Reducing edge loading and alignment outliers with image-free robotic-assisted unicompartmental knee arthroplasty: a case controlled study

Author:

Lau Wai Hong,Liu Wai Kiu Thomas,Chiu Kwong Yuen,Cheung Man Hong,Cheung Amy,Chan Ping Keung,Chan Vincent Wai Kwan,Fu HenryORCID

Abstract

Abstract Background Survivorship of medial unicompartmental knee arthroplasty (UKA) is technique-dependent. Correct femoral-tibial component positioning associates with improved survivorship. Image-free robotic-assisted unicompartmental knee arthroplasty enables preoperative and intraoperative planning of alignment and assessment of positioning prior to execution. This study aimed to compare the radiological outcomes between robotic-assisted UKA (R-UKA) and conventional UKA (C-UKA). Methods This retrospective case control study involved 140 UKA (82 C-UKA and 58 R-UKA) performed at an academic institution between March 2016 to November 2020, with a mean follow-up of 3 years. Postoperative radiographs were evaluated for mechanical axis and femoral-tibial component position. Component position was measured by two methods: (1) femoral-tibial component contact point with reference to four medial-to-lateral quadrants of the tibial tray and (2) femoral-tibial component contact point deviation from the center of the tibial tray as a percentage of the tibial tray width. Baseline demographics and complications were recorded. Results There was a higher mean component deviation in C-UKA compared with R-UKA using method 2 (17.2% vs. 12.8%; P = 0.007), but no difference in proportion of zonal outliers using method 1 (4 outliers in C-UKA, 5.1% vs. 1 outlier in R-UKA, 1.8%; P = 0.403). R-UKA showed no difference in mean mechanical alignment (C-UKA 5° vs. R-UKA 5°; P = 0.250). 2-year survivorship was 99% for C-UKA and 97% for R-UKA. Mean operative time was 18 min longer for R-UKA (P < 0.001). Conclusion Image-free robotic-assisted UKA had improved component medio-lateral alignment compared with conventional technique.

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3