单室膝关节置换术
医学
生存曲线
植入
患者满意度
外科
前瞻性队列研究
关节置换术
置信区间
固定(群体遗传学)
骨关节炎
癌症
内科学
病理
替代医学
环境卫生
人口
作者
Tarik Bayoumi,Laura J. Kleeblad,Todd A. Borus,Thomas M. Coon,Jon Dounchis,Joseph Nguyen,Andrew D. Pearle
标识
DOI:10.2106/jbjs.22.01104
摘要
Robotic-arm-assisted unicompartmental knee arthroplasty (UKA) has been shown to result in high short- and mid-term survivorship. However, it is not known whether these outcomes are maintained at long-term follow-up. This study aimed to evaluate long-term implant survivorship, modes of failure, and patient satisfaction following robotic-arm-assisted medial UKA.A prospective multicenter study of 474 consecutive patients (531 knees) undergoing robotic-arm-assisted medial UKA was conducted. A cemented, fixed-bearing system with a metal-backed onlay tibial implant was used in all cases. Patients were contacted at 10-year follow-up to determine implant survivorship and satisfaction. Survival was analyzed using Kaplan-Meier models.Data were analyzed for 366 patients (411 knees) with a mean follow-up of 10.2 ± 0.4 years. A total of 29 revisions were reported, corresponding to a 10-year survivorship of 91.7% (95% confidence interval, 88.8% to 94.6%). Of all revisions, 26 UKAs were revised to total knee arthroplasty. Unexplained pain and aseptic loosening were the most commonly reported modes of failure, accounting for 38% and 35% of revisions, respectively. Of patients without revision, 91% were either satisfied or very satisfied with their overall knee function.This prospective multicenter study found high 10-year survivorship and patient satisfaction following robotic-arm-assisted medial UKA. Pain and fixation failure remained common causes for revision following cemented fixed-bearing medial UKA, despite the use of a robotic-arm-assisted technique. Prospective comparative studies are needed to assess the clinical value of robotic assistance over conventional techniques in UKA.Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.
科研通智能强力驱动
Strongly Powered by AbleSci AI