ArticleJournal of robotic surgery2026
Robot-assisted total knee arthroplasty: adverse events related to the robotic system.
Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Robotic-assisted total knee arthroplasty in post-traumatic and previously operated knees with retained hardware: Practical decision-making workflow.Journal of robotic surgery · 2026Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Robot-assisted total knee arthroplasty (RA-TKA) aims to enhance surgical precision and reproducibility. However, technical malfunctions occasionally occur. This study analyses single-centre RA-TKA malfunction cases to explore causative factors and reflect on the relationship between surgeons and robotic assistance. A retrospective analysis was conducted on 188 consecutive RA-TKA procedures performed between January 2020 and June 2025 by the same senior arthroplasty consultant using five distinct robotic systems (Brainlab template-guided, HURWA automated alignment, Smith & Nephew CORI milling-drilling, BoneSage automated alignment, and Jianjia template-guided). Cases meeting predefined ‘malfunction’ criteria. Malfunction defined as: inability to complete critical steps according to the robot’s predetermined plan due to any cause, necessitating intraoperative abandonment of robotic assistance or major plan adjustments; or direct robot-related factors causing poor postoperative alignment (mechanical axis deviation > 3°) or abnormal soft tissue balance requiring early intervention. Systematic classification and statistical analysis of malfunction causes. Seventeen malfunction cases were categorised into three primary groups: (1) Robot malfunction (3 cases, 17.6%): intraoperative robotic system failure; (2) Technical malfunction (7 cases, 41.2%): loosening of positioning/reference frame (5 cases), misplacement of calibrator in osteotomy zone (2 cases); (3) Workflow and learning curve issues (2 cases, 11.8%): significant time prolongation and subsequent abandonment due to unfamiliarity with specific new system procedures (2 cases); (4) Conflict between surgeon decision-making and robotic planning (5 cases, 29.4%): surgeons performed unplanned mobilisation or osteotomy adjustments based on experience, ultimately resulting in failure to achieve anticipated balance/alignment. The success of RA-TKA relies on a reliable platform, standardised procedures, and human-machine collaboration. Clinical observations from 188 cases revealed: (1) 17 cases (9.0%) experienced robot-related malfunctions; (2) Different robotic systems exhibited distinct failure modes; (3) Malfunction rates were higher during the early learning curve phase; (4) All malfunctions were resolved through surgeon intervention without causing surgical failure. This indicates that technical malfunctions can be progressively mitigated through system optimisation and training, while intraoperative human-machine coordination and stepwise verification remain critical for surgical safety.
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