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

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.

Keywords: Kidney transplantation; Learning curve; Regional hypothermia; Robot-assisted kidney transplantation; Robotic surgery; Vascular anastomosis.