Use of a Low-fidelity simulator to improve trans-nasal fibre-optic flexible laryngoscopy in the clinical setting: A randomized, single-blinded, prospective study
Bibliographic record
Abstract
BACKGROUND: Trans-nasal flexible fibre-optic laryngoscopy (TFFL) is an essential skill for otolaryngologists. There is evidence to suggest that simulators help residents acquire procedural skills. The objective of this study was to examine the effect of simulation on endoscopy skill acquistion. METHODS: A randomized controlled trial was conducted utilizing medical students and junior residents with limited experience in TFFL. Learners all performed a baseline endoscopy and were then randomized to receive either 45 minutes of simulation training or not. Following this, a second endoscopy was performed. Time to adequate visualization of the glottis, the percentage of time adequate visualization of the airway was maintained, and the number of collisions with mucosa were analyzed. Qualitative assessments were also obtained from the learner, patient, and staff laryngologist. RESULTS: Time to adequate visualization of the glottis and the number of mucosal collisions were significantly less during the second endoscopy, irrespective of the use of simulation (84.8 sec vs. 68 sec, p < 0.01; 5.0 vs. 3.2, p < 0.01, respectively). Analysis using a two-way ANOVA with interaction established that none of the quantitative measures analyzed in this study improved with the addition of simulation. CONCLUSION: Improvements in time to visualization of the glottis and number of mucosal contacts were seen between the first and second endoscopy irrespective of simulator use. No additional benefit was conferred with the use of a low-fidelity simulator.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".