Robotic docking time with the Hugo™ RAS system in gynecologic surgery: a procedure independent learning curve using the cumulative summation analysis (CUSUM)

Robot-assisted surgery has been proven to offer improvements in term of surgical learning curve and feasibility of minimally invasive surgery, but has often been criticized for its longer operative times compared to conventional laparoscopy. Additional times can be split into time required for system set-up, robotic arms docking and calibration of robotic instruments; secondly, surgeon's learning curve. One of the newest systems recently launched on the market is the Hugo & TRADE; RAS (MEDTRONIC Inc, United States). As some of the earliest adopters of the Hugo & TRADE; RAS system technology, we present our data on robotic docking learning curve for the first 192 gynecologic robotic cases performed at our institution. Our data indicates that robotic set-up and docking with the new Hugo & TRADE; RAS robotic surgical system can be performed time-effectively and that the specific robotic docking learning curve is comparable to preexisting data for other platforms. This preliminary insights into this recently released system may be worthwhile for other centers which may soon adopt this new technology and may need some relevant information on topics such as OR times. Further studies are necessary to assess the different features of the Hugo & TRADE; RAS considering other technical and surgical aspects, to fully become familiar with this novel technology.