BACKGROUND: Laparoscopic Roux-en-Y gastric bypass (LRYGBP) is a technically demanding procedure, with a long learning curve. The aim of this study was three-fold: to develop a task-based approach to training in LRYGBP, define a tool for objective technical skills assessments, and objectively determine the efficacy of this approach. METHODS: Videos of expert and novice surgeons performing LRYGBP on patients and anesthetised porcine models were analyzed to define an appropriate task for skills assessment. Subsequently, a jejuno-jejunostomy model was developed using cadaveric porcine small bowel, placed into a video-box trainer. 27 surgeons of varying experience levels in advanced laparoscopic procedures performed the task. Assessments of technical skill were by hand motion analysis and video-based scoring. A further 16 surgeons inexperienced in LRYGBP attended a task-based hands-on training course and performed the jejuno-jejunostomy task at start and end of the course. RESULTS: The jejuno-jejunostomy model differentiated between surgeons of varying experience levels for time taken (P<0.001), economy of movement (P=0.001) and video scores (P<0.001). Surgeons attending the training course made significant improvements in time taken (P=0.002) and economy of movement (P=0.006), although not for generic video scores (P=0.243) by the end of course. CONCLUSIONS: The structured, task-based approach for commencement of training in LRYGBP leads to objective improvements in the technical skills of inexperienced surgeons at the end of a short course. The next stage of the curriculum should be to achieve proficiency in the complete procedure on an anesthetised porcine model, prior to preceptorship on human cases.
BACKGROUND: Laparoscopic Roux-en-Y gastric bypass (LRYGBP) is a technically demanding procedure, with a long learning curve. The aim of this study was three-fold: to develop a task-based approach to training in LRYGBP, define a tool for objective technical skills assessments, and objectively determine the efficacy of this approach. METHODS: Videos of expert and novice surgeons performing LRYGBP on patients and anesthetised porcine models were analyzed to define an appropriate task for skills assessment. Subsequently, a jejuno-jejunostomy model was developed using cadaveric porcine small bowel, placed into a video-box trainer. 27 surgeons of varying experience levels in advanced laparoscopic procedures performed the task. Assessments of technical skill were by hand motion analysis and video-based scoring. A further 16 surgeons inexperienced in LRYGBP attended a task-based hands-on training course and performed the jejuno-jejunostomy task at start and end of the course. RESULTS: The jejuno-jejunostomy model differentiated between surgeons of varying experience levels for time taken (P<0.001), economy of movement (P=0.001) and video scores (P<0.001). Surgeons attending the training course made significant improvements in time taken (P=0.002) and economy of movement (P=0.006), although not for generic video scores (P=0.243) by the end of course. CONCLUSIONS: The structured, task-based approach for commencement of training in LRYGBP leads to objective improvements in the technical skills of inexperienced surgeons at the end of a short course. The next stage of the curriculum should be to achieve proficiency in the complete procedure on an anesthetised porcine model, prior to preceptorship on human cases.
Authors: Gerald M Fried; Liane S Feldman; Melina C Vassiliou; Shannon A Fraser; Donna Stanbridge; Gabriela Ghitulescu; Christopher G Andrew Journal: Ann Surg Date: 2004-09 Impact factor: 12.969
Authors: Lars Sjöström; Anna-Karin Lindroos; Markku Peltonen; Jarl Torgerson; Claude Bouchard; Björn Carlsson; Sven Dahlgren; Bo Larsson; Kristina Narbro; Carl David Sjöström; Marianne Sullivan; Hans Wedel Journal: N Engl J Med Date: 2004-12-23 Impact factor: 91.245
Authors: Garth H Ballantyne; Douglas Ewing; Rafael F Capella; Joseph F Capella; Dan Davis; Hans J Schmidt; Annette Wasielewski; Richard J Davies Journal: Obes Surg Date: 2005-02 Impact factor: 4.129