Predictive Accuracy Analysis of a Novel Robotic-Assisted System for Total Knee Arthroplasty:A Prospective Observational Study
Haichuan Miao, Zhiyong Zhu, Huisheng Wang, Xizhuang Bai, Xi Li
- 发表年份
- 2024
- 引用次数
- 2
- 访问权限
- 开放获取
摘要
Background: Robotic-assisted total knee arthroplasty (RATKA) has been reported to enhance operative decision-making. The purpose of this study was intended to assess the predictive accuracy of bone cuts, lower limb alignment, and component size of a novel system for RATKA preoperatively and intraoperatively. Methods: Preoperatively planned bone cuts, limb alignment, and component size were projected using a reconstructed 3D model. Intraoperative bone cuts and postoperative limb alignment were measured. Errors between planned and real bone cuts, limb alignment, and component size were compared. Results: The mean absolute errors for bone cuts and alignment were within 1.40mm/1.30° with a standard deviation (SD) of 0.96mm/1.12°. For all errors of bone cuts and alignment compared with the plan, there were no statistically significant differences except for the lateral distal of femoral cuts ( P =0.004). The accuracy for predicting the femoral, tibial, and polyethylene component sizes was 100% (48/48), 90% (43/48), and 88% (42/48), respectively. Regarding all mean absolute errors of bone cuts and alignments, no significant differences were observed among surgeons. Conclusion: The novel robotically-assisted system for RATKA donated reliable operative decision-making based on the predictive accuracy regardless of the surgeon’s level of experience. Keywords: robotic surgery, total knee arthroplasty, resection, implant, level of experience
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