BACKGROUND: Although currently limited, the requirement for colorectal trainees to attain skills in robotic surgery is likely to increase due to further utilization of robotic platforms globally. The aim of the study is to describe the training programme utilized and assess outcomes of fellowship training in robotic colorectal surgery. METHODS: A structured robotic training programme was generated across a tertiary hospital setting. Review of four prospectively maintained fellow operative logbooks was performed to assess caseload and skill acquisition. Operative and patient-related outcomes were compared with consultant trainer performed cases. Data were analysed using R with a P < 0.05 considered significant. RESULTS: The structured robotic training scheme is a two-tiered system over a 12-month period. The trainer-directed pathway comprised of a robotic console safety course followed by cart-side assisting, a wet lab animal course, dual-console accreditation training course and onsite proctoring, prior to becoming an independent console surgeon. Over 2 years, 265 robotic (n = 143 primary/component surgeon) cases were undertaken with fellows A, B, C and D involved in 63, 77, 75 and 50 robotic colorectal cases, respectively. Individual learning curves revealed independent procedure competency at cases 11, 14, 15 and 12, respectively, for robotic anterior resection. There was no significant difference observed in operative time (P = 0.39), blood loss (P = 0.41), lymph node harvest (P = 0.35), conversion rates (2% versus 4%), anastomotic leaks (1% versus 3%) and R0 resection rates (100% versus 98% colonic, 96% versus 96% rectal, P = 0.48) between surgical fellows and consultant trainers. Clavien-Dindo(III-IV) complications were similar (10% versus 6%,P = 0.25) with no mortalities encountered. CONCLUSION: It is feasible and safe to train fellows in robotic colorectal surgery without compromise of operative- and patient-related outcomes.
BACKGROUND: Although currently limited, the requirement for colorectal trainees to attain skills in robotic surgery is likely to increase due to further utilization of robotic platforms globally. The aim of the study is to describe the training programme utilized and assess outcomes of fellowship training in robotic colorectal surgery. METHODS: A structured robotic training programme was generated across a tertiary hospital setting. Review of four prospectively maintained fellow operative logbooks was performed to assess caseload and skill acquisition. Operative and patient-related outcomes were compared with consultant trainer performed cases. Data were analysed using R with a P < 0.05 considered significant. RESULTS: The structured robotic training scheme is a two-tiered system over a 12-month period. The trainer-directed pathway comprised of a robotic console safety course followed by cart-side assisting, a wet lab animal course, dual-console accreditation training course and onsite proctoring, prior to becoming an independent console surgeon. Over 2 years, 265 robotic (n = 143 primary/component surgeon) cases were undertaken with fellows A, B, C and D involved in 63, 77, 75 and 50 robotic colorectal cases, respectively. Individual learning curves revealed independent procedure competency at cases 11, 14, 15 and 12, respectively, for robotic anterior resection. There was no significant difference observed in operative time (P = 0.39), blood loss (P = 0.41), lymph node harvest (P = 0.35), conversion rates (2% versus 4%), anastomotic leaks (1% versus 3%) and R0 resection rates (100% versus 98% colonic, 96% versus 96% rectal, P = 0.48) between surgical fellows and consultant trainers. Clavien-Dindo(III-IV) complications were similar (10% versus 6%,P = 0.25) with no mortalities encountered. CONCLUSION: It is feasible and safe to train fellows in robotic colorectal surgery without compromise of operative- and patient-related outcomes.
Authors: Deena Harji; Fergus Houston; Joshua Burke; Ben Griffiths; Henry Tilney; Danilo Miskovic; Charles Evans; Jim Khan; Naeem Soomro; Simon P Bach Journal: J Robot Surg Date: 2022-06-03
Authors: Arjun Nathan; Sonam Patel; Maria Georgi; Monty Fricker; Aqua Asif; Alexander Ng; William Mullins; Man Kien Hang; Alexander Light; Senthil Nathan; Nader Francis; John Kelly; Justin Collins; Ashwin Sridhar Journal: J Robot Surg Date: 2022-10-17