Pujol Oriol, Minguell Joan, Pijoan Joan, Aguilar Marc, Reverté Mercè, Plomer Martí, García-Albó Enrique, Joshi Nayana
Knee Surgery Unit, Orthopaedic Surgery Department, Vall d'Hebron University Hospital, Pg. Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Musculoskeletal Reconstructive Surgery Department, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain.
J Robot Surg. 2025 Jul 22;19(1):411. doi: 10.1007/s11701-025-02597-7.
To perform a literature review analyzing the surgical team learning curve (LC) for robotic-assisted total knee arthroplasty (RATKA), assessing: (1) operative time, (2) accuracy to reproduce the planned limb alignment, (3) accuracy for implant positioning, (4) functional outcomes and (5) reoperation and complication rates. A systematic search of the literature was performed using two different electronic databases: PubMed (MEDLINE) and Cochrane Library. The search strategy was: "Knee" AND ("Robot" OR "Robotic") AND ("Learning" OR "Curve" OR "Time"). All manuscripts with full text available, written in English or Spanish and published up to December 2024 analyzing RATKA LC were included in the review. Thirty-two articles published between 2018 and 2024 were included. Eighteen (56%) were published in the last two years, reflecting a growing interest in RATKA LC. The 96.9% of the articles analyzed the LC of operative time. The mean number of cases required to reach the proficiency phase was 16 ± 12 (range: 3-61), and the mean number of cases needed to match the operative time of manual TKA was 32 ± 24 (range: 3-73). Accuracy in reproducing planned limb alignment and implant positioning was assessed in 25.0% and 28.1% of the articles, respectively; 94% of them (16/17) reported no LC effect. Only a few studies analyzed the LC of functional outcomes (3/32) and reoperation or complication rates (5/32), and all reported no LC effect. There is a significant learning curve effect for operative time in robotic-assisted TKA, with a mean of 16 ± 12 cases required to reach the proficiency phase and 32 ± 24 cases needed to match the operative time of manual TKA. However, there is no learning curve for accuracy in achieving the planned limb alignment and implant positioning, functional outcomes, or reoperation and complication rates.
进行一项文献综述，分析机器人辅助全膝关节置换术（RATKA）的手术团队学习曲线（LC），评估：（1）手术时间，（2）重现计划肢体对线的准确性，（3）植入物定位的准确性，（4）功能结果，以及（5）再次手术和并发症发生率。使用两个不同的电子数据库进行文献系统检索：PubMed（MEDLINE）和Cochrane图书馆。检索策略为：“膝关节”与（“机器人”或“机器人的”）与（“学习”或“曲线”或“时间”）。所有全文可用、以英文或西班牙文撰写且截至2024年12月发表的分析RATKA LC的手稿均纳入本综述。纳入了2018年至2024年间发表的32篇文章。其中18篇（56%）发表于过去两年，反映出对RATKA LC的兴趣日益浓厚。96.9%的文章分析了手术时间的学习曲线。达到熟练阶段所需的平均病例数为16±12（范围：3 - 61），与手动全膝关节置换术手术时间匹配所需的平均病例数为32±24（范围：3 - 73）。分别有25.0%和28.1%的文章评估了重现计划肢体对线和植入物定位的准确性；其中94%（16/17）报告无学习曲线效应。仅有少数研究分析了功能结果（3/32）以及再次手术或并发症发生率（5/32）的学习曲线，且均报告无学习曲线效应。机器人辅助全膝关节置换术中手术时间存在显著的学习曲线效应，达到熟练阶段平均需要16±12例病例，与手动全膝关节置换术手术时间匹配需要32±24例病例。然而，在实现计划肢体对线和植入物定位的准确性、功能结果或再次手术及并发症发生率方面不存在学习曲线。
