PDF(Pubmed)
Abstract：
BACKGROUND: The adoption of robot-assisted total knee arthroplasty (TKA) aims to enhance the precision of implant positioning and limb alignment. Despite its benefits, the adoption of such technology is often accompanied by an initial learning curve, which may result in increased operative times. This study sought to determine the learning curve for the ROSA (Robotic Surgical Assistant) Knee System (Zimmer Biomet) in performing TKA and to evaluate the accuracy of the system in executing bone cuts and angles as planned. The hypothesis of this study was that cumulative experience with this robotic system would lead to reduced operative times. Additionally, the ROSA system demonstrated reliability in terms of the accuracy and reproducibility of bone cuts.
METHODS: In this retrospective observational study, we examined 110 medical records from 95 patients who underwent ROSA-assisted TKA performed by three surgeons. We employed the cumulative summation methodology to assess the learning curves related to operative time. Furthermore, we evaluated the accuracy of the ROSA Knee System in performing TKA by comparing planned versus validated values for femoral and tibial bone cuts and angles.
RESULTS: The learning curve for the ROSA Knee System spanned 14, 14, and 6 cases for the respective surgeons, with operative times decreasing by 22 min upon reaching proficiency (70.8 vs. 48.9 min; p < 0.001). Significant discrepancies were observed between the average planned and validated cuts and angles for femoral bone cuts (0.4 degree ± 2.4 for femoral flexion, 0.1 degree ± 0.6 for femoral coronal alignment, 0.3 mm ± 1.2 for distal medial femoral resection, 1.4 mm ± 8.8 for distal lateral femoral resection) and hip-knee-ankle axis alignment (0.3 degree ± 1.9 )(p < 0.05) but not for tibial bone cuts. Differences between planned and validated measurements during the learning and proficiency phases were nonsignificant across all parameters, except for the femoral flexion angle (0.42 degree ± 0.8 vs. 0.44 degree ± 2.7) (p = 0.49).
CONCLUSIONS: The ROSA Knee System can be integrated into surgical workflows after a modest learning curve of 6 to 14 cases. The system demonstrated high accuracy and reproducibility, particularly for tibial bone cuts. Acknowledging the learning curve associated with new robot-assisted TKA technologies is vital for their effective implementation.
METHODS: In this retrospective observational study, we examined 110 medical records from 95 patients who underwent ROSA-assisted TKA performed by three surgeons. We employed the cumulative summation methodology to assess the learning curves related to operative time. Furthermore, we evaluated the accuracy of the ROSA Knee System in performing TKA by comparing planned versus validated values for femoral and tibial bone cuts and angles.
RESULTS: The learning curve for the ROSA Knee System spanned 14, 14, and 6 cases for the respective surgeons, with operative times decreasing by 22 min upon reaching proficiency (70.8 vs. 48.9 min; p < 0.001). Significant discrepancies were observed between the average planned and validated cuts and angles for femoral bone cuts (0.4 degree ± 2.4 for femoral flexion, 0.1 degree ± 0.6 for femoral coronal alignment, 0.3 mm ± 1.2 for distal medial femoral resection, 1.4 mm ± 8.8 for distal lateral femoral resection) and hip-knee-ankle axis alignment (0.3 degree ± 1.9 )(p < 0.05) but not for tibial bone cuts. Differences between planned and validated measurements during the learning and proficiency phases were nonsignificant across all parameters, except for the femoral flexion angle (0.42 degree ± 0.8 vs. 0.44 degree ± 2.7) (p = 0.49).
CONCLUSIONS: The ROSA Knee System can be integrated into surgical workflows after a modest learning curve of 6 to 14 cases. The system demonstrated high accuracy and reproducibility, particularly for tibial bone cuts. Acknowledging the learning curve associated with new robot-assisted TKA technologies is vital for their effective implementation.
摘要：
背景：采用机器人辅助的全膝关节置换术（TKA）旨在提高植入物定位和肢体对准的精度。尽管有好处,这种技术的采用通常伴随着初始的学习曲线，这可能会导致手术时间增加。这项研究旨在确定ROSA（机器人手术助手）膝关节系统（ZimmerBiomet）在执行TKA时的学习曲线，并评估系统按计划执行骨切割和角度的准确性。这项研究的假设是，这种机器人系统的累积经验将导致手术时间减少。此外,ROSA系统在骨切割的准确性和可重复性方面证明了可靠性。
方法：在这项回顾性观察研究中，我们检查了由3名外科医生进行ROSA辅助TKA的95例患者的110份病历.我们采用累积求和方法来评估与手术时间相关的学习曲线。此外，我们通过比较股骨和胫骨骨切口和角度的计划值和验证值,评估了ROSA膝关节系统进行TKA的准确性.
结果：ROSA膝关节系统的学习曲线跨越14、14和6例，分别适用于外科医生，手术时间在达到熟练程度后减少22分钟(70.8与48.9分钟；p<0.001）。在股骨骨切割的平均计划和验证的切割和角度之间观察到显着差异（股骨屈曲的0.4度±2.4，股骨冠状排列0.1度±0.6，股骨远端内侧切除术0.3mm±1.2,对于股骨远端外侧切除术为1.4mm±8.8）和髋-膝-踝轴对齐（0.3度±1.9）（p<0.05），但对于胫骨骨切割则不适用。在学习和熟练阶段，计划和验证的测量之间的差异在所有参数中都不显著，除了股骨屈曲角度（0.42度±0.8vs.0.44度±2.7)(p=0.49)。
结论：ROSA膝关节系统可以在6至14例的适度学习曲线后整合到手术工作流程中。该系统具有较高的准确性和可重复性,特别是胫骨骨切割。认识到与新的机器人辅助TKA技术相关的学习曲线对于其有效实施至关重要。
方法：在这项回顾性观察研究中，我们检查了由3名外科医生进行ROSA辅助TKA的95例患者的110份病历.我们采用累积求和方法来评估与手术时间相关的学习曲线。此外，我们通过比较股骨和胫骨骨切口和角度的计划值和验证值,评估了ROSA膝关节系统进行TKA的准确性.
结果：ROSA膝关节系统的学习曲线跨越14、14和6例，分别适用于外科医生，手术时间在达到熟练程度后减少22分钟(70.8与48.9分钟；p<0.001）。在股骨骨切割的平均计划和验证的切割和角度之间观察到显着差异（股骨屈曲的0.4度±2.4，股骨冠状排列0.1度±0.6，股骨远端内侧切除术0.3mm±1.2,对于股骨远端外侧切除术为1.4mm±8.8）和髋-膝-踝轴对齐（0.3度±1.9）（p<0.05），但对于胫骨骨切割则不适用。在学习和熟练阶段，计划和验证的测量之间的差异在所有参数中都不显著，除了股骨屈曲角度（0.42度±0.8vs.0.44度±2.7)(p=0.49)。
结论：ROSA膝关节系统可以在6至14例的适度学习曲线后整合到手术工作流程中。该系统具有较高的准确性和可重复性,特别是胫骨骨切割。认识到与新的机器人辅助TKA技术相关的学习曲线对于其有效实施至关重要。
