Robotic-assisted partial nephrectomy with the Hugo-RAS system: Initial experience, surgical outcomes, and learning-curve assessment.

Introduction: Robotic-assisted partial nephrectomy (RAPN) is a standard approach for nephron-sparing surgery. The Hugo-RAS system is an emerging platform, but data on its outcomes and learning curve are limited. This study evaluates the safety, efficacy, and learning curve of RAPN using Hugo-RAS in a high-volume laparoscopic center. Material and methods: We analyzed 42 consecutive RAPN cases performed with the Hugo-RAS system from May 2023 to October 2024. Perioperative outcomes, renal function, and the learning curve were assessed. The primary endpoint was the "trifecta" (warm ischemia time <25 min, negative surgical margins, and no major complications). Learning curve analysis used Cumulative Sum Control Chart (CUSUM) methodology. Results: The median console time was 88 minutes (IQR: 74-107), with a docking time of 5 minutes (IQR: 240-420s). The trifecta rate was 83.3%, and no conversions occurred. Docking proficiency was achieved by the 5 Conclusions: The Hugo-RAS system allows for safe and effective RAPN with a rapid learning curve. Surgeons adapt quickly, achieving proficiency within a short number of cases. Further studies are needed to validate long-term outcomes and broader applicability.