Learning curve of robotic distal and total gastrectomy

Abstract

Background This study aims to assess the learning curve of robotic distal gastrectomy (RDG) and robotic total gastrectomy (RTG) for gastric cancer. Methods Data on consecutive patients who underwent robotic gastrectomy for gastric cancer by five surgeons between March 2010 and August 2019 at two high-volume institutions were collected. The learning curve was determined based on the analyses of operation time and postoperative complications within 30 days. Cumulative sum analysis (CUSUM) and risk-adjusted-CUSUM (RA-CUSUM) were applied to identify the turning points (TPs). Results A total of 899 consecutive patients were included. The mean number of patients needed to overcome the learning curve for operation time of RDG and RTG were 22 and 20, respectively. The number of patients needed to overcome the learning curve for postoperative complications after RDG and RTG were 23 and 18, respectively. The surgical outcomes in the post-TP group were better than in the pre-TP group and improved as surgeons’ experience increased. Also, increased case numbers in RDG promoted the RTG learning process. Conclusion The present study demonstrated a substantial influence of surgical cumulative volume on improved surgical outcomes in robotic gastrectomy. Increased experience in RDG may help surgeons to achieve proficiency faster in RTG.

The adoption of oncoplastic surgery: Is there a learning curve?

“…Our reported learning curve is similar to other fields of surgery when comparing the impact of experience to operative time and complication rate, the two most commonly measured variables for learning curves. Our finding of decreased mean operative time is consistent with findings from several other studies 9,18–22 . While the measured complications are different, several studies in other surgical fields have demonstrated a decrease in individual and overall complication rates with experience 18,21,23,24 …”

Expert consensus on a standardized training curriculum for robotic gastrectomy for gastric cancer using Delphi process

“…The turning point in the learning curve of RG was reportedly considered to be around 18 to 25 cases; the complication rate and conversion rate up to the turning point were signi cantly higher than those afterwards [12][13][14]. In other words, the technical immaturity of endoscopic surgeons has a signi cant impact on the surgical outcome of RG.…”

“…However, robot-speci c aspects such as port placement, docking maneuvers, the master controller and foot pedals on the surgeons' console, and the lack of haptic feedback are all crucial for surgeons to master in their training [11]. The learning curve for RG is reportedly less steep compared to traditional laparoscopic surgery, but there may have been bias since these studies were conducted on endoscopic surgeons with prior experience in conventional LG [12][13][14]. Nevertheless, with the increasingly widespread use of surgical robots, the number of surgeons performing RG for gastric cancer are expected to increase.…”

A multidimensional learning curve analysis of totally laparoscopic ileostomy reversal using a single surgeon' s experience

“…Furthermore, RA-CUSUM analysis was applied to depict the success or failure of the TLAP technique. First, baseline variables with P < 0.20 in the univariate association were considered for inclusion, and the predicted probabilities of each case were calculated according to the regression coefficients of the variables in the final multivariate regression model ( 20 ). Then, for each failure case, the RA-CUSUM value was incremented by (1-predicted probability of failure).…”