Robotic-assisted laparoscopic radical hysterectomy for early-stage cervical cancer: The more experienced the bedside assistant, the better?

Background: Aim to investigate the impact of bedside assistant's work experience and learning curve on the short-term safety and efficacy in robotic-assisted laparoscopic radical hysterectomy for early-stage cervical cancer. Methods: Our research retrospectively retrieved 120 cases of early-stage cervical cancer patients who underwent robotic-assisted laparoscopic radical hysterectomy at the First Affiliated Hospital of Guangxi Medical University. According to the different work experiences of the two bedside assistants (BA), patients were divided into a research group (inexperienced BA 1) and a control group (experienced BA 2). Furthermore, the learning curves of these BAs were plotted separately and divided into two distinct phases by cumulative summation: the first learning phase and the second master phase. Result: In terms of work experience, comparing BA 1 with BA 2 who was more experienced, although the average operative time was prolonged by 29 min (P＜0.001), it did not increase the incidence of operative complication [24.4 % VS 29.1 %, P = 0.583], positive resection margin [4.9 % VS 7.6 %, P = 0.714], intraoperative organ damage [0 % VS 2.5 %, P = 0.546] and there was no significant difference in the number of lymph nodes [19 VS 15, P = 0.103]. Additionally, comparing two distinct phases of the same bedside assistant, there was no significant increasing rate in terms of operative complication, positive resection margin, intraoperative organ damage, and the number of lymph nodes (P＞0.05) neither BA 1 nor BA 2, except for a slight extension of operative time about 20 min in learning phase (P＜0.05). Conclusion: In robotic-assisted laparoscopic radical hysterectomy for early-stage cervical cancer, work inexperience and the learning phase of BA only result in a slight extension of operative time, without causing worse short-term surgical outcomes.