Warm-up in a Virtual Reality Environment Improves Performance in the Operating Room
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Bibliographic record
Abstract
In Brief Objective: To assess the impact of warm-up on laparoscopic performance in the operating room (OR). Background: Implementation of simulation-based training into clinical practice remains limited despite evidence to show that the improvement in skills is transferred to the OR. The aim of this study was to evaluate the impact of a short virtual reality warm-up training program on laparoscopic performance in the OP. Methods: Sixteen Laparoscopic Cholecystectomies were performed by 8 surgeons in the OR. Participants were randomized to a group which received a preprocedure warm-up using a virtual reality simulator and no warm-up group. After the initial laparoscopic cholecystectomy all surgeons served as their own controls by performing another procedure with or without preoperative warm-up. All OR procedures were videotaped and assessed by 2 independent observers using the generic OSATS global rating scale (from 7 to 35). Results: There was significantly better surgical performance on the laparoscopic Cholecystectomy following preoperative warm-up, median 28.5 (range = 18.5–32.0) versus median 19.25 (range = 15–31.5), P = 0.042. The results demonstrated excellent reliability of the assessment tool used (Cronbach's α = 0.92). Conclusion: This study showed a significant beneficial impact of warm-up on laparoscopic performance in the OP. The suggested program is short, easy to perform, and therefore realistic to implement in the daily life in a busy surgical department. This will potentially improve the procedural outcome and contribute to improved patient safety and better utilization of OR resources. This study evaluates the impact of warm-up in a virtual reality environment on performance in the operating room. Results suggest that a short period of warm-up (15 minutes) does improve the quality of technical performance. Further studies should replicate this finding for other procedures and determine the effects of warm-up on nontechnical performance and patient outcomes.
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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 | 0.002 | 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 it