Learning fibreoptic intubation with a virtual computer program transfers to ‘hands on’ improvement
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Fibreoptic intubation is an essential skill in anaesthesiology that is challenging to learn in the clinical setting. The goal of this study was to evaluate 'virtual fibreoptic intubation' (VFI) software as an adjunct to the traditional fibreoptic intubation teaching. METHODS: After informed consent, 42 undergraduate medical students were randomized into two groups. The 'control group' was taught conventionally by an expert bronchoscopist with a 1 h lecture. In addition to the didactic lecture by the expert, the 'VFI group' was given the VFI CD-ROM, and students self-trained with the software until they felt competent performing a virtual fibreoptic bronchoscopy on the normal patient models. Students were evaluated 2 weeks later on their first orotracheal fibreoptic intubation of an airway manikin. The primary endpoint was success, as evaluated by a staff anaesthesiologist blinded to the group of teaching. Fibreoptic intubation ability was the secondary endpoint. RESULTS: The fibreoptic intubation success rate was significantly higher in the VFI group than in the control group (81 versus 52%, P < 0.05). Among 10 failures in the control group, nine were due to oesophageal intubation as compared with only one out of four in the VFI group. Among four failures in the VFI group, three were because of taking longer than 4 min as compared with only one out of 10 in the control group. The VFI group tended towards better ability in the procedural skills of fibreoptic intubation than the control group. CONCLUSION: Self-training in fibreoptic intubation with the VFI software may improve the acquisition of fibreoptic intubation skills.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Non-randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".