A Comparison of the Forces Applied to a Manikin during Laryngoscopy with the Glidescope <sup>®</sup> and Macintosh Laryngoscopes
Bibliographic record
Abstract
The force applied during laryngoscopy can cause local tissue trauma and can induce cardiovascular responses and cervical spine movement in susceptible patients. Previous studies have identified numerous operator and patient factors that influence the amount of force applied during intubation. There are few studies evaluating the effect of different laryngoscope blades and no study involving video laryngoscopes. In this study we measured the forces using two laryngoscopic techniques. Three FlexiForce Sensors (A201-25, Tekscan, Boston, MA, USA) were attached to the concave blade surface of a Macintosh and a GlideScope laryngoscope. Experienced anaesthetists performed Macintosh and GlideScope intubations on the Laerdal Airway Management Trainer manikin. Compared to Macintosh intubations, the GlideScope intubations had equal or superior views of the glottis with 55%, 58% and 66% lower median peak, average and impulse forces applied to the tongue base. The distal sensor registered the most force in both devices and the force distribution pattern was similar between the devices. The findings suggest that the GlideScope requires less force for similar or better laryngoscopic views, at least in a manikin model.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".