Precision soft tissue balance in robot-assisted total knee arthroplasty: a bibliometric and visualization analysis of...

To systematically review the current research status, knowledge structure, and development trends in the fields of dynamic gap balance and soft tissue balance in robot-assisted total knee arthroplasty (RATKA), identify the core research forces, hot topics, and frontier directions, and provide evidence-based references for clinical practice and subsequent research. Based on the Web of Science Core Collection database, we retrieved relevant literature on dynamic gap regulation and soft tissue balance in RATKA published between January 2015 and May 2026. We conducted bibliometric analysis using Bibliometrix, VOSviewer, and CiteSpace, covering aspects such as annual publication volume, national/institutional/author collaboration networks, journal distribution, co-citation of documents, keyword co-occurrence and clustering, emergent themes, and reference literature explosion detection. A total of 350 articles were included, with an annual growth rate of 18.2%. The United States had the highest number of publications (113), and French institutions (especially CHU Lyon) dominated at the institutional level. Core authors included Plaskos C, Lustig S, and Batailler C, etc. There was a differentiation between high-cited authors and high-productivity author groups. The core journals were Knee Surgery Sports Traumatology Arthroscopy and "Journal of Arthroplasty. Keyword clustering identified 9 major research directions, covering personalized force lines, robot-assisted technology, soft tissue release, gap balance strategies, and clinical prognosis assessment. The emergent analysis showed that the research focus shifted from the early stage of computer-assisted navigation (2015-2018) to robot surgery, functional alignment, and kinematic assessment (2020-2026), and multiple keywords continued to explode in the past three years, indicating that this field is in a rapid evolving stage. RATKA soft tissue balance research has shifted from feasibility testing to individualized biomechanics and functional prognosis. Key challenges persist: virtual-actual gap mismatch, uncertain equivalence among balance strategies, and non-standardized workflows. Future work should prioritize multicenter cohorts, soft tissue modeling, and AI-integrated sensors to enable an "intelligent collaboration" paradigm over "assisted execution".