A Virtual Reality Simulation Model of Spinal Ultrasound
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Ultrasound assessment of the lumbar spine improves the success of spinal and epidural anesthesia, especially for patients with underlying difficult anatomy. To assist with the teaching and learning of ultrasound-guided neuraxial anesthesia, we have created an online interactive educational model (http://www.usra.ca/vspine.php and http://pie.med.utoronto.ca/vspine). The aim of the current study was to determine whether the virtual spine model improved the knowledge of neuraxial anatomy and sonoanatomy. METHODS: After obtaining ethics board approval and written participant consent, 14 anesthesia trainees with no prior experience with spine ultrasound imaging were included in this study. Construct validity was assessed using a pretest/posttest design to measure the knowledge acquired from self-study of the virtual spine simulation modules. Two tests (A and B) with 20 multiple-choice questions were used either for the pretest or posttest, at random in order to account for possible differences in difficulty between the 2 tests. These tests were administered immediately before and after a 1-hour training session using the spine ultrasound model. RESULTS: Fourteen anesthesia trainees completed the study. Seven used test A as the pretest (group A), and 7 used test B as the pretest (group B). Both groups showed a statistically significant improvement (P < 0.05) in test scores after a 1-hour session with the spine ultrasound model. The mean scores were 55% (SD, 11.2%) on the pretest and 77% (SD, 8.7%) on the posttest. CONCLUSIONS: The study demonstrated that after 1 hour of self-study by the trainees on the spine ultrasound model test scores improved by 40%.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".