Skill Transfer from Laparoscopic Partial Nephrectomy to the Hugo™ RAS System: A Novel Proficiency Score to Assess Surgical Quality during the Learning Curve

Abstract

Background/Objectives: The absence of validated tools to assess the skill transfer from laparoscopy to robotic surgery remains an unsolved issue in the context of robot-assisted partial nephrectomy (RAPN). We aimed to describe and validate a novel proficiency score to critically evaluate the surgical quality of RAPN with the Hugo™ RAS System (Medtronic, Minneapolis, MN, USA). Methods: Between October 2022 and September 2023, 27 consecutive patients underwent off-clamp RAPN for localized renal tumors at our institution. To analyze the learning curve (LC), the cohort was chronologically divided into two phases of 6 months each. Proficiency was defined as the achievement of trifecta while maintaining a comparable intraoperative time in the interquartile range of laparoscopic partial nephrectomy performed by the same surgeon. A logistic binary regression model was built to identify predictors of proficiency achievement. Results: A proficiency score was achieved in 14 patients (74.1%). At univariable analysis, number of consecutive procedures > 12 (OR 13.7; 95%CI 2.05–21.1, p = 0.007), pathological tumor size (OR 0.92; 95%CI 0.89–0.99, p = 0.04) and essential blood hypertension (OR 0.16; 95%CI 0.03–0.82, p = 0.02) were found to be predictors of proficiency score. At multivariable analysis, after adjusting for potential confounding factors, number of consecutive procedures > 12 (OR 8.1; 95%CI 1.44–14.6, p = 0.03) was the only independent predictor of proficiency score achievement. Conclusions: Our results showed that the skills of an experienced laparoscopic surgeon are transferrable to the novel Hugo™ RAS System in the context of nephron-sparing surgery. Improved surgical quality may be expected after completing the first 12 consecutive procedures.