86: Success Rate and Associated Clinical Factors of Early Extubation in the Preterm Neonate Below 29 Weeks of Gestation
Bibliographic record
Abstract
Mechanical ventilation in preterm neonates is associated with adverse health outcomes. Early extubation may mitigate these risks. Success rate and associated factors of early extubation are not clearly described. Assess success rate of early extubation in infants <29 weeks gestation and identify factors associated with extubation outcome. Retrospective study in a level 3 NICU (Ste Justine, Montreal, Canada). Neonates born in 2012 and 2013 at <29 weeks gestation intubated in the first seven days of life and extubated in the following 72 hours were included. Infants with congenital anomaly or that died before extubation were excluded. Primary outcome was success of early extubation (not requiring reintubation for >72 h). Secondary outcome was to identify factors associated with extubation success.χ2 was used for categorical variables, independent t test was used for continuous variables and multiple logistic regression (MLR) was performed to identify factors contributing to extubation success. Of the 209 patients born at <29 weeks gestation during the study period, 75 were included. Characteristics of infants who remained extubated (success) vs. were reintubated (failure) are presented. There were no differences in pre-extubation ventilatory parameters. MLR identified PDA as a significant contributor to extubation failure: OR 0.05 (95% CI 0.01 – 0.42). Patients failing early extubation had increased risk of severe ROP or death: OR 0.14 (95% CI 0.03 – 0.66). In our cohort of infants <29 weeks gestation, early extubation succeeded in 2/3 of patients. PDA might be a significant contributor to extubation outcome. Patients failing extubation had increased risk of severe ROP or death.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".