<b>Assessment of a Virtual Interventional Simulator Trainer</b>
Bibliographic record
Abstract
PURPOSE: To assess the construct validity of the Procedicus Virtual Interventional Simulator Trainer (Procedicus-VIST) and its use as a training tool. METHODS: Two groups comprised of 8 interventional radiologists (experts) and 8 medical students (novices) performed 6 renal artery procedures on the Procedicus-VIST. All participants received a 45-minute standardized didactic introduction before starting the simulations. The first 2-hour session was used for familiarization, whereas the second session constituted the testing period. During each procedure, objective performance data including procedure time, fluoroscopic time, contrast, cine loops, lesion coverage, tool:lesion ratio, placement accuracy, and residual stenosis were recorded by the Procedicus-VIST software. Exit surveys were completed to document demographic and subjective data. A visual analogue scale (VAS) from 0 to 100 was used to rate total, guidewire, catheter, balloon, stent, fluoroscopic, and joystick realism, as well as the simulator's pedagogic value. RESULTS: There were no significant differences in performances between the 2 groups in residual stenosis, placement accuracy, procedure time, number of cine loops, lesion coverage, or tool:lesion ratio. The total fluoroscopic use was greater for the novice group (p < 0.01). Experts rated 6 of the 8 subjective parameters favorably, whereas the novice group approved of 7. CONCLUSIONS: Using this study design, the quantitative metrics recorded by the Procedicus-VIST software failed to stratify performances based upon experience level, with the exception of fluoroscopic use. Investigation comparing standard training to virtual reality training should be performed to assess any differences in actual performance in the catheterization laboratory.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".