Impact of extended reality on robot-assisted surgery training: a systematic review and meta-analysis

扩展现实技术对机器人辅助手术训练的影响:系统评价和荟萃分析

阅读:1

Abstract

Robot-assisted surgeries (RAS) have an extremely steep learning curve. Because of this, surgeons have created many methods to practice RAS outside the operating room. These training models usually include animal or plastic models; however, extended reality simulators have recently been introduced into surgical training programs. This systematic review and meta-analysis was conducted to determine if extended reality simulators can improve the performance of robotic novices and how their performance compares to the conventional training of surgeons on surgical robots. Using the PRISMA 2020 guidelines, a systematic review was performed searching PubMed, Embase, Web of Science, and Cochrane library for studies that compared the performance of robotic novices that received no additional training, trained with extended reality, or trained with inanimate physical simulators (conventional additional training). Articles that gauged performance using GEARS or time to complete measurements were included, while articles that did not make this comparison were excluded. A meta-analysis was performed on the 15 studies found using SPSS to compare the performance outcomes of the novices after training. Robotic novices trained with extended reality simulators showed a statistically significant improvement in time to complete (Cohen's d = -0.95, p = 0.02) compared to those with no additional training. Extended reality training also showed no statistically significant difference in performance in time to complete (Cohen's d = 0.65, p = 0.14) or GEARS scores (Cohen's d = -0.093, p = 0.34) compared to robotic novices trained with conventional models. This meta-analysis seeks to determine if extended reality simulators translate complex skills to surgeons in a low-cost and low-risk environment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。