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    XIA Tian, WANG Youpeng, SUN Xu, LI Tengteng, WANG Kai, FU Haixiao, FU Wei. The learning curve of da Vinci robot-assisted radical resection for rectal cancer[J]. Journal of Xuzhou Medical University, 2023, 43(6): 433-438. DOI: 10.3969/j.issn.2096-3882.2023.06.008
    Citation: XIA Tian, WANG Youpeng, SUN Xu, LI Tengteng, WANG Kai, FU Haixiao, FU Wei. The learning curve of da Vinci robot-assisted radical resection for rectal cancer[J]. Journal of Xuzhou Medical University, 2023, 43(6): 433-438. DOI: 10.3969/j.issn.2096-3882.2023.06.008

    The learning curve of da Vinci robot-assisted radical resection for rectal cancer

    • Objective To explore the learning curve of da Vinci robot-assisted radical resection for rectal cancer by surgeons with rich experience in laparoscopy, in order to provide reference for promoting the use of da Vinci robot for radical resection of rectal cancer.Methods Clinical data concerning the use of da Vinci robot for radical resection of rectal cancer in the Affiliated Hospital of Xuzhou Medical University from August 2020 to March 2022 were retrospectively analyzed. The duration of operation was evaluated by cumulative sum analysis (CUSUM) to fit a learning curve. According to the critical value of the learning curve, the learning curve of da Vinci robot was divided into different stages. The relevant data of these patients in different learning stages were compared and the learning curve of da Vinci robot for radical resection of rectal cancer was analyzed.Results The optimal curve-fitting equation was y=0.015 8 x3-2.138 5 x2+69.145x+161.39,R2=0.968 7,P<0.05, and the learning curve was achieved after at least 20 surgical cases. According to the results, the learning curve of da Vinci robot-assisted surgery was divided into three stages. There were statistical differences in the distance from the anal edge to the distal edge of the tumor and the duration of operation (P<0.05).Conclusions The learning curve of da Vinci robot-assisted radical resection for rectal cancer by surgeons with rich experience in laparoscopy can be achieved after 20 cases. The learning curve can be divided into three stages.
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