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机器人辅助膝关节置换术的学习曲线因有经验丰富的机器人辅助手术外科医生而变得平坦。

The learning curve in robotic assisted knee arthroplasty is flattened by the presence of a surgeon experienced with robotic assisted surgery.

机构信息

Department for Orthopedics and Traumatology, Kepler University Hospital GmbH, Krankenhausstrasse 9, 4020, Linz, Austria.

Johannes Kepler University Linz, Altenberger Strasse 69, 4040, Linz, Austria.

出版信息

Knee Surg Sports Traumatol Arthrosc. 2023 Mar;31(3):760-767. doi: 10.1007/s00167-022-07048-6. Epub 2022 Jul 21.

Abstract

PURPOSE

The purpose of this study was to investigate the learning curve associated with robotic assisted knee arthroplasty (RAS KA). Therefore, the evaluation of the influence of an experienced surgeon on the overall team performance of three surgeons regarding the learning curve in RAS KA was investigated. It was hypothesized that the presence of an experienced surgeon flattens the learning curve and that there was no inflection point for the learning curve of the surgical team.

METHODS

Fifty-five cases consisting of 31 total knee arthroplasties (TKA) and 24 unicompartmental arthroplasties (UKA) performed by three surgeons during 2021 were prospectively investigated. Single surgeon and team performance for operation time learning curve and inflection points were investigated using cumulative sum analysis (CUSUM).

RESULTS

A downward trend line for individual surgeons and the team performance regarding the operation time learning curve was observed. No inflexion point was observed for the overall team performance regarding TKA and UKA. The surgeon that performed all cases with the assistance of the experienced surgeon had significantly shorter surgical times than the surgeon that only occasionally received assistance from the experienced surgeon (p = 0.004 TKA; p = 0.002 UKA).

CONCLUSION

The presence of an experienced surgeon in robotically assisted knee arthroplasty can flatten the learning curve of the surgical team formerly unexperienced in robotic assisted systems. Manufacturers should provide expanded support during initial cases in centres without previous experience to robotic assisted knee arthroplasty.

LEVEL OF EVIDENCE

III.

摘要

目的

本研究旨在探讨机器人辅助膝关节置换术(RAS KA)相关的学习曲线。因此,评估了经验丰富的外科医生对三名外科医生团队整体表现的影响,以研究 RAS KA 学习曲线。研究假设,经验丰富的外科医生的存在可以使学习曲线变平,并且手术团队的学习曲线没有拐点。

方法

前瞻性研究了 2021 年期间三名外科医生完成的 55 例手术,其中包括 31 例全膝关节置换术(TKA)和 24 例单髁关节置换术(UKA)。使用累积和分析(CUSUM)对单名外科医生和团队的手术时间学习曲线和拐点的表现进行了研究。

结果

观察到个体外科医生和团队在手术时间学习曲线方面呈下降趋势。对于 TKA 和 UKA,整个团队的表现都没有观察到拐点。与偶尔接受经验丰富的外科医生协助的外科医生相比,所有手术都由经验丰富的外科医生协助的外科医生的手术时间明显更短(p=0.004 TKA;p=0.002 UKA)。

结论

在机器人辅助膝关节置换术中,有经验的外科医生的存在可以使以前没有机器人辅助系统经验的手术团队的学习曲线变平。制造商应在没有先前经验的中心提供初始病例期间提供扩展支持。

证据水平

III。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49bb/9957851/4b2f2d1138a5/167_2022_7048_Fig1_HTML.jpg

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