Andrea Moglia1, Vincenzo Ferrari2, Luca Morelli3, Mauro Ferrari4, Franco Mosca5, Alfred Cuschieri6. 1. EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Pisa, Italy. Electronic address: andrea.moglia@endocas.org. 2. EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Pisa, Italy; Information Engineering Department, University of Pisa, Pisa, Italy. 3. EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Pisa, Italy; Multidisciplinary Center for Robotic Surgery, University Hospital of Pisa, Pisa, Italy. 4. EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Pisa, Italy. 5. Cisanello Teaching Hospital, Pisa, Italy. 6. Scuola Superiore Sant'Anna, Pisa, Italy; Institute for Medical Science and Technology, University of Dundee, Dundee, UK.
Abstract
CONTEXT: No single large published randomized controlled trial (RCT) has confirmed the efficacy of virtual simulators in the acquisition of skills to the standard required for safe clinical robotic surgery. This remains the main obstacle for the adoption of these virtual simulators in surgical residency curricula. OBJECTIVE: To evaluate the level of evidence in published studies on the efficacy of training on virtual simulators for robotic surgery. EVIDENCE ACQUISITION: In April 2015 a literature search was conducted on PubMed, Web of Science, Scopus, Cochrane Library, the Clinical Trials Database (US) and the Meta Register of Controlled Trials. All publications were scrutinized for relevance to the review and for assessment of the levels of evidence provided using the classification developed by the Oxford Centre for Evidence-Based Medicine. EVIDENCE SYNTHESIS: The publications included in the review consisted of one RCT and 28 cohort studies on validity, and seven RCTs and two cohort studies on skills transfer from virtual simulators to robot-assisted surgery. Simulators were rated good for realism (face validity) and for usefulness as a training tool (content validity). However, the studies included used various simulation training methodologies, limiting the assessment of construct validity. The review confirms the absence of any consensus on which tasks and metrics are the most effective for the da Vinci Skills Simulator and dV-Trainer, the most widely investigated systems. Although there is consensus for the RoSS simulator, this is based on only two studies on construct validity involving four exercises. One study on initial evaluation of an augmented reality module for partial nephrectomy using the dV-Trainer reported high correlation (r=0.8) between in vivo porcine nephrectomy and a virtual renorrhaphy task according to the overall Global Evaluation Assessment of Robotic Surgery (GEARS) score. In one RCT on skills transfer, the experimental group outperformed the control group, with a significant difference in overall GEARS score (p=0.012) during performance of urethrovesical anastomosis on an inanimate model. Only one study included assessment of a surgical procedure on real patients: subjects trained on a virtual simulator outperformed the control group following traditional training. However, besides the small numbers, this study was not randomized. CONCLUSIONS: There is an urgent need for a large, well-designed, preferably multicenter RCT to study the efficacy of virtual simulation for acquisition competence in and safe execution of clinical robotic-assisted surgery. PATIENT SUMMARY: We reviewed the literature on virtual simulators for robot-assisted surgery. Validity studies used various simulation training methodologies. It is not clear which exercises and metrics are the most effective in distinguishing different levels of experience on the da Vinci robot. There is no reported evidence of skills transfer from simulation to clinical surgery on real patients.
CONTEXT: No single large published randomized controlled trial (RCT) has confirmed the efficacy of virtual simulators in the acquisition of skills to the standard required for safe clinical robotic surgery. This remains the main obstacle for the adoption of these virtual simulators in surgical residency curricula. OBJECTIVE: To evaluate the level of evidence in published studies on the efficacy of training on virtual simulators for robotic surgery. EVIDENCE ACQUISITION: In April 2015 a literature search was conducted on PubMed, Web of Science, Scopus, Cochrane Library, the Clinical Trials Database (US) and the Meta Register of Controlled Trials. All publications were scrutinized for relevance to the review and for assessment of the levels of evidence provided using the classification developed by the Oxford Centre for Evidence-Based Medicine. EVIDENCE SYNTHESIS: The publications included in the review consisted of one RCT and 28 cohort studies on validity, and seven RCTs and two cohort studies on skills transfer from virtual simulators to robot-assisted surgery. Simulators were rated good for realism (face validity) and for usefulness as a training tool (content validity). However, the studies included used various simulation training methodologies, limiting the assessment of construct validity. The review confirms the absence of any consensus on which tasks and metrics are the most effective for the da Vinci Skills Simulator and dV-Trainer, the most widely investigated systems. Although there is consensus for the RoSS simulator, this is based on only two studies on construct validity involving four exercises. One study on initial evaluation of an augmented reality module for partial nephrectomy using the dV-Trainer reported high correlation (r=0.8) between in vivo porcine nephrectomy and a virtual renorrhaphy task according to the overall Global Evaluation Assessment of Robotic Surgery (GEARS) score. In one RCT on skills transfer, the experimental group outperformed the control group, with a significant difference in overall GEARS score (p=0.012) during performance of urethrovesical anastomosis on an inanimate model. Only one study included assessment of a surgical procedure on real patients: subjects trained on a virtual simulator outperformed the control group following traditional training. However, besides the small numbers, this study was not randomized. CONCLUSIONS: There is an urgent need for a large, well-designed, preferably multicenter RCT to study the efficacy of virtual simulation for acquisition competence in and safe execution of clinical robotic-assisted surgery. PATIENT SUMMARY: We reviewed the literature on virtual simulators for robot-assisted surgery. Validity studies used various simulation training methodologies. It is not clear which exercises and metrics are the most effective in distinguishing different levels of experience on the da Vinci robot. There is no reported evidence of skills transfer from simulation to clinical surgery on real patients.
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