Accuracy and Outcomes of a Novel Cut-Block Positioning Robotic-Arm Assisted System for Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

新型切割块定位机器人手臂辅助系统在全膝关节置换术中的准确性和结果:系统评价和荟萃分析

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Abstract

BACKGROUND: The primary objective of this study was to determine the accuracy and precision of component positioning of the ROSA Robotic System for total knee arthroplasty (TKA). METHODS: A Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic review was conducted using 4 electronic databases (MEDLINE, EMBASE, Pubmed, and Cochrane Library) to identify all clinical and radiological studies reporting information about the use and results of the ROSA system. The criteria for inclusion were published research articles evaluating the accuracy of component positioning, learning curve, component alignment, complications, and functional outcomes in adults who underwent robotic-assisted TKA. The National Institutes of Health Quality Assessment Tool was used to evaluate the quality of all the included studies. RESULTS: A total of 26 studies were assessed for eligibility, and 17 met the inclusion criteria. Nine studies reported on the accuracy and precision of component positioning. The ROSA platform for TKA had a cutting error of less than 0.6(°) for all coronal and sagittal parameters. Pooled analysis demonstrated accuracy within 0.61-1.87(°) and precision within 0.97-1.34(°) when the final intraoperative plan was compared to postoperative radiographs with fewer outliers. Four studies reported improved functional scores with ROSA-assisted TKA than conventional TKA within 1 year of surgery. There was no difference in overall complication rates when compared to conventional TKA. CONCLUSIONS: The ROSA system is both highly accurate and precise, with fewer outliers when analyzed at various time points, including postoperative standing radiographs. Future studies with robust methodology and longer follow-up are required to demonstrate whether these findings have any clinical benefits in the long term.

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