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.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".