Abstract
Hysterectomy is the most frequent surgery done with robotic assistance in the world and has been widely studied since its emergence. The surgical outcomes of the robotic hysterectomy are similar to those obtained with other minimally invasive hysterectomy techniques (laparoscopic and vaginal) and appear as a promising surgical technique in gynecology surgery. The aim of this study was to observe the learning curve of robot-assisted hysterectomy in a French surgical center, and was to evaluate the impact of the surgical mentoring. We retrospectively collected the data from the files of the robot-assisted hysterectomies with the Da Vinci® Surgical System performed between March 2010 and June 2014 at the Foch hospital in Suresnes (France). We first studied the operative time according to the number of cases, independently of the surgeon to determine two periods: the initial learning phase (Phase 1) and the control of surgical skills phase (Phase 2). The phase was defined by mastering the basic surgical tasks. Secondarily, we compared these two periods for operative time, blood losses, body mass index (BMI), days of hospitalizations, and uterine weight. We, finally, studied the difference of the learning curve between an experimented surgeon (S1) who practiced first the robot-assisted hysterectomies and a less experimented surgeon (S2) who first assisted S1 and then operated on his own patients. A total of 154 robot-assisted hysterectomies were analyzed. Twenty procedures were necessary to access to the control of surgical skills phase. There was a significant decrease of the operative time between the learning phase (156.8 min) compared to the control of surgical skills phase (125.8 min, p = 0.003). No difference between these two periods for blood losses, BMI, days of hospitalizations and uterine weight was demonstrated. The learning curve of S1 showed 20 procedures to master the robot-assisted hysterectomies with a significant decrease of the operative time, while the learning curve of S2 showed no improvement in operative time with respect to case number. Twenty robot-assisted hysterectomies are necessary to achieve control of surgical skills. The companionship to learn robotic surgery seems also promising, by improving the learning phase for this surgical technique.
Highlights
Since the first hysterectomy with robotic assistance, the emergence of this new surgical technique was widely studied [1,2,3,4,5]
The learning curve of S1 showed 20 procedures to master the robot-assisted hysterectomies with a significant decrease of the operative time, while the learning curve of S2 showed no improvement in operative time with respect to case number
Overall 154 robotic hysterectomies were realized between March 2010 and June 2014 at the Foch hospital in Suresnes (France)
Summary
Since the first hysterectomy with robotic assistance, the emergence of this new surgical technique was widely studied [1,2,3,4,5]. Bogani et al [9] demonstrated that the implementation of roboticassisted surgery for endometrial cancer staging improves patient outcomes as lower post-operative complication rate, lower blood transfusion rate, longer median operating time, shorter median length of stay, and lower readmission rate compared to patients undergoing open staging. Hysterectomy is the most frequent surgery done with robotic assistance in the world and has been widely studied since its emergence. The surgical outcomes of the robotic hysterectomy are similar to those obtained with other minimally invasive hysterectomy techniques (laparoscopic and vaginal) and appear as a promising surgical technique in gynecology surgery. The aim of this study was to observe the learning curve of robot-assisted hysterectomy in a French surgical center, and was to evaluate the impact of the surgical mentoring
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