PubMed | The Bristol Urological Institute and Albert Ludwigs University of Freiburg
Type: Journal Article | Journal: Arab journal of urology | Year: 2015
To define the learning curve of robot-assisted laparoscopic surgery for prostatectomy (RALP) and upper tract procedures, and show the differences between the classical approach to training and the new concept of parallel learning.This mini-review is based on the results of a Medline search using the keywords da Vinci, robot-assisted laparoscopic surgery, training, teaching and learning curve.For RALP and robot-assisted upper tract surgery, a learning curve of 8-150 procedures is quoted, with most articles proposing that 30-40 cases are needed to carry out the procedure safely. There is no consensus about which endpoints should be measured. In the traditional proctored training model, the surgeon learns the procedure linearly, following the sequential order of the surgical steps. A more recent approach is to specify the relative difficulty of each step and to train the surgeon simultaneously in several steps of equal difficulty. The entire procedure is only performed after all the steps are mastered in a timely manner. Recently, a warm-up before robotic surgery has been shown to be beneficial for successful surgery in the operating room.There is no clear definition of the duration of the effective learning curve for RALP and robotic upper tract surgery. The concept of stepwise, parallel learning has the potential to accelerate the learning process and to make sure that initial cases are not too long. It can also be assumed that a preoperative warm up could help significantly to improve the progress of the trainee.
PubMed | The Bristol Urological Institute, Eastbourne Hospital, St Georges Hospital and East Surrey Hospital
Type: Journal Article | Journal: Journal of robotic surgery | Year: 2016
Although the advantages of laparoscopic surgery are well documented, one disadvantage is that, for optimum performance, an experienced camera driver is required who can provide the necessary views for the operating surgeon. In this paper we describe our experience with urological laparoscopic techniques using the novel EndoAssist robotic camera holder and review the current status of alternative devices. A total of 51 urological procedures (25 using the EndoAssist device and 26 using a conventional human camera driver) conducted by three experienced surgeons were studied prospectively, including nephrectomy (simple and radical), pyeloplasty, radical prostatectomy, and radical cystoprostatectomy. The surgeon noted the extent of body comfort and muscle fatigue in each case. Other aspects documented were ease of scope movement, i.e. usability, need to clean the telescope, time of set-up, surgical performance, and whether it was necessary to change the position of the arm during the surgery. All three surgeons involved in the evaluation felt comfortable throughout all procedures, with no loss of autonomy. It was, however, obvious that the large arc generated whilst doing a nephrectomy led to more episodes of lens cleaning, and the arm had to be relocated on some occasions. Clearer benefits were seen while performing pelvic surgery or pyeloplasty, perhaps because the arc of movement was smaller. The EndoAssist is an effective, easy to use device for robotic camera driving which reduces the constraint of having to have an experienced camera driver for optimum visualisation during laparoscopic urological procedures.