Andrea Gallioli1, Angelo Territo2, Romain Boissier2, Riccardo Campi3, Graziano Vignolini3, Mireia Musquera4, Antonio Alcaraz4, Karel Decaestecker5, Volkan Tugcu6, Davide Vanacore7, Sergio Serni3, Alberto Breda2. 1. Department of Urology, Fundaciò Puigvert, Autonomous University of Barcelona, Barcelona, Spain; Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Urology, Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy. Electronic address: andrea.gallioli@gmail.com. 2. Department of Urology, Fundaciò Puigvert, Autonomous University of Barcelona, Barcelona, Spain. 3. Department of Urological Robotic Surgery and Renal Transplantation, Careggi Hospital, University of Florence, Florence, Italy; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy. 4. Department of Urology, Hospital Clinic, Barcelona, Spain. 5. Department of Urology, Ghent University Hospital, Ghent, Belgium. 6. Department of Urology, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey. 7. Department of Urology, Fundaciò Puigvert, Autonomous University of Barcelona, Barcelona, Spain; Department of Urological Robotic Surgery and Renal Transplantation, Careggi Hospital, University of Florence, Florence, Italy.
Abstract
BACKGROUND: Recently, robot-assisted kidney transplantation (RAKT) was recently introduced as renal replacement mini-invasive surgery. OBJECTIVE: To report surgical technique, including tips and tricks, and the learning curve for RAKT. DESIGN, SETTING, AND PARTICIPANTS: All consecutive RAKTs performed in the five highest-volume centers of the European Robotic Urological Society RAKT group were reviewed, and a step-by-step description of the technique was compiled. SURGICAL PROCEDURE: Surgeries were performed with Da Vinci Si/Xi. The patient was placed in the lithotomy position. The Trendelenburg position was set at 20-30° and the robot was docked between the legs. MEASUREMENTS: Shewhart control charts and cumulative summation (CUSUM) graphs and trifecta were generated to assess the learning curve according to rewarming time (RWT), intra/postoperative complications, and renal graft function (glomerular filtration rate) on days 7 and 30, and at 1 yr. Linear regressions were performed to compare the learning curves of each surgeon. RESULTS AND LIMITATIONS: Arterial anastomosis time was below the alarm/alert line in 93.3%/88.9% of RAKTs, while venous anastomosis time was below the alarm/alert line in 88.9%/73.9%. The nonanastomotic RWT exceeded +3 standard deviation (SD) in 24.7% of procedures and +2SD in 37.1%. In only 46% cases, the RWT was below the alert line. The ureteroneocystostomy time was below +2SD and +3SD in 87.9% and 90.2% of cases, respectively. CUSUM showed that the learning curve for arterial anastomosis required up to 35 (mean = 16) cases. Complications and delayed graft function rates decreased significantly and reached a plateau after the first 20 cases. Trifecta was achieved in 75% (24/32) of the cases after the first 34 RAKTs in each center. CONCLUSIONS: A minimum of 35 cases are necessary to reach reproducibility in terms of RWT, complications, and functional results. PATIENT SUMMARY: Robot-assisted kidney transplantation requires a learning curve of 35 cases to achieve reproducibility in terms of timing, complications, and functional results. Synergy between the surgeon and the assistant is crucial to reduce rewarming time. High-grade complications and delayed graft function are rare after ten surgeries. Hands-on training and proctorship are highly recommended.
BACKGROUND: Recently, robot-assisted kidney transplantation (RAKT) was recently introduced as renal replacement mini-invasive surgery. OBJECTIVE: To report surgical technique, including tips and tricks, and the learning curve for RAKT. DESIGN, SETTING, AND PARTICIPANTS: All consecutive RAKTs performed in the five highest-volume centers of the European Robotic Urological Society RAKT group were reviewed, and a step-by-step description of the technique was compiled. SURGICAL PROCEDURE: Surgeries were performed with Da Vinci Si/Xi. The patient was placed in the lithotomy position. The Trendelenburg position was set at 20-30° and the robot was docked between the legs. MEASUREMENTS: Shewhart control charts and cumulative summation (CUSUM) graphs and trifecta were generated to assess the learning curve according to rewarming time (RWT), intra/postoperative complications, and renal graft function (glomerular filtration rate) on days 7 and 30, and at 1 yr. Linear regressions were performed to compare the learning curves of each surgeon. RESULTS AND LIMITATIONS: Arterial anastomosis time was below the alarm/alert line in 93.3%/88.9% of RAKTs, while venous anastomosis time was below the alarm/alert line in 88.9%/73.9%. The nonanastomotic RWT exceeded +3 standard deviation (SD) in 24.7% of procedures and +2SD in 37.1%. In only 46% cases, the RWT was below the alert line. The ureteroneocystostomy time was below +2SD and +3SD in 87.9% and 90.2% of cases, respectively. CUSUM showed that the learning curve for arterial anastomosis required up to 35 (mean = 16) cases. Complications and delayed graft function rates decreased significantly and reached a plateau after the first 20 cases. Trifecta was achieved in 75% (24/32) of the cases after the first 34 RAKTs in each center. CONCLUSIONS: A minimum of 35 cases are necessary to reach reproducibility in terms of RWT, complications, and functional results. PATIENT SUMMARY: Robot-assisted kidney transplantation requires a learning curve of 35 cases to achieve reproducibility in terms of timing, complications, and functional results. Synergy between the surgeon and the assistant is crucial to reduce rewarming time. High-grade complications and delayed graft function are rare after ten surgeries. Hands-on training and proctorship are highly recommended.
Authors: Julien Grammens; Michal Yaela Schechter; Liesbeth Desender; Tom Claeys; Céline Sinatti; Johan VandeWalle; Frank Vermassen; Ann Raes; Caroline Vanpeteghem; Agnieszka Prytula; Mesrur Selçuk Silay; Alberto Breda; Karel Decaestecker; Anne-Françoise Spinoit Journal: Front Surg Date: 2021-03-25