Objective: To compare user performance of four fundamental inanimate robotic skills tasks (FIRST) as well as eight da Vinci Skills Simulator (dVSS) virtual reality tasks with intra-operative performance (concurrent validity) during robot-assisted radical prostatectomy (RARP) and to show that a positive correlation exists between simulation and intra-operative performance.
Materials And Methods: A total of 21 urological surgeons with varying robotic experience were enrolled. Demographics were captured using a standardized questionnaire. User performance was assessed concurrently in simulated (FIRST exercises and dVSS tasks) and clinical environments (endopelvic dissection during RARP). Intra-operative robotic clinical performance was scored using the previously validated six-metric Global Evaluative Assessment of Robotic Skills (GEARS) tool. The relationship between simulator and clinical performance was evaluated using Spearman's rank correlation.
Results: Performance was assessed in 17 trainees and four expert robotic surgeons with a median (range) number of previous robotic cases (as primary surgeon) of 0 (0-55) and 117 (58-600), respectively (P = 0.001). Collectively, the overall FIRST (ρ = 0.833, P < 0.001) and dVSS (ρ = 0.805, P < 0.001) simulation scores correlated highly with GEARS performance score. Each individual FIRST and dVSS task score also demonstrated a significant correlation with intra-operative performance, with the exception of Energy Switcher 1 exercise (P = 0.063).
Conclusions: This is the first study to show a significant relationship between simulated robotic performance and robotic clinical performance. Findings support implementation of these robotic training tools in a standardized robotic training curriculum.
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http://dx.doi.org/10.1111/bju.13511 | DOI Listing |
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January 2025
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School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Buk-gu, Gwangju 61005, Republic of Korea.
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November 2024
College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
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November 2024
Department of Electronic Engineering, Tsinghua University, 100084 Beijing, China.
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