Tomescu Horia, Avram George M, Pacchiarotti Giacomo, Elsheikh Randa, Russu Octav, Nowakowski Andrej M, Hirschmann Michael T, Predescu Vlad
Faculty of General Medicine, Carol Davila University of Medicine and Pharmacy, Bulevardul Eroii Sanitari Numarul 8, Sector 5, 050474 Bucuresti, Romania.
Department of Orthopedic Surgery and Traumatology, Kantonsspital Baselland, 4101 Bruderholz, Switzerland.
J Clin Med. 2025 Aug 25;14(17):5996. doi: 10.3390/jcm14175996.
: Robotic-assisted unicompartmental knee arthroplasty (UKA) enhances the precision of component alignment compared to conventional techniques. Although various robotic systems exist, direct comparisons assessing their relative clinical performance remain limited. The purpose of this study is to provide a comparison between image-based and imageless robotic UKA. : A systematic review was conducted in accordance with PRISMA guidelines. Five databases were searched: PubMed (via MEDLINE), Epistemonikos, Cochrane Library, Web of Science, and Scopus. Inclusion criteria were (1) studies comparing rUKA and cUKA with radiologic parameters and revision rates (prospective or retrospective), (2) human subjects, (3) meta-analyses for cross-referencing, and (4) English language. Data collected included (1) pre- and postoperative radiologic parameters, (2) radiologic outliers, and (3) revisions and their causes. A random-effects meta-analysis was employed to enable a generalizable comparison. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated for continuous variables, and log odds ratios (LORs) with 95% CIs for binary outcomes. : Image-based robotic UKA was associated with fewer joint line height outliers (LOR = 3.5, 95% CI: 0.69-6.30, = 0.015) using a 2° threshold. HKA outliers (thresholds 2-3°) were also reduced (LOR = 0.6, 95% CI: 0.09-1.19, = 0.024). Posterior tibial and posterior femoral implant fit were significantly lower with image-based systems (LOR = 1.7, 95% CI: 1.37-2.03, respectively, LOR = 1.7, 95% CI: 1.29-1.91; < 0.001 for both). No significant differences in revision rates were observed. : Image-based robotic systems may result in fewer outliers in key radiologic parameters, including hip-knee angle, joint-line height, posterior tibial, and posterior femoral fit, though reporting remains highly heterogeneous.
与传统技术相比，机器人辅助单髁膝关节置换术（UKA）提高了假体对线的精度。尽管存在各种机器人系统，但评估它们相对临床性能的直接比较仍然有限。本研究的目的是对基于图像和无图像的机器人UKA进行比较。
按照PRISMA指南进行了系统评价。检索了五个数据库：PubMed（通过MEDLINE）、Epistemonikos、Cochrane图书馆、科学网和Scopus。纳入标准为：（1）比较机器人辅助UKA（rUKA）和传统UKA（cUKA）的放射学参数和翻修率的研究（前瞻性或回顾性）；（2）人类受试者；（3）用于交叉引用的荟萃分析；（4）英文文献。收集的数据包括：（1）术前和术后放射学参数；（2）放射学异常值；（3）翻修及其原因。采用随机效应荟萃分析进行可推广的比较。连续变量计算95%置信区间（CI）的平均差（MD），二元结局计算95%CI的对数比值比（LOR）。
使用2°阈值时，基于图像的机器人UKA关节线高度异常值较少（LOR = 3.5，95%CI：0.69 - 6.30，P = 0.015）。髋膝角（HKA）异常值（阈值2 - 3°）也减少了（LOR = 0.6，95%CI：0.09 - 1.19，P = 0.024）。基于图像的系统中胫骨后和股骨后假体匹配度显著更低（LOR分别为1.7，95%CI：1.37 - 2.03；LOR为1.7，95%CI：1.29 - 1.91；两者P均<0.001）。翻修率未观察到显著差异。
基于图像的机器人系统可能会使包括髋膝角、关节线高度、胫骨后和股骨后匹配度等关键放射学参数的异常值减少，尽管报告的异质性仍然很高。
