Abstract
OBJECTIVES
Robot-assisted laparoscopic ureteric reimplantation (RALUR) is a minimally invasive procedure for treating vesicoureteral reflux (VUR) and congenital megaureter. Despite its benefits, the adoption of RALUR involves a significant learning curve. This study aims to evaluate the learning curve of a fellowship-trained surgeon performing RALUR using cumulative sum (CUSUM) analysis.
METHODS
A retrospective review of RALUR cases without concurrent procedures from July 2012 to July 2024 was conducted. Patients' clinical characteristics and surgical outcomes were assessed. The learning curve was analyzed using CUSUM for operative time (OT) and complication rates (CR), dividing the curve into three phases: learning (phase 1), competency (phase 2), and proficiency (phase 3).
RESULTS
There was a total of 65 eligible RALUR cases within specified time-period (38 bilateral). There was an overall median follow up of 16.8 months (IQR 8.2-39.4). The overall reoperation rates were 6.2% (4/65). CUSUM-OT peaked at case 23, indicating the end of the learning phase, and progression to competency (phase 2). By case 40, the surgeon achieved proficiency, with continued improvement in CUSUM-CR. Increased case complexity and trainee involvement in phase 3 did not adversely affect patient outcomes. Mention traditional OT analysis finding.
CONCLUSION
The learning curve for RALUR can be effectively mapped using CUSUM analysis, with technical competency reached by the 24th case. Patient safety was not compromised during the learning process of trainees. Future research should include multi-institutional studies and simulation-based training to generalize findings and enhance surgical training programs.