Lung Recruitment Using High-Frequency Oscillation Volume Guarantee in Preterm Infants with Evolving Bronchopulmonary Dysplasia
Bibliographic record
Abstract
BACKGROUND: Stepwise lung recruitment maneuvers (LRMs) may be used in ventilated preterm infants. However, its use in high-frequency oscillation with volume guarantee (HFO-VG) is not well studied. METHODS: Preterm infants treated with HFO-VG who had LRMs were identified. Patient and respiratory parameters were recorded. RESULTS: Ten infants, median GA 25+6 (IQR 24+2-27+0) weeks, and 21 LRMs were identified. LRMs were performed at a median age of 26 days, with a starting MAP of 16 (14-17) cm H2O and the highest MAP of 23.5 (22.0-24.8) cm H2O. Most (76%) resulted in immediate improved SpO2/FiO2. There were no sustained differences in median oxygen saturation index (8.4 vs. 9, p = 0.09), SpO2/FiO2 (1.8 vs. 1.8, p = 0.8), ∆P (21 vs. 23, p = 0.64), or transcutaneous CO2 (58 vs. 60, p = 0.84) in 24 h before and after LRMs. CONCLUSIONS: In preterm infants with evolving bronchopulmonary dysplasia, LRMs on HFO-VG did not result in sustained improvement to oxygenation or ventilation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".