Zhou Junfeng, Shi Yan, Qian Feng, Tang Bo, Hao Yingxue, Zhao Yongliang, Yu Peiwu
Department of General Surgery and Center of Minimal Invasive Gastrointestinal Surgery, Southwest Hospital, Third Military Medical University, Chongqing, China.
J Surg Oncol. 2015 May;111(6):760-7. doi: 10.1002/jso.23876. Epub 2015 Jan 8.
The purpose of this study was to determine the learning curve for robot-assisted gastrectomy using the Cumulative Summation (CUSUM) technique.
Two series of consecutive robotic gastrectomy were retrospective analyzed. Patient demographics, surgical performance, and short-term outcomes were examined and data of operation time were abstracted for the learning curve analysis.
Similar processes occurred in the two surgeons. Each of their learning curves of robotic gastrectomy was best modeled as a third-order polynomial, with equation CUSUMOT in minutes equal to 0.0495 case number (3) - 4.217 case number(2) + 91.206 case number 100.11(R(2) = .8731) for surgeon A and 0.0314 case number (3) - 2.4106 case number(2) + 33.682 case number + 315.28(R(2) = 0.8816) for surgeon B. They both included three unique phases: an initial phase, a well-developed phase, and a mastery phase after the accumulation of additional experience.
The CUSUM method is a useful tool for objective evaluation of practical skills for surgeons during the learning phase of robotic surgery training. The robotic gastrectomy is found to have a short learning curve for experienced laparoscopic surgeons and the popularity of this new technology won't reduce because of its difficulty to learn.
本研究旨在使用累积求和(CUSUM)技术确定机器人辅助胃切除术的学习曲线。
对两系列连续的机器人胃切除术进行回顾性分析。检查患者人口统计学、手术表现和短期结局,并提取手术时间数据用于学习曲线分析。
两位外科医生的情况相似。他们各自的机器人胃切除术学习曲线最佳拟合为三次多项式,对于外科医生A,以分钟为单位的CUSUMOT方程等于0.0495×病例数³ - 4.217×病例数² + 91.206×病例数 + 100.11(R² = 0.8731),对于外科医生B,方程为0.0314×病例数³ - 2.4106×病例数² + 33.682×病例数 + 315.28(R² = 0.8816)。他们都包括三个独特阶段:初始阶段、成熟阶段以及积累更多经验后的精通阶段。
CUSUM方法是在机器人手术训练学习阶段客观评估外科医生实践技能的有用工具。对于有经验的腹腔镜外科医生而言,机器人胃切除术的学习曲线较短,且这项新技术不会因其学习难度而降低受欢迎程度。