91: Lung Aeration in Spontaneously Breathing Preterm Infants Immediately After Birth
Bibliographic record
Abstract
At birth preterm infants have to facilitate the early development of an effective functional residual capacity (FRC), remove CO2, and improve oxygenation in order to achieve fetal-to-neonatal transition. The aim of the study was to examine how preterm infants <35 weeks achieve lung aeration at birth. Deliveries of preterm infants ≤35 weeks gestation at the Royal Alexandra Hospital were attend by the research team. Infants who received CPAP only were eligible for inclusion. A combined CO2 and flow-sensor was placed between the mask and the ventilation device. During spontaneous breathing tidal volume (VT) and exhaled CO2 (ECO2) were recorded for the first 200 breaths to analyze lung aeration patterns. Thirty preterm infants were included with a total of 3200 breaths were analyzed. The mean (SD) gestational age was 30.3 (2) weeks and birth weight 1517 (442)g. The mean initial VT for the first 30 breath was 5–6 mL/kg and ECO2 between 15–22 mm Hg. VT and ECO2 increased over the next 20 breaths to 7–8 mL/kg and 25–32 mm Hg. For the remaining observation period VT plateaued at 4–6 mL/kg and ECO2 continued to increase to 35–37 mm Hg (Figure 1A and B). Preterm infants start taking deeper breaths approximately 30 breaths after initiating spontaneous breathing to inflate their lung. Concurrently CO2 removal rises as alveoli are recruited. FRC is established in two phases – phase one involves large volume breaths with poor alveolar aeration (so poor CO2 elimination), and phase two involves smaller breaths but elimination of CO2 as a consequence of adequate aeration.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".