Patel Kishan, Judd Hyrum, Harm Richard G, Nolan Joseph R, Hummel Matthew, Spanyer Jonathon
OrthoCincy Orthopaedics and Sports Medicine, 560 South Loop Rd, Edgewood, KY, 41017, United States.
Larkin Hospital Orthopaedic Surgery Residency, 7031 SW 62nd Ave Suite 602, South Miami, FL, 33143, United States.
J Orthop. 2022 Feb 15;31:13-16. doi: 10.1016/j.jor.2022.02.015. eCollection 2022 May-Jun.
Recent studies have attempted to quantify the learning curve associated with integration of robotic technology into surgical practice, but to our knowledge, no study has demonstrated the number of cases needed to reach a steady state of maximum efficiency in operating times using robotic assisted technology.
This was a retrospective analysis of 682 consecutive knees that underwent a robotic-assisted TKA for osteoarthritis by a single surgeon between 2017 and 2020. Procedure times (minutes), length of stay (LOS), and short-term postoperative complications and reoperations were analyzed to define trends. Time series analyses were used to identify the approximate time-point at which a maximum level of surgical operating speed was achieved. Analysis of Variance (ANOVA) and chi-square analyses then followed to compare average procedure duration, LOS, and complications across distinct moving groups of 50 procedures.
Time series analyses suggest substantially improved times by the 50th procedure and reached a stable plateau between the 150th and 200th procedure. Average duration for the first 50 procedures was approximately 85 min, dropping to 69 min for procedures 51-100, 66 min for procedures 101-150, and then plateauing at approximately 61 min for procedures 151-682, demonstrating significant improvements in surgical efficiency at each 50-procedure interval (p < 0.05). There was no significant difference in LOS, readmissions, and reoperations with increasing groups of 50 procedures performed.
Results from this study will allow surgeons to better understand the implications of integrating robotic arm-assisted technology into their practice. Surgeons can expect significant improvement of their operative time following completion of at least 50 procedures, while likely reaching a maximum level of surgical efficiency between 151 and 200 procedures.
近期研究试图量化将机器人技术融入外科手术实践相关的学习曲线,但据我们所知,尚无研究表明使用机器人辅助技术达到手术时间最大效率稳定状态所需的病例数。
这是一项对2017年至2020年间由一名外科医生连续进行机器人辅助全膝关节置换术治疗骨关节炎的682例膝关节病例的回顾性分析。分析手术时间(分钟)、住院时间(LOS)以及术后短期并发症和再次手术情况以确定趋势。采用时间序列分析来确定达到手术操作速度最高水平的大致时间点。随后进行方差分析(ANOVA)和卡方分析,以比较50例不同分组的平均手术持续时间、住院时间和并发症情况。
时间序列分析表明,到第50例手术时时间有显著改善,并在第(150)例至第(200)例手术之间达到稳定平台期。前(50)例手术的平均持续时间约为(85)分钟,第(51 - 100)例手术降至(69)分钟,第(101 - 150)例手术为(66)分钟,然后第(151 - 682)例手术稳定在约(61)分钟,表明在每(50)例手术间隔中手术效率都有显著提高((p < 0.05))。随着每组进行(50)例手术的增加,住院时间、再入院率和再次手术情况无显著差异。
本研究结果将使外科医生更好地理解将机器人手臂辅助技术融入其手术实践的影响。外科医生在完成至少(50)例手术后,手术时间有望显著缩短,而在第(151)例至第(200)例手术之间可能达到手术效率的最高水平。