Zadzilka Jayson, Stulberg Bernard, Davis Brian
Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, OH, USA.
Department of Orthopedic Surgery, Crystal Clinic Orthopaedic Center, Fairlawn, Ohio, USA.
J Orthop. 2025 Mar 10;69:42-46. doi: 10.1016/j.jor.2025.03.004. eCollection 2025 Nov.
There are many factors to consider while planning and executing a successful total knee arthroplasty. One of these, the amount of bony resection, is determined in part based on the patients' anatomy and preoperative deformity. Utilizing intraoperative technology such as robotics allows for resection to be done accurately. Therefore, the goal of this study was to investigate the relationship between tibial & femoral resection depths and postoperative outcomes. Additionally, a quantitative method for preoperatively determining the level of resection depth needed was developed.
A de-identified dataset containing 107 robotic total knee arthroplasty cases was reviewed. Preoperative demographics, preoperative planning details, and sub-scale scores from the Knee Society Scoring System were reviewed. Analysis was performed to find significant associations with the sub-scale scores. Additionally, multiple regression models were developed to predict resection depth values.
Associations were found between femoral resection depth and Satisfaction & Function scores three months postoperatively. Additionally, Satisfaction and Function were 6 % and 16 % higher respectively when the native alignment strategy was used rather than mechanical alignment of the lower limb. Three-month Function scores were also 6 % higher for males than females. The models to predict resection depth included alignment strategy, preoperative knee deformity, and gender as the significant contributors.
Tibial and femoral resection depth can influence postoperative outcomes. Therefore, it is important to understand what factors contribute to the determination of how much bone should be resected. With that information, patient-specific preoperative plans can be developed with the intent of optimizing postoperative outcomes.
在计划和实施成功的全膝关节置换术时,有许多因素需要考虑。其中之一,骨切除量部分取决于患者的解剖结构和术前畸形情况。利用术中技术,如机器人技术,可实现精确切除。因此,本研究的目的是调查胫骨和股骨切除深度与术后结果之间的关系。此外,还开发了一种术前确定所需切除深度水平的定量方法。
回顾了一个包含107例机器人辅助全膝关节置换术病例的匿名数据集。审查了术前人口统计学资料、术前规划细节以及膝关节协会评分系统的子量表评分。进行分析以找出与子量表评分的显著关联。此外,还建立了多元回归模型来预测切除深度值。
发现股骨切除深度与术后三个月的满意度和功能评分之间存在关联。此外,采用自然对线策略而非下肢机械对线时,满意度和功能分别提高了6%和16%。男性的三个月功能评分也比女性高6%。预测切除深度的模型包括对线策略、术前膝关节畸形和性别作为重要因素。
胫骨和股骨切除深度会影响术后结果。因此,了解哪些因素有助于确定应切除多少骨量很重要。有了这些信息,就可以制定针对患者的术前计划,以优化术后结果为目的。