Department Orthopaedic Surgery, University Hospital Ghent, Ghent, Belgium.
Int Orthop. 2023 Feb;47(2):503-509. doi: 10.1007/s00264-022-05630-8. Epub 2022 Nov 17.
The assistance of robot technology is introduced into the operating theatre to improve the precision of a total knee arthroplasty. However, as with all new technology, new technology requires a learning curve to reach adequate proficiency. The primary aim of this study was to identify the learning curve of an imageless robotic system with standardised laxity testing. The secondary aim of this study was to evaluate the accuracy of the intra-operative coronal alignment during the learning curve.
A prospective study was performed on 30 patients undergoing robot-assisted total knee arthroplasty with an imageless robotic system (Corin, Massachusetts, USA) associated with a dedicated standardised laxity testing device. The learning curve of all surgical steps was assessed with intra-operative video monitoring. As comparison, the total surgical time of the last 30 patients receiving conventional total knee arthroplasty by the same surgeon and with the same implant was retrospectively assessed. Coronal lower limb alignment was evaluated pre- and post-operatively on standing full-leg radiographs.
CUSUM (cumulative summation) analysis has shown inflexion points in multiple steps associated with robot-assisted surgery between one and 16 cases, which indicates the progression from the learning phase to the proficiency phase. The inflexion point for total operative time occurred after nine cases. Robot-assisted total knee surgery required significantly longer operative times than the conventional counterpart, with an average increase of 22 min. Post-operative limb and implant alignment was not influenced by a learning curve.
The introduction of an imageless robotic system with standardised laxity assessment for total knee arthroplasty results in a learning curve of nine cases based on operative time. Compared to conventional surgery, the surgeon is not able to reach time neutrality with the robotic platform. There is no learning curve associated with coronal limb or implant alignment. This study enables orthopaedic surgeons to understand the implementation of this surgical system and its specific workflow into clinical practice.
将机器人技术引入手术室，以提高全膝关节置换术的精度。然而，与所有新技术一样，新技术需要一个学习曲线才能达到足够的熟练程度。本研究的主要目的是确定无图像机器人系统与标准化松弛度测试相结合的学习曲线。本研究的次要目的是评估学习曲线期间术中冠状对线的准确性。
对 30 例接受无图像机器人系统（美国马萨诸塞州科林）辅助全膝关节置换术的患者进行前瞻性研究，该系统与专用标准化松弛度测试设备相关联。通过术中视频监测评估所有手术步骤的学习曲线。作为比较，回顾性评估了同一位外科医生和相同植入物接受传统全膝关节置换术的最后 30 例患者的总手术时间。术前和术后站立全长下肢正位片评估冠状下肢对线。
CUSUM（累积和）分析显示，机器人辅助手术的多个步骤在 1 到 16 例之间出现拐点，这表明从学习阶段到熟练阶段的进展。总手术时间的拐点发生在 9 例之后。机器人辅助全膝关节置换术所需的手术时间明显长于传统手术，平均增加 22 分钟。术后肢体和植入物对线不受学习曲线的影响。
引入无图像机器人系统和标准化松弛度评估用于全膝关节置换术会导致基于手术时间的 9 例学习曲线。与传统手术相比，外科医生无法使用机器人平台达到时间中立性。冠状肢体或植入物对线没有学习曲线。本研究使骨科医生能够了解该手术系统及其特定工作流程在临床实践中的实施情况。
