The learning curve of robot-assisted laparoscopic pyeloplasty in children: a multi-outcome approach

Abstract

Introduction: Few studies have evaluated the learning curve (LC) for robot-assisted laparoscopic pyeloplasty (RALP) for ureteropelvic junction obstruction in children. It was attempted to assess the LC of this procedure using a multi-outcome approach, accounting for patient complexity.

Material and methods: Data on the first series of children undergoing RALP between November 2007 and December 2017 at the study institution were prospectively collected. Patient complexity factors and peri-operative data including operative time (OT) were retrospectively analyzed. The LC was analyzed using cumulative sum (CUSUM) methodology for OT and a composite parameter (combination of 3 parameters: OT adjusted for patient complexity factors (AOT), complications, and surgical success).

Results: Two surgeons without any experience in robotic surgery performed 42 consecutive RALP in 41 patients. Median age at surgery was 5 years (6 months-15 years), and mean OT was 200 ± 72.8 min. Cumulative sum chart demonstrated biphasic LC for OT and multiphasic LC for composite factor. Based on the CUSUM analysis for composite outcome, the LC for RALP could be divided into three different phases: phase 1, the learning period (1-12 cases); phase 2, the consolidation period (13-22 cases); and phase 3, representing the period of increased competence (23-39 cases). Interphase comparison showed a significant reduction in OT, length of stay, and postoperative pain (P = 0.0001; P = 0.0076; P = 0.039, respectively) CONCLUSION: Numerous distinctly shaped LCs depending on the outcome measures and well-defined learning phase transition points were demonstrated. Patient complexity factors were accounted for, which can influence surgical outcomes. Because there is no perfect indicator of proficiency, a multi-outcome approach was adopted to provide a comprehensive view of the learning process for RALP. More than 41 cases are needed to achieve mastery.

Keywords: CUSUM analysis; Learning curve; Pediatric surgery; Robot-assisted pyeloplasty.