Robot‐assisted partial nephrectomy using the Hugo™ RAS System: first multicentre study and Tetrafecta achievement
Francesco Prata, Paolo Dell’Oglio, Angelo Mottaran, Riccardo Bertolo, Stefano Tappero, Pietro Piazza, Francesca Montanaro, Alessandro Veccia, Alberto Ragusa, Alberto Caviglia, Francesco Tedesco, Angelo Civitella, Andrea Iannuzzi, Tommaso Saccucci, Giovanni Muto, Aldo Massimo Bocciardi, Eugenio Brunocilla, Roberto Mario Scarpa, Alessandro Antonelli, Riccardo Schiavina
- Year
- 2025
- Citations
- 3
- Access
- Open access
Abstract
OBJECTIVE: To evaluate the perioperative outcomes and the rate of Tetrafecta achievement in robot-assisted partial nephrectomy (RAPN) cases performed using the Hugo™ robot-assisted surgery (RAS) system (Medtronic, Minneapolis, MN, USA). PATIENTS AND METHODS: Data from five tertiary care referral centres performing RAPN with the Hugo RAS System since October 2022 were collected. For the study purpose, a novel Tetrafecta was defined as a proxy for surgical quality. This included the coexistence of negative surgical margins, absence of intraoperative and Clavien-Dindo Grade ≥II postoperative complications, and 90-day decline in estimated glomerular filtration rate of no more than 30% from baseline. RESULTS: A total of 140 patients, who underwent RAPN with the Hugo RAS system, were included. The median (interquartile range [IQR]) docking, console, and total operative times were 5 (4-7) min, 79 (45.5-135) min, and 150 (96-205) min, respectively. The median (IQR) estimated blood loss was 150 (100-300) mL. No additional port placements were required, and no conversions to open surgery occurred. Overall, postoperative complications were observed in 20.7% of cases, 5% of which were classified as major (Clavien-Dindo Grade >II). Tetrafecta was achieved in 80% of cases. Multivariate logistic regression analysis showed that R.E.N.A.L. (Radius, Exophytic/Endophytic, Nearness to collecting system or sinus, Anterior/Posterior, Location) nephrometry score (odds ratio [OR] 0.69; P = 0.01) and Hugo RAS surgical experience (OR 1.03; P = 0.02) were independent predictors of Tetrafecta achievement. CONCLUSIONS: Relying on the largest multicentre series, our findings demonstrate that this novel robotic platform enables safe and effective RAPN, achieving a satisfactory Tetrafecta rate. These results would support the adoption of the Hugo RAS system to perform RAPN.
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