显微外科
吻合
学习曲线
计算机科学
外科
医学
医学物理学
人工智能
物理医学与康复
操作系统
作者
Felix Strübing,Jonathan Weigel,Emre Gazyakan,Laura C. Siegwart,Charlotte Holup,Ulrich Kneser,Arne H. Boecker
出处
期刊:Life
[Multidisciplinary Digital Publishing Institute]
日期:2025-05-09
卷期号:15 (5): 763-763
被引量:3
摘要
INTRODUCTION: Mastering microsurgery requires advanced fine motor skills, hand-eye coordination, and precision, making it challenging for novices. Robot-assisted microsurgery offers benefits, such as eliminating physiological tremors and enhancing precision through motion scaling, which may potentially make learning microsurgical skills easier. MATERIALS AND METHODS: Sixteen medical students without prior microsurgical experience performed 160 anastomoses in a synthetic model. The students were randomly assigned into two cohorts, one starting with the conventional technique (HR group) and one with robotic assistance (RH group) using the Symani surgical system. RESULTS: > 0.05). DISCUSSION: This study demonstrated a steep preclinical learning curve for robot-assisted microsurgery (RAMS) among novices in a synthetic, preclinical model. No significant differences in SAMS scores between robotic and manual techniques after ten anastomoses. Robot-assisted microsurgery required more time per anastomosis, but the results suggest that experience with RAMS may aid in manual skill acquisition. The study indicates that further exploration into the sequencing of robotic and manual training could be valuable, especially in designing structured microsurgical curricula.
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