Improving Residency Training in Arthroscopic Knee Surgery with Use of a Virtual-Reality Simulator
Bibliographic record
Abstract
BACKGROUND: There is a paucity of articles in the surgical literature demonstrating transfer validity (transfer of training). The purpose of this study was to assess whether skills learned on the ArthroSim virtual-reality arthroscopic knee simulator transferred to greater skill levels in the operating room. METHODS: Postgraduate year-3 orthopaedic residents were randomized into simulator-trained and control groups at seven academic institutions. The experimental group trained on the simulator, performing a knee diagnostic arthroscopy procedure to a predetermined proficiency level based on the average proficiency of five community-based orthopaedic surgeons performing the same procedure on the simulator. The residents in the control group continued their institution-specific orthopaedic education and training. Both groups then performed a diagnostic knee arthroscopy procedure on a live patient. Video recordings of the arthroscopic surgery were analyzed by five pairs of expert arthroscopic surgeons blinded to the identity of the residents. A proprietary global rating scale and a procedural checklist, which included visualization and probing scales, were used for rating. RESULTS: Forty-eight (89%) of the fifty-four postgraduate year-3 residents from seven academic institutions completed the study. The simulator-trained group averaged eleven hours of training on the simulator to reach proficiency. The simulator-trained group performed significantly better when rated according to our procedural checklist (p = 0.031), including probing skills (p = 0.016) but not visualization skills (p = 0.34), compared with the control group. The procedural checklist weighted probing skills double the weight of visualization skills. The global rating scale failed to reach significance (p = 0.061) because of one extreme outlier. The duration of the procedure was not significant. This lack of a significant difference seemed to be related to the fact that residents in the control group were less thorough, which shortened their time to completion of the arthroscopic procedure. CONCLUSIONS: We have demonstrated transfer validity (transfer of training) that residents trained to proficiency on a high-fidelity realistic virtual-reality arthroscopic knee simulator showed a greater skill level in the operating room compared with the control group. CLINICAL RELEVANCE: We believe that the results of our study will stimulate residency program directors to incorporate surgical simulation into the core curriculum of their residency programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".