Airway Management with Leksell Frame in situ with or without Frontal Bar: A Mannequin Study
Bibliographic record
Abstract
ABSTRACT: Background: The use of stereotactic headframes for neurosurgical procedures requiring targeted localization continues to grow with new advancements in technology and treatment modalities. A configuration of the Leksell stereotactic G frame with a straight front bar, useful in epilepsy and laser cases, almost completely obscures oral access and presents a significant airway challenge for the anesthetist. Although previous papers have suggested that the entire headframe should be removed during an airway emergency, we describe a novel method to remove only the front bar. Methods: We performed an observational mannequin study. Anesthesia personnel from a single center were asked to intubate a mannequin with the Leksell frame fully in situ and again with the front bar removed. In addition, the time to remove the entire frame versus only the front bar was investigated. Results: Eighteen anesthesia personnel participated in the study as well as four neurosurgeons. The average time to intubate the mannequin in the frame was 23.5 (11.4) seconds and with the front bar removed, 10.9 (2.5) seconds (p < 0.001). The average time taken to remove just the front bar by the neurosurgeons was 35.4 (7.3) seconds compared to an average of 83.3 (18.6) seconds to remove the headframe entirely (p < 0.001). Conclusion: Our study demonstrates that intubating with the Leksell front bar in situ is possible with videolaryngoscopy under an ideal situation. More importantly, the removal of just the front bar is a simpler more streamlined approach requiring statistically less time to secure an airway.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".