A new reservoir-based CPAP with low oxygen consumption: the Bag-CPAP
Bibliographic record
Abstract
Abstract Background Several noninvasive ventilatory supports rely in their design on high oxygen consumption which may precipitate oxygen shortage, as experienced during the COVID-19 pandemic. In this bench-to-bedside study, we assessed the performance of a new continuous positive airway pressure (CPAP) device integrating a large reservoir (“Bag-CPAP”) designed to minimize oxygen consumption, and compared it with other CPAP devices. Methods First, a bench study compared the performances of Bag-CPAP and four CPAP devices with an intensive care unit ventilator. Two FiO 2 targets (40–60% and 80–100%) at a predefined positive end expiratory pressure (PEEP) level between 5 and 10 cm H 2 O were tested and fraction of inspired oxygen (FiO 2 ) and oxygen consumption were measured. Device-imposed work of breathing (WOB) was also evaluated. Second, an observational clinical study evaluated the new CPAP in 20 adult patients with acute respiratory failure in two hospitals in France. Actual FiO 2 , PEEP, peripheral oxygen saturation, respiratory rate, and dyspnea score were assessed. Results All six systems tested in the bench study reached the minimal FiO 2 target of 40% and four reached at least 80% FiO 2 while maintaining PEEP in the predefined range. Device-delivered FiO 2 /consumed oxygen ratio was the highest with the new reservoir-based CPAP irrespective of FiO 2 target. WOB induced by the device was higher with Bag-CPAP. In the clinical study, Bag-CPAP was well tolerated and could reach high (> 90%) and moderate (> 50%) FiO 2 with an oxygen flow rate of 15 [15–16] and 8 [7–9] L/min, respectively. Dyspnea score improved significantly after introduction of Bag-CPAP, and SpO 2 increased. Conclusions In vitro, Bag-CPAP exhibited the highest oxygen saving properties albeit had increased WOB. It was well accepted clinically and reduced dyspnea. Bag-CPAP may be useful to treat patients with acute respiratory failure in the field, especially when facing constraints in oxygen delivery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".