Observational analysis of criteria for a difficult airway alert
Bibliographic record
Abstract
Introduction: Difficult airway alerts are a tool used to document difficulties encountered with the patient’s airway and assist with future management. There is no universally accepted criterion as to who should get a difficult airway alert and the indication for these alerts may be changing with the proliferation of videolaryngoscopes. The purpose of this study was to characterize the airway events that were encountered in patients who had been assigned a difficult airway alert by staff anesthesiologists. Methods: This retrospective study analyzed the airway details of patients who were assigned a difficult airway letter at an academic teaching institution between November 2011 and January 2016. Electronic records of intraoperative airway management and difficult airway letters were reviewed for the methods used, difficulties encountered, and what recommendations were provided for future airway management. Results: A cohort of 107 adult patients (62 males and 45 females) issued difficult airway letters identified for analysis. The mean age (SD) of the cohort was 57 (±13) years, and the mean body mass index was 31 (±7) kg/m2. Direct laryngoscopy failed in 68 of 89 cases, with 77 reported grade III views and 9 grade IV views. Videolaryngoscopy (VL) was used successfully in 63 cases, with 8 documented VL failures. Ten patients were intubated awake with a flexible bronchoscope (FB), and 6 cases were managed using an asleep FB technique. The most common methods suggested for future airway management were VL (57 cases) or either awake or asleep FB (31 cases). Conclusions: Patients with difficult direct laryngoscopy were predominant in this cohort who were assigned a difficult airway alert. Many of the difficult airways were successfully managed using VL, however, FB was required in some cases. Staff preferentially recommended VL over flexible bronchoscopy for future management of the known difficult 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".