Tracheal Intubation in Term Infants—Trends, Risk Factors, and Outcomes: A Population-Based Study [A281]
Bibliographic record
Abstract
INTRODUCTION: Tracheal intubation (TI) is associated with hypoxia and an increase in intracranial pressure, potentially leading to brain injury. We aimed to estimate trends, risk factors, and outcomes among term neonates undergoing TI, using a large population-based database. METHODS: This is a retrospective cohort study of 2,122,245 births using the Healthcare Cost and Utilization Project/Nationwide Inpatient Sample from 2015 to 2018. Term infants having undergone TI were identified using ICD-10 codes. Infants with congenital anomalies were excluded. Multivariate logistic regression models were used to evaluate outcomes while adjusting for confounders. RESULTS: Rate of death was 4.4% among the 13,205 infants who had TI, and 0.04% among the 2,109,040 infants who did not have TI. Infants undergoing TI in urban teaching hospitals had higher odds of death compared to infants in rural hospitals (OR 1.77, 95% CI 1.17–2.69). Infants who had TI and died had higher odds of intraventricular hemorrhage (IVH; OR 5.28, 95% CI 4.08–6.83), hypoxic-ischemic encephalopathy (HIE; OR 2.34, 95% CI 1.86–2.94), and sepsis (OR 1.50, 95% CI 1.23–1.83); pulmonary hemorrhage (PH) was the greatest predictor of death (OR 7.34, 95% CI 5.17–10.42). Among infants who had TI and survived, odds of IVH (OR 76.24, 95% CI 67.33–86.32), HIE (OR 291.86, 95% CI 263.26–323.56), sepsis (OR 28.76, 95% CI 27.39–30.31), and PH (OR 542.01, 95% CI 384.73–763.58) were higher compared to controls. CONCLUSION: Term infants undergoing TI have higher mortality rates compared to controls; TI survivors have an increased risk of neurological sequelae. Non-invasive respiratory support and postnatal neuroprotective interventions should be optimized in term infants.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".