Performances and limits of Bag-Valve-Device for pre-oxygenation and manual ventilation: A comparative bench and cadaver study
Bibliographic record
Abstract
Introduction Bag-Valve-Device (BVD) is the most frequently used device for pre-oxygenation and ventilation during cardiopulmonary resuscitation (CPR). A minimal expired fraction of oxygen (FeO 2 ) above 0.85 is recommended during pre-oxygenation while insufflated volume (VTi) should be reduced during manual ventilation. The objective was to compare the performances of different BVD in simulated conditions. Methods Nine BVD were evaluated during pre-oxygenation: spontaneous breathing patients were simulated on a test lung (mild and severe conditions). FeO 2 was measured with and without positive end-expiratory pressure (PEEP). CO 2 rebreathing was evaluated. Then, manual ventilation was performed by 36 caregivers ( n = 36) from three hospitals on a specific manikin; same procedure was repeated by 3 caregivers ( n = 3) on two human cadavers with three of the nine BVD: In non-CPR scenario and during mechanical CPR with Interrupted Chest Compressions strategy (30:2). Results Pre-oxygenation: FeO 2 was lower than 0.85 for three BVD in severe condition and for two BVD in mild condition. FeO 2 was higher than 0.85 in eight of nine BVD with an additional PEEP valve (PEEP 5 cmH 2 O). One BVD induced CO 2 rebreathing. Manual ventilation: For non-CPR manual ventilation, mean VTi was within the predefined lung protective range (4–8 mL/kg PBW) for all BVD on the bench. For CPR manual ventilation, mean VTi was above the range for three BVD on the bench. Similar results were observed on cadavers. Conclusions Several BVD did not reach the FeO 2 required during pre-oxygenation. Manual ventilation was significantly less protective in three BVD. These observations are related to the different BVD working principles.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".