Use of robot-assisted surgery is increasing since its advent in the 1990s. Robotic surgical training is the subject of much interest. Robotic technology would seem to facilitate training allowing more rapid attainment of competence. The safety and success of a particular surgical team depends on adequacy of training of its members. A learning curve is a way of describing the changes observed in surgical outcomes with increasing experience of the surgeon and can be used to plan training programs. The majority of published papers regarding learning curves are retrospective with small numbers of surgeons with different levels of experience comparing a variety of different outcomes. In this review, we describe the published literature on learning curves in robotic urological surgery, with the aim of offering a guide to both experienced and naïve surgeons who plan to learn new robotic procedure.

The presence of preoperative anemia in patients undergoing iRARC is not associated with increased surgical risk, although preoperative anemic patients were significantly more likely to require blood transfusion. Blood transfusion requirement and specifically postoperative blood transfusion are independently associated with perioperative morbidity and are an important factor for the optimization of postoperative outcomes.

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