Raising the awareness for insufficient oxygen delivery from self-inflating resuscitation bags lacking expiratory valve during preoxygenation
Bibliographic record
Abstract
We recently read an interesting study which demonstrated that self-inflating resuscitation bag (SIRB) lacking expiratory valve has unreliable performance in oxygen delivery during spontaneous breathing mimicked by mechanical lung simulator. It was postulated that the absence of an expiratory valve and the resulting air entrainment via the exhaust port accounts for the poor oxygen delivery performance. The current disposable SIRB in-use in our institutions (Med-Rescuer Disposable BVM Resuscitator 4000, BLS Systems Limited, ON, Canada) has a duckbill valve but no expiratory valve. Safety concerns regarding its oxygen delivery performance during spontaneous breathing were raised, as this SIRB was commonly used to preoxygenate critically ill patient with potentially transmissible respiratory infection (e.g. COVID-19) before tracheal intubation. We therefore performed an experiment on this SIRB using one of us as a healthy volunteer. Our small experiment demonstrated that air entrainment could occur via the exhaust port and affect oxygen delivery performance. Our experiment also demonstrated that attaching a positive end-expiratory pressure (PEEP) valve to the exhaust port improves the oxygen delivery performance. The findings of this experiment were sent to the relevant department of our institutions for safety consideration.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".