Video Laryngoscope Intubation With an Aerosol Barrier Device: A Randomized Sequential Crossover Pilot Study
Bibliographic record
Abstract
Objectives: To assess the impact of the use of aerosol barrier device, Splashguard-CG, on the endotracheal intubation with different types of laryngoscope. Design: A pilot randomized sequential crossover simulation study. Setting: A single academic center in Japan. Subjects: Physicians in a single academic university hospital in Japan. Interventions: Use of Splashguard-CG. Measurements and Main Results: All participants were asked to perform endotracheal intubation to a manikin simulator using three different devices (Macintosh laryngoscope; Airway Scope [Nihon Kohden, Tokyo, Japan]; and McGRATH MAC [Aircraft Medical, Edinburgh, United Kingdom]) with and without Splashguard-CG in place, which required a total of six attempts and measured the intubation time as the primary outcome. Thirty physicians (15 experienced physicians and 15 less-experienced physicians) were included. Intubation time using Macintosh laryngoscope was significantly longer in the group with Macintosh laryngoscope and Splashguard-CG compared with the group without Splashguard-CG by the median difference of 4.3 seconds (interquartile range, 2.6–7.4 s; p < 0.001). There was no significant increase in the intubation time with or without Splashguard-CG for the Airway Scope (0.6 s; interquartile range, –3.7 to 3.2 s; p = 0.97) and the McGRATH MAC (0.5 s; interquartile range, –1.4 to 4.6 s; p = 0.09). This trend was found in both the experienced and less-experienced groups. We observed significant increases of subjective difficulty of the endotracheal intubation evaluated by using a Visual Analog Scale in the Splashguard-CG groups for all three types of devices. Conclusions: The use of a video laryngoscope with an aerosol barrier device does not impact the time required endotracheal intubation in a simulation environment. This method can be considered as airway management for coronavirus disease 2019.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".