Global evolution of robot-assisted spine surgery: a bibliometric and knowledge-mapping study (1997-2026).

Robot-assisted spine surgery has emerged as a transformative approach to spinal instrumentation, yet the global knowledge structure, collaborative landscape, and thematic evolution of this field remain incompletely characterised. This study performed a comprehensive bibliometric and knowledge-mapping analysis of robot-assisted spine surgery research from 1997 to 2026. Publications were retrieved from the Web of Science Core Collection using a predefined search strategy, and bibliometric indicators, co-authorship networks, citation patterns, keyword co-occurrence, and thematic maps were analysed using VOSviewer and CiteSpace. A total of 589 publications were identified, spanning 175 source journals and comprising 13,950 cited references, with a compound annual growth rate of 18.79% over the complete publication years 1997–2025. Original research articles constituted the majority (n = 427, 72.5%), followed by reviews (n = 139, 23.6%), with a mean citation count of 21.73 per publication. Internationally co-authored papers accounted for 14.6% of the corpus, with the United States and China dominating both output volume and network centrality. Tian W was the most productive and influential contributor (21 publications; H-index 16; 1,004 citations). Core publication venues included Spine, Neurosurgery, and Journal of Neurosurgery: Spine. Keyword co-occurrence analysis identified accuracy, pedicle screw placement, navigation, and fluoroscopy as dominant themes, while citation burst detection revealed a temporal shift from technical validation toward implementation-oriented topics including risk management, feasibility, and clinical governance. These findings characterise robot-assisted spine surgery as a rapidly maturing discipline transitioning from procedural accuracy assurance to risk-stratified, implementation-focused inquiry. Future research should prioritise standardised outcome frameworks, multicentre comparative effectiveness studies, and risk-stratified implementation pathways to optimise patient benefit and guide durable clinical adoption.