Learning Curve in Robot-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group

Andrea Gallioli, Angelo Territo, Romain Boissier, Riccardo Campi, Graziano Vignolini, Mireia Musquera, Antonio Alcaraz, Karel Decaestecker, Volkan Tugcu, Davide Vanacore, Sergio Serni, Alberto Breda

Research output: Contribution to journalArticlepeer-review

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. Robot-assisted kidney transplantation (RAKT) requires a learning curve of 35 cases. Teamwork is crucial to reduce rewarming time. High-grade complications are rare after ten surgeries; functional results are significantly better after 20 cases of RAKT. Hands-on training/proctorship is highly recommended.

Original languageEnglish
JournalEuropean Urology
DOIs
Publication statusAccepted/In press - Jan 1 2020
Externally publishedYes

Keywords

  • Kidney transplantation
  • Learning curve
  • Regional hypothermia
  • Robot-assisted kidney transplantation
  • Robotic surgery
  • Vascular anastomosis

ASJC Scopus subject areas

  • Urology

Fingerprint

Dive into the research topics of 'Learning Curve in Robot-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group'. Together they form a unique fingerprint.

Cite this