Respiratory Management of Extremely Preterm Infants: An International Survey
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: There are significant international variations in chronic lung disease rates among very preterm infants yet there is little data on international variations in respiratory strategies. OBJECTIVE: To evaluate practice variations in the respiratory management of extremely preterm infants born at < 29 weeks' gestational age (GA) among 10 neonatal networks participating in the International Network for Evaluating Outcomes (iNeo) of Neonates collaboration. METHODS: A web-based survey was sent to the representatives of 390 neonatal intensive care units from Australia/New Zealand, Canada, Finland, Illinois (USA), Israel, Japan, Spain, Sweden, Switzerland, and Tuscany (Italy). Responses were based on practices in 2015. RESULTS: Overall, 321 of the 390 units responded (82%). The majority of units within networks (40-92%) mechanically ventilate infants born at 23-24 weeks' GA on continuous positive airway pressure (CPAP) with 30-39% oxygen in respiratory distress within 48 h after birth, but the proportion of units that offer mechanical ventilation for infants born at 25-26 weeks' GA at similar settings varied significantly (20-85% of units within networks). The most common respiratory strategy for infants born at 27-28 weeks' GA on CPAP with 30-39% oxygen with respiratory distress within 48 h after birth used by units also varied significantly among networks: mechanical ventilation (0-60%), CPAP (3-82%), intubation and surfactant administration with immediate extubation (0-75%), and less invasive surfactant administration (0-68%). CONCLUSIONS: There are marked variations but also similarities in respiratory management of extremely preterm infants between networks. Further collaboration and exploration is needed to better understand the association of these variations in practice with pulmonary outcomes.
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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 | 0.001 | 0.000 |
| 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 it