Due to its advantages over open surgery and conventional laparoscopy, uptake of robot-assisted surgery has rapidly increased. It is important to know whether the existing open or laparoscopic skills of robotic novices shorten the robotic surgery learning curve, potentially reducing the amount of training required. This systematic review aims to assess psychomotor skill transfer to the robot in clinical and simulated settings. PubMed, EMBASE, Cochrane Library and Scopus databases were systematically searched in accordance with PRISMA guidelines from inception to August 2021 alongside website searching and citation chaining. Article screening, data extraction and quality assessment were undertaken by two independent reviewers. Outcomes included simulator performance metrics or in the case of clinical studies, peri- and post-operative metrics. Twenty-nine studies met the eligibility criteria. All studies were judged to be at high or moderate overall risk of bias. Results were narratively synthesised due to heterogeneity in study designs and outcome measures. Two of the three studies assessing open surgical skill transfer found evidence of successful skill transfer while nine of twenty-seven studies evaluating laparoscopic skill transfer found no evidence. Skill transfer from both modalities is most apparent when advanced robotic tasks are performed in the initial phase of the learning curve but quality and methodological limitations of the existing literature prevent definitive conclusions. The impact of incorporating laparoscopic simulation into robotic training curricula and on the cost effectiveness of training should be investigated.
Background: Urology has been at the forefront of adopting laparoscopic and robot-assisted techniques to improve patient outcomes. This systematic review aimed to examine the literature relating to the learning curves of major urological robotic and laparoscopic procedures. Methods: In accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search strategy was employed across PubMed, EMBASE, and the Cochrane Library from inception to December 2021, alongside a search of the grey literature. Two independent reviewers completed the article screening and data extraction stages using the Newcastle–Ottawa Scale as a quality assessment tool. The review was reported in accordance with AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. Results: Of 3702 records identified, 97 eligible studies were included for narrative synthesis. Learning curves are mapped using an array of measurements including operative time (OT), estimated blood loss, complication rates as well as procedure-specific outcomes, with OT being the most commonly used metric by eligible studies. The learning curve for OT was identified as 10–250 cases for robot-assisted laparoscopic prostatectomy and 40–250 for laparoscopic radical prostatectomy. The robot-assisted partial nephrectomy learning curve for warm ischaemia time is 4–150 cases. No high-quality studies evaluating the learning curve for laparoscopic radical cystectomy and for robotic and laparoscopic retroperitoneal lymph node dissection were identified. Conclusion: There was considerable variation in the definitions of outcome measures and performance thresholds, with poor reporting of potential confounders. Future studies should use multiple surgeons and large sample sizes of cases to identify the currently undefined learning curves for robotic and laparoscopic urological procedures.
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