Matthew Valdis1, Michael W A Chu2, Christopher Schlachta3, Bob Kiaii2. 1. Division of Cardiac Surgery, Department of Surgery, Western University, London Health Sciences Centre, London, Ontario, Canada. Electronic address: matthew.valdis@gmail.com. 2. Division of Cardiac Surgery, Department of Surgery, Western University, London Health Sciences Centre, London, Ontario, Canada. 3. Division of General Surgery, Department of Surgery, Western University, London Health Sciences Centre, London, Ontario, Canada.
Abstract
OBJECTIVE: To compare the currently available simulation training modalities used to teach robotic surgery. METHODS:Forty surgical trainees completed a standardized robotic 10-cm dissection of the internal thoracic artery and placed 3 sutures of a mitral valve annuloplasty in porcine models and were then randomized to a wet lab, a dry lab, a virtual reality lab, or a control group that received no additional training. All groups trained to a level of proficiency determined by 2 expert robotic cardiac surgeons. All assessments were evaluated using the Global Evaluative Assessment of Robotic Skills in a blinded fashion. RESULTS: Wet lab trainees showed the greatest improvement in time-based scoring and the objective scoring tool compared with the experts (mean, 24.9 ± 1.7 vs 24.9 ± 2.6; P = .704). The virtual reality lab improved their scores and met the level of proficiency set by our experts for all primary outcomes (mean, 24.9 ± 1.7 vs 22.8 ± 3.7; P = .103). Only the control group trainees were not able to meet the expert level of proficiency for both time-based scores and the objective scoring tool (mean, 24.9 ± 1.7 vs 11.0 ± 4.5; P < .001). The average duration of training was shortest for the dry lab and longest for the virtual reality simulation (1.6 hours vs 9.3 hours; P < .001). CONCLUSIONS: We have completed the first randomized controlled trial to objectively compare the different training modalities of robotic surgery. Our data demonstrate the significant benefits of wet lab and virtual reality robotic simulation training and highlight key differences in current training methods. This study can help guide training programs in investing resources in cost-effective, high-yield simulation exercises.
RCT Entities:
OBJECTIVE: To compare the currently available simulation training modalities used to teach robotic surgery. METHODS: Forty surgical trainees completed a standardized robotic 10-cm dissection of the internal thoracic artery and placed 3 sutures of a mitral valve annuloplasty in porcine models and were then randomized to a wet lab, a dry lab, a virtual reality lab, or a control group that received no additional training. All groups trained to a level of proficiency determined by 2 expert robotic cardiac surgeons. All assessments were evaluated using the Global Evaluative Assessment of Robotic Skills in a blinded fashion. RESULTS: Wet lab trainees showed the greatest improvement in time-based scoring and the objective scoring tool compared with the experts (mean, 24.9 ± 1.7 vs 24.9 ± 2.6; P = .704). The virtual reality lab improved their scores and met the level of proficiency set by our experts for all primary outcomes (mean, 24.9 ± 1.7 vs 22.8 ± 3.7; P = .103). Only the control group trainees were not able to meet the expert level of proficiency for both time-based scores and the objective scoring tool (mean, 24.9 ± 1.7 vs 11.0 ± 4.5; P < .001). The average duration of training was shortest for the dry lab and longest for the virtual reality simulation (1.6 hours vs 9.3 hours; P < .001). CONCLUSIONS: We have completed the first randomized controlled trial to objectively compare the different training modalities of robotic surgery. Our data demonstrate the significant benefits of wet lab and virtual reality robotic simulation training and highlight key differences in current training methods. This study can help guide training programs in investing resources in cost-effective, high-yield simulation exercises.
Authors: Stepan Cerny; Wouter Oosterlinck; Burak Onan; Sandeep Singh; Patrique Segers; Cengiz Bolcal; Cem Alhan; Emiliano Navarra; Matteo Pettinari; Frank Van Praet; Herbert De Praetere; Jan Vojacek; Theodor Cebotaru; Paul Modi; Fabien Doguet; Ulrich Franke; Ahmed Ouda; Ludovic Melly; Ghislain Malapert; Louis Labrousse; Monica Gianoli; Alfonso Agnino; Tine Philipsen; Jean-Luc Jansens; Thierry Folliguet; Meindert Palmen; Daniel Pereda; Francesco Musumeci; Piotr Suwalski; Koen Cathenis; Jef Van den Eynde; Johannes Bonatti Journal: Front Cardiovasc Med Date: 2022-01-20