Development and Testing of a Bubble Bi-Level Positive Airway Pressure System
Bibliographic record
Abstract
BACKGROUND: Neonatal respiratory distress results in > 1 million annual deaths worldwide. Bubble CPAP is a simple, effective, and widely used therapy for infants in respiratory distress. In low-resource settings, more advanced respiratory support is limited by cost, technical expertise, and sporadic electricity. We sought to develop a safe, inexpensive, and simple solution to provide further respiratory support for these infants. METHODS: A standard bubble CPAP system was modified to provide 2 levels of positive airway pressure (bi-level positive airway pressure) by attaching a novel device. To demonstrate reliability, the system was run with continuous pressure monitoring on full-term and preterm neonatal mannikins with pressure targets of 8/5 cm H 2 O and 15/5 cm H 2 O to simulate 2 different modes of noninvasive ventilation (NIV). RESULTS: At a ventilation rate set between 30 and 45 cycles/min, by adjusting the leak rate of the device, the following mean pressures ± SD were demonstrated: term mannikin low-pressure NIV, 7.9 ± 0.2/5.3 ± 0.2 cm H 2 O; term mannikin high-pressure NIV, 15.1 ± 0.1/6.1 ± 0.1 cm H 2 O; preterm mannikin low-pressure NIV, 7.9 ± 0.2/5.3 ± 0.2 cm H 2 O; preterm mannikin high-pressure NIV, 16.5 ± 0.4/5.1 ± 0.1 cm H 2 O. CONCLUSIONS: The modified bubble CPAP system reliably provided alternating pressures similar to bi-level positive airway pressure modes of respiratory support in neonatal mannikins. The dual-pressure technology is a simple, single connection add-on that can readily be applied to existing bubble CPAP systems.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 teacher head, 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".