A Prospective Assessment of Knee Arthroscopy Skills Between Medical Students and Residents—Simulator Exercises for Partial Meniscectomy and Analysis of Learning Curves
Background The Covid-19 pandemic has created the largest disruption of education in history. In a response to this, we aimed to evaluate the knee arthroscopy learning curve among medical students and orthopaedic residents. Methods An arthroscopy simulator was used to compare the learning curves of t...
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Veröffentlicht in: | Surgical innovation 2022-06, Vol.29 (3), p.398-405 |
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Sprache: | eng |
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Zusammenfassung: | Background
The Covid-19 pandemic has created the largest disruption of education in history. In a response to this, we aimed to evaluate the knee arthroscopy learning curve among medical students and orthopaedic residents.
Methods
An arthroscopy simulator was used to compare the learning curves of two groups. Medical students with any prior knowledge of arthroscopy (n=24) were compared to a residents group (n=16). Analyzed parameters were “time to complete a task,” assessment of the movement of tools and values scoring damage to the surrounding tissues.
Results
After several repetitions, both groups improved their skills in terms of time and movement. Residents were on average faster, had less camera movement, and touched the cartilage tissue less often than did students. Students showed a steeper improvement curve than residents for certain parameters, as they started from a different experience level.
Conclusion
The participants were able to reduce the time to complete a task. There was also a decrease in possible damage to the virtual surrounding tissues. In general, the residents had better mean values, but the students had the steeper learning curve. Particularly less experienced surgeons can especially train their hand–eye coordination skills required for arthroscopy surgery. Training simulators are an important training tool that supplements cadaveric training and participation in arthroscopic operations and should be included in training. |
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ISSN: | 1553-3506 1553-3514 |
DOI: | 10.1177/15533506211037792 |