Positive‐pressure ventilation during transport: a randomized crossover study of self‐inflating and flow‐inflating resuscitators in a simulation model
Bibliographic record
Abstract
BACKGROUND: Positive-pressure ventilation during transport of intubated patients is generally delivered via a hand-pressurized device. Of these devices, self-inflating resuscitators (SIR) and flow-inflating resuscitators (FIR) constitute the two major types used. Selection of a particular device for transport, however, remains largely an institutional practice. OBJECTIVE: To evaluate the hypothesis that transport ventilation goals of intubated pediatric patients are better achieved using an FIR compared to an SIR. METHODS: This randomized crossover simulation study compared the performance of SIR and FIR among anesthesia providers in a pediatric transport scenario. Subjects hand-ventilated a test lung while simultaneously maneuvering a stretcher bed to simulate patient transport. Hand ventilation was carried out using a Jackson-Rees circuit (FIR) and a Laerdal pediatric silicone resuscitator (SIR). The primary outcome was the proportion of total breaths delivered within the predefined target PIP/PEEP range (30+/- 3, 10+/- 3 cm H2O). Secondary outcomes included proportion of total breaths delivered with operationally defined unacceptable breath variables (PIP > 35 cm H2O or PEEP < 5 cm H2O). RESULTS: Overall, participants were four times more likely to deliver target breaths and one-third less likely to deliver unacceptable breaths using the FIR compared to the SIR. When comparing device performance, a 44% increase in the proportions of target breaths and a 40.4% decrease in unacceptable breaths using the FIR were observed (P < 0.0001 for both). CONCLUSIONS: Hand ventilation during patient transport is superior using the FIR compared to the SIR to achieve target ventilatory goals and avoid unacceptable ventilatory cycles.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".