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Do image-based robotic TKR systems improve...
Journal article

Do image-based robotic TKR systems improve radiological or clinical outcomes compared to image-free systems? A systematic review and meta-analysis

Abstract

Robotic total knee replacement (TKR) systems improve the precision of implant positioning. They can either be image-based(IB) or image-free(IF), and each has a different pre-operative imaging requirement and workflow. The primary aim of this systematic review and meta-analysis is to compare the differences in post-operative radiographic alignment and implant position between IB and IF systems. The secondary aim is to compare patient-reported outcome measures(PROMs) and complications between IB and IF systems. A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. Studies reporting on implant position, radiological alignment, clinical outcomes or complications between IB and IF robotic knee systems were included. The studies were assessed using the Methodical Index for Non-Randomised Studies (MINORS) tool. Five studies fulfilled the inclusion criteria. There was no significant difference in outlier rates between IB and IF systems for femoral coronal alignment 6.8% vs. 2.6% [OR 2.00, (95% CI 0.81 to 4.96)], tibial coronal alignment 3.4% vs. 2.1% [OR 1.49, (95% CI 0.57 to 3.89)], posterior tibial slope 23.5% vs. 4.4% [OR 2.90, (95% CI 0.11 to 73.49)], HKA 4.8% vs. 2.5% [OR 1.38, (95% CI 0.19 to 9.81)] between the two groups. There was no significant difference in complication rate between IB and IF groups, 7.6% vs. 3.0% [OR 2.53, (95% CI 0.86 to 7.42)]. No studies reported improved PROMs between IB and IF robotic TKR systems. The mean MINORS score for comparative studies was 16.8 (Range 15–19). This meta-analysis did not find evidence of any improvement in radiological, clinical or PROMs outcomes in IB systems compared to IF systems. Further randomised controlled trials are required to assess the superiority of either system as the current evidence base is small with heterogenous measurement methodologies.

Authors

Saeed AZ; Faraz A; Davies PSE; Ahmed U; Aslam N; Meena A; de SA D; Malik SS

Journal

Journal of Robotic Surgery, Vol. 20, No. 1,

Publisher

Springer Nature

Publication Date

December 1, 2026

DOI

10.1007/s11701-025-03005-w

ISSN

1863-2483

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