A randomized crossover comparison of the bébé VieScope and direct laryngoscope for pediatric airway management by nurses in medical simulation settings
Bibliographic record
Abstract
BACKGROUND: Airway management in life-threatening emergencies is essential for children, and endotracheal intubation is the gold standard. It protects against regurgitation and enables mechanical ventilation. New types of airway management equipment are being developed and implemented to meet the needs of medical personnel. RESEARCH DESIGN AND METHODS: This prospective, randomized, cross-over simulation trial evaluated the success of endotracheal intubation in three scenarios: normal airway (scenario-A), tongue edema (scenario-B), and continuous chest compression (scenario-C), using the bébé Vie Scope™ laryngoscope (VieScope) and the Macintosh blade laryngoscope (MAC) as a comparative tool performed by nurses with limited tracheal intubation experience. RESULTS: The results of the study showed that in scenario-A, there were no significant differences in the first attempt success rate or endotracheal intubation time between VieScope and MAC. However, VieScope was associated with better visualization of the glottis. In scenarios B and C, VieScope was significantly more effective than MAC in terms of first-pass success rate, time to intubate, Cormack-Lehane grade, POGO score, and ease of endotracheal intubation. CONCLUSIONS: Bébé VieScope may be useful for endotracheal intubation in pediatric patients, particularly in cases of tongue edema and ongoing chest compression, providing a higher first-pass success rate than conventional laryngoscopes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".