Feasibility of bubble non-invasive positive pressure ventilation, a first-in-human study
Bibliographic record
Abstract
PURPOSE: Infant respiratory distress is a significant cause of mortality globally. Bubble continuous positive airway pressure (CPAP) is a simple and effective therapy, but sicker infants may require additional support such as non-invasive positive-pressure ventilation (NIPPV). We investigated the feasibility of a simple, low-cost, non-electric bubble NIPPV device. METHODS: In this cross-over feasibility study, seven newborns with moderate respiratory distress (Downes score ≥ 3), weight > 1500 g and gestational age > 32 weeks were randomized to 4 h of treatment with bubble CPAP (5-8 cm H2O) vs. bubble NIPPV (Phigh 8-10 cm H2O/Plow 5-8 cm H2O) followed by 4 h of the alternate treatment. Treatment order (CPAP vs. NIPPV) was randomized. Outcome measures included hourly vital signs, Downes score and O2 saturation. Adverse events including pneumothorax, nasal septal necrosis, necrotizing enterocolitis and death before discharge were also recorded. RESULTS: It took nurses 39 (7.3) s to assemble the bubble NIPPV device. Patients had similar vital signs and Downes scores on both treatments; median (IQR) values on bubble CPAP vs. bubble NIPPV were: heart rate 140 (134.5, 144), 140 (134.5, 144); respiratory rate 70 (56, 80), 65 (58, 82), Downes score 4 (3, 5.75), 4 (3, 5), O2 96 (94, 98), 97 (96, 98). All newborns survived to discharge and there were no adverse events. . CONCLUSIONS: A simple, low-cost, non-electric method of providing NIPPV for newborns with respiratory distress is feasible in limited resource settings. Randomized-controlled trials comparing bubble CPAP and bubble NIPPV are justified.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".