Institute of Women's Life Medical Science, Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Yonsei University College of Medicine, Seoul, Korea.
J Gynecol Oncol. 2013 Oct;24(4):303-12. doi: 10.3802/jgo.2013.24.4.303. Epub 2013 Oct 2.
The aim of this study was to evaluate the learning curve and perioperative outcomes of robot-assisted laparoscopic procedure for cervical cancer.
A series of 65 cases of robot-assisted laparoscopic radical hysterectomies with bilateral pelvic lymph node dissection for early stage cervical cancer were included. Demographic data and various perioperative parameters including docking time, console time, and total operative time were reviewed from the prospectively collected database. Console time was set as a surrogate marker for surgical competency, in addition to surgical outcomes. The learning curve was evaluated using cumulative summation method.
The mean operative time was 190 minutes (range, 117 to 350 minutes). Two unique phases of the learning curve were derived using cumulative summation analysis; phase 1 (the initial learning curve of 28 cases), and phase 2 (the improvement phase of subsequent cases in which more challenging cases were managed). Docking and console times were significantly decreased after the first 28 cases compared with the latter cases (5 minutes vs. 4 minutes for docking time, 160 minutes vs. 134 minutes for console time; p<0.001 and p<0.001, respectively). There was a significant reduction in blood loss during operation (225 mL vs. 100 mL, p<0.001) and early postoperative complication rates (28% vs. 8.1%, p=0.003) in phase 2. No conversion to laparotomy occurred.
Improvement of surgical performance in robot-assisted surgery for cervical cancer can be achieved after 28 cases. The two phases identified by cumulative summation analysis showed significant reduction in operative time, blood loss, and complication rates in the latter phase of learning curve.
本研究旨在评估机器人辅助腹腔镜宫颈癌根治术的学习曲线和围手术期结果。
本研究纳入了 65 例早期宫颈癌行机器人辅助腹腔镜广泛子宫切除术和双侧盆腔淋巴结清扫术的病例。从前瞻性收集的数据库中回顾了人口统计学数据和各种围手术期参数，包括对接时间、控制台时间和总手术时间。控制台时间被设定为手术能力的替代标志物，除了手术结果。使用累积和分析评估学习曲线。
平均手术时间为 190 分钟（范围 117-350 分钟）。使用累积和分析得出了学习曲线的两个独特阶段；第 1 阶段（28 例的初始学习曲线）和第 2 阶段（后续更具挑战性病例的改进阶段）。与后期病例相比，前 28 例的对接和控制台时间显著减少（对接时间 5 分钟对 4 分钟，控制台时间 160 分钟对 134 分钟；p<0.001 和 p<0.001）。手术中出血量显著减少（225 毫升对 100 毫升，p<0.001），术后早期并发症发生率也显著降低（28%对 8.1%，p=0.003）。没有病例转为开腹手术。
在完成 28 例手术后，机器人辅助宫颈癌手术的手术性能可以得到提高。累积和分析确定的两个阶段显示，在学习曲线的后期阶段，手术时间、出血量和并发症发生率显著降低。
