Prospective observational study evaluating the C-MAC Video Stylet for awake tracheal intubation: a single-center study
Bibliographic record
Abstract
BACKGROUND: The gold standard for management of known or predicted difficult airways is awake tracheal intubation. The newly developed C-MAC Video Stylet promises to combine the advantages of rigid stylets and flexible optical scopes. We therefore evaluated the feasibility of awake orotracheal intubations with this device. METHODS: In this prospective observational study, three anesthesiologists experienced in advanced airway management performed each 12 awake oral intubations with this device on adult patients with known or predicted intubation difficulties. The primary outcome was overall intubation success. Secondary outcomes were total attempts, successful time, first postoperative day sequelae, and subjective intubation difficulty rated on a visual analogue scale (1, very easy; 10, extremely difficult). RESULTS: , were enrolled in the study. ASA status II, III, IV were eight (22%), 23 (64%), and five (14%), respectively. Indications for awake oral intubation were: oropharyngeal tumor 20 (56%), cervical-spine fracture eight (22%), previously known difficult airway four (11%), spinal canal stenosis three (8%), and bilateral peritonsillar abscess one (3%). Overall, 97% were successfully intubated in 45 s (31-88). First-attempt success rate was 80% in 37 s (29-54); 92% of patients would choose the same procedure again. On the first postoperative day, 11 (31%) patients complained of sore throat; five (14%) had minor injuries. Ease of intubation was rated as median VAS 3 (IQR: 1-7). CONCLUSIONS: The new C-MAC Video Stylet has the potential to serve as a suitable device for visualized oral awake intubation in difficult airway situations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".