Tracheostomies in term and preterm infants: A single‐center Canadian retrospective cohort
Bibliographic record
Abstract
OBJECTIVE: To examine patient characteristics, hospital course, and medical outcomes of neonatal tracheostomy at a single center. DESIGN: Retrospective cohort study. SETTING: Level III neonatal intensive care units (NICUs) in Edmonton, Canada. PATIENTS: Infants admitted to NICU who underwent tracheostomy between January 2013 and December 2017 inclusive. MAIN OUTCOME MEASURES: Hospital course, discharge, and 3-year post-tracheostomy outcomes were compared between preterm infants <29 weeks gestation and infants with congenital anomalies. RESULTS: Forty-three infants were identified; seven were lost to follow-up and excluded. Of the 36 analyzed, 86% survived to discharge. At discharge, 13% were decannulated, 36% required no mechanical ventilation, and 52% required mechanical ventilation. Median hospitalization was 295 days. At 3 years post-tracheostomy, 97% were alive. Proportions of infants with tracheostomy in situ was 80%, 73%, and 60% at 1, 2, and 3 years post tracheostomy. Tracheostomy incidence was 2.7% for preterm infants <29 weeks gestational age with 55% for subglottic stenosis. All preterm infants received postnatal steroids. Preterm infants underwent tracheostomy at later chronological age (123 vs. 81 days, p < 0.001), but similar corrected gestational age (42 + 5 vs. 51 + 2 weeks, p = 0.095). Preterm infants had more intubation attempts (17 vs. 4, p < 0.001), total extubations (8 vs. 2, p < 0.001), and days on ventilation before tracheostomy (100 vs. 78, p < 0.001). CONCLUSIONS: Infants who underwent tracheostomy in a Canadian public healthcare setting demonstrated decreasing tracheostomy dependence and high survival post tracheostomy, despite prolonged hospitalization. Preterm infants had more intubation and extubation events which may have contributed to airway injury.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".