Self-inflating bags versus T-piece resuscitator to deliver sustained inflations in a preterm lamb model
Bibliographic record
Abstract
OBJECTIVE: In neonatal resuscitation, the use of a sustained inflation (SI) may facilitate lung aeration. Previous studies comparing different resuscitation devices have shown that one model of self-inflating bag (SIB) could not deliver an SI. We aimed to compare the delivery of an SI using four SIBs with that of a T-piece. STUDY DESIGN: In intubated preterm lambs, we compared four models of SIB fitted with a positive end expiratory pressure (PEEP) valve to a T-piece using a gas flow of 8 L/min. Four operators aimed to deliver three SIs of 20 cm H₂O for 30 s. The study was repeated with the PEEP valve removed and again with no flow. We measured duration of SI, average inflation pressure (IP) and analysed the shape of the pressure curves. RESULTS: 204 combinations were analysed. Mean (SD) duration of SI was Ambu 6(2)s, Laerdal 14(8)s, Parker Healthcare 5(1)s, Mayo Healthcare 33(2)s and T-piece 33(1)s. Mean (SD) average IP was Ambu 17(3)cm H₂O, Laerdal 17(3)cm H₂O, Parker Healthcare 12(5)cm H₂O, Mayo Healthcare 21(2)cm H₂O and T-piece 20(0)cm H₂O. Duration of SI and average IP was significantly different between SIBs (all p<0.001). The findings were substantially unchanged when PEEP valve and flow were removed (all p>0.05). Only the Mayo system delivered SIs with duration and average IP not significantly different from the T-piece (p>0.05). CONCLUSIONS: The performance of the four SIBs tested varied considerably. Some are able to deliver an SI even in the absence of gas flow. This may be useful in a resource-limited setting with no gas supply.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".