Determining the amount of training needed for competency of anesthesia trainees in ultrasonographic identification of the cricothyroid membrane
Bibliographic record
Abstract
BACKGROUND: Airway guidelines recommend the use of ultrasound to localize the cricothyroid membrane prior to airway manipulation in difficult airways. In this study, we aimed to determine the amount of training anesthesia trainees would need to achieve competence in bedside ultrasound to identify the cricothyroid membrane. METHODS: This is a prospective non-randomized cohort study in the Department of Anesthesia at Mount Sinai Hospital (Toronto, Ontario, Canada). Following institutional ethics approval, six anesthesia trainees consisting of four residents and two fellows underwent a 2-h training session on neck ultrasound to identify neck landmarks and the cricothyroid membrane. The trainees had no previous airway ultrasound experience. One-two weeks later, each trainee performed consecutive neck ultrasound scans on 20 healthy volunteers to identify the cricothyroid membrane. Cumulative sum (CUSUM) learning curves were constructed for each trainee. Primary outcome was the number of ultrasound examinations required to achieve competence, defined as 90% success rate in a series of 20 ultrasound scans. Secondary outcomes were the overall success rate, the time (sec.) required to perform the task, and 3-month skills assessment. RESULTS: CUSUM analysis showed four trainees achieved competence with a mean [range] success rate of 94.0% [90-100%] and a median [range] number of attempts of 14 [9-18]. Two trainees did not achieve competence, but obtained a success rate of 75.0 and 80.0% each. Overall (number of attempts) success rate was 88.3% (106/120) with a mean (SD) time of 36.9 (9.0) sec. Three months after training, ultrasound of five consecutive neck scans showed a mean success rate of 86.7% (26/30) and mean (SD) time of 47.7 (16.0) sec. CONCLUSIONS: After a short 2-h training session, most anesthesia trainees (n = 4/6) achieved competence in ultrasound-identification of the cricothyroid membrane with less than 20 scans in a mean time less than 60 s., and that they remain reasonably competent 3 months later. The learning curve for ultrasound identification of the cricothyroid membrane seems to be short even without prior airway ultrasound experience.
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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 | 0.014 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".