Volume targeted mask ventilation during simulated neonatal resuscitation – A randomized crossover manikin study
Bibliographic record
Abstract
To compare mask positive pressure ventilation (PPV) provided by pressure guided devices (i.e., T-Piece) with or without a respiratory function monitor (RFM) with ventilator-based volume-targeted ventilation (VTV) using a VN500 Draeger ventilator or the NextStep TM , a novel ventilation device designed for the delivery room. Prospective, randomized, crossover, simulation study. Following orientation to ventilation devices, participants were randomized to order of four ventilation devices (NextStep TM , VN500 Draeger ventilator, T-piece PPV with RFM visible, and T-piece PPV with RFM masked) and order of four simulation scenarios. The study was performed in a neonatal resuscitation room within a level 3 neonatal intensive care unit. Participants were trained neonatal resuscitation providers or instructors with experience as team leader. Semi-automated, ventilator-based volume-targeted mask PPV (VTV-PPV) (NextStep TM or Draeger Ventilator) was compared to manual PPV via a T-piece device (RFM either visible or masked). Primary outcome was reduction in mask leak with the NextStep TM compared to the other devices. Thirty-two healthcare professionals [25 (78.1%) were female and 7 (21.9%) were male] participated. The median (interquartile range) mask leak was significantly lower with VTV-PPV with NextStep TM [6 (1-12)%] compared to the Draeger Ventilator [24 (25-38)%, p=0.01], T-Piece with RFM [18 (9-33)%, p=0.0088], and T-Piece without RFM [32 (12-57)%, p=>0.0001]. The median (IQR) delivered tidal volume was not different between groups, although the NextStep TM had less tidal volume variation compared to all other groups and peak inflation pressure was significantly lower with VTV-PPV with NextStep TM compared to all other groups. In a neonatal manikin model, VTV-PPV with the NextStep TM using a two-hand hold reduced mask leak compared to the T-piece without RFM guidance.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".