Comparison of the Learning Curve for Robot-Assisted Laparoscopic Pyeloplasty Between Senior and Junior Surgeons

Abstract

Introduction: The widespread use of robotic surgery has provided surgeons a high-quality and alternative method to perform pyeloplasty. Indeed, robot-assisted technology has made it a lot easier to obtain the advanced technical skills required to perform this procedure. The learning curve (LC) reflects the increase in learning as a function of experience. Robot-assisted laparoscopic pyeloplasty (RALP) represents a well-standardized and reproducible procedure with an LC that allows reliable results to readily be obtained. The aim of our study was to compare the RALP LC of senior versus junior surgeons. Materials and Methods: We reviewed all of the RALP procedures performed at three pediatric surgery centers between November 2007 and November 2018. Three senior surgeons and 4 junior surgeons performed the robotic procedures. Neither the senior nor the junior surgeons had previous experience with robotic surgery; they had experience with conventional laparoscopic procedures but not with laparoscopic pyeloplasty. The primary metric that we selected to evaluate competence acquisition was a composite outcome defined by a combination of operative time (OT), complications, and surgical success. The complications were rated according to the Clavien-Dindo classification expressed by a complication factor; surgical success was expressed as a success factor, and we used a cumulative sum (CUSUM) analysis to determine the LC. The CUSUM method, through its multioutcome approach, is a very effective way to evaluate LCs. Results: Between November 2007 and November 2018, 3 senior surgeons and 4 junior surgeons performed 88 RALP procedures. The included patients had a median age of 6.1 years (range 7 months-16 years). The median duration of follow-up was 6.4 years (range 14 months-12 years). The median OT was 198.86 minutes (range 106-335 minutes). By CUSUM analysis of the composite outcome, we found that despite the junior surgeons having performed fewer procedures than the senior surgeons, their LCs exhibited an earlier inflection point (Fig. 1) followed by a constant rate of improvement in proficiency, thus indicating a more rapid learning process. The median composite scores for the senior surgeons and the junior surgeons were 299 (range 210-370) and 193 (range 131-255), respectively, after seven procedures. Conclusion: Assuming proper exposure to robotics and an adequate case volume, we demonstrated that junior surgeons can readily achieve comparable levels of expertise compared with senior practitioners in the field of pediatric RALP. It can be assumed that the LC in robotic pyeloplasty is not only directly influenced by the individual surgical experience but also by the experience of the surgical team.

Keywords: CUSUM analysis; learning curve; robot-assisted laparoscopic pyeloplasty; robotic surgery.