It has been performed laparoscopically with good results [1]. In 2000, the Food and Drug Administration HTC (FDA) approved the da Vinci Surgical System (Intuitive Surgical Inc, Sunnyvale, CA, USA) for use in general laparoscopic surgery, and since then many surgeons have used this system in order to improve their surgical outcomes [5]. It has also been used in bariatric surgery to complete demanding surgeries such as GBP, which requires high levels of expertise even in trained surgeons [6, 7]. Our data support the conclusion that both setup and docking of the robot can be achieved within an acceptable time after the learning curve. The learning curve process may have a low impact on overall surgical time. However this can only be determined by comparing subsequent cases with the first cases performed by each surgeon.

Unfortunately, the relevant data were not available. Set-up time and docking time were recently evaluated for different robotic surgeries, and it was shown that they could be initially time consuming but that they are easy to learn and have steep learning curves [8]. The same was found in our initial experience working with the same scrub-nurse team and the same surgical team members. No data are available on the learning curve for robotic sleeve gastrectomy. Also, we have not been able to compare the learning curve of RSG procedure to RGBP because only 7 cases have been performed. Laparoscopic sleeve gastrectomy can be safely and efficiently performed in a newly established bariatric centre following a mentorship procedure.

Extended mentoring has been shown to affect outcomes, especially for less experienced surgeons [9]. It is known that sleeve gastrectomy is a less technically demanding procedure compared to gastric bypass. However, when implementing new technologies such as robotic assisted surgery, it can be a more amenable procedure than gastric bypass. In addition, the learning curve has been reported to be shorter for surgeons who initiated their experience at an institution with an established laparoscopic bariatric programme [10, 11]. A learning curve can be identified in operative times and complications. Some authors have shown that proficiency seems to require 68 cases [12]. We included more patients in order to determine the number of cases needed to produce a plateau in these variables.

Some previous articles have suggested that it took 30 robotic cases to perform the procedure in less time than it took for her median laparoscopic times. They, therefore, concluded that the learning curve was 30 cases [13]. Buchs in his article ��Learning curve for robot-assisted Roux-en-Y gastric bypass�� assessed the learning curve using a cumulative sum method. He found the learning curve consisted of two distinct phases: phase 1 (the GSK-3 initial 14 cases; mean OT, 288.