubations by pediatric residents and neonatal fellows using direct laryngoscopy. Secondary objectives were to identify characteristics and indications for the procedure in a tertiary-care center. METHODS: A cross-sectional observational study was conducted. We prospectively collected performance and infant outcome data after neonatal intubation between March 1, 2019 and February 29, 2020. RESULTS: 171 intubations were observed in 105 infants. The median infant gestational age was 31.0 weeks (interquartile range [IQR]: 27.5-36.0 weeks). Fifty infants (48%) were very low birth weight (VLBW, <1500 g; median 1640 g [IQR: 870-2420 g]). The most common indication for intubation was respiratory failure (65%). Pediatric residents and neonatal fellows had overall success rates of 66% and 98%, respectively. The success rate for the first intubation attempt was higher with more advanced pediatric residency training (P < 0.001). The median attempts for each intubation were 1 (IQR: 1-2) for both VLBW and non-VLBW infants (P = 0.48). The adverse outcome rates were 5% and 3% for VLBW and non-VLBW infants, respectively (P = 0.53). More than 2 intubation attempts was the only significant independent risk factor for adverse outcomes (adjusted odds ratio 6.7; 95% CI 1.3-33.6; P = 0.02). CONCLUSIONS: The success rate of pediatric residents for neonatal intubation was similar for VLBW and non-VLBW infants. The main indication was respiratory failure, and nearly half were infants with VLBW. To minimize adverse sequelae, written guidelines limiting the number of intubation attempts by junior trainees are 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".