Urology robotic journey: demonstrating the learning curve in robot-assisted pyeloplasties (RALP)

Abstract

The advantages of robot-assisted pyeloplasties (RALP) have been widely documented and increasingly familiar. A ‘learning curve’ (LC) is difficult to define and its objective review remains problematic. We aimed to evaluate the LC, and outcomes, of RALP performed at our newly established robotic centre. After the appropriate training, robot-assisted surgery (RAS) commenced at our centre. A prospective database was maintained regarding demographics and intra-operative timings of all cases, post-operative stay and complications. The data were statistically interrogated and linear regression analysis was performed. Between April 2014 and September 2018, 29 urological RAS were performed including 23 RALP. The total operating and total console times were significantly decreased over time, with no significant differences seen in length of stay or complication rates. Regression analysis predicted achievement of open pyeloplasty time (148 min) at 26 cases and ‘expert’ console time (58 min) by case 34. Median length of stay was 2 days and operative success rate 96%. RAS is proliferating across the globe. LC is difficult to define objectively. We suggest that the points described here in this ‘learning journey’ can be applied to other nascent departments and that RALP is safe and feasible within a developing urology unit.