A biomechanical comparison between robotic and conventional total knee arthroplasty (TKA) in resection accuracy: a meta-analysis on cadaveric specimens

机器人辅助全膝关节置换术(TKA)与传统全膝关节置换术在切除精度方面的生物力学比较:基于尸体标本的荟萃分析

阅读:1

Abstract

PURPOSE: Robotic total knee arthroplasty (TKA) has seen a rapid increase in utilization with recent literature suggesting that implant accuracy and resection are better optimized than in conventional TKA. The purpose of this study was to evaluate the biomechanical properties of robotic-assisted versus conventional TKA in minimizing biplanar femoral and tibial resection error in cadaveric specimens. METHODS: A systematic review and meta-analysis was performed by searching through PubMed, Cochrane library, and Embase to identify studies that analyzed the biomechanical properties of robotic assisted and conventional TKA, according to standard PRISMA guidelines. Evaluated outcomes included femoral coronal resection error (deg), femoral sagittal resection error (deg), tibial coronal resection error (deg), and tibial sagittal resection error (deg). RESULTS: Seven studies met inclusion criteria, including a total of 140 cadaveric specimens (robotic: 70, conventional: 70), for resection accuracy between robotic and conventional TKA. Pooled analysis from seven studies revealed a significant difference in femoral coronal and sagittal resection error in favor of robotic systems compared to conventional systems (p < 0.001 & p < 0.001, respectively). The pooled analysis from seven studies revealed a significant difference in tibial sagittal resection error in favor of robotic systems compared to conventional systems following TKA (p = 0.012). Posthoc power analysis revealed a power of 87.2%. CONCLUSION: The use of robotic TKA is associated with lower femoral coronal, lower femoral sagittal and tibial sagittal resection error compared to conventional TKA. It should be noted that these findings are purely biomechanical - surgeons should interpret these findings along with clinical differences between conventional and robotic systems to determine which system is best for each patient.

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。