Details

Autor(en) / Beteiligte

• Harji, Deena
• Aldajani, Nour
• Cauvin, Thomas
• Chauvet, Alexander
• Denost, Quentin

Titel

Parallel, component training in robotic total mesorectal excision

Ist Teil von

• Journal of robotic surgery, 2023-06, Vol.17 (3), p.1049-1055

Ort / Verlag

London: Springer London

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• There has been widespread adoption of robotic total mesorectal excision (TME) for rectal cancer in recent years. There is now increasing interest in training robotic novice surgeons in robotic TME surgery using the principles of component-based learning. The aims of our study were to assess the feasibility of delivering a structured, parallel, component-based, training curriculum to surgical trainees and fellows. A prospective pilot study was undertaken between January 2021 and May 2021. A dedicated robotic training pathway was designed with two trainees trained in parallel per each robotic case based on prior experience, training grade and skill set. Component parts of each operation were allocated by the robotic trainer prior to the start of each case. Robotic proficiency was assessed using the Global Evaluative Assessment of Robotic Skills (GEARS) and the EARCS Global Assessment Score (GAS). Three trainees participated in this pilot study, performing a combined number of 52 TME resections. Key components of all 52 TME operations were performed by the trainees. GEARS scores improved throughout the study, with a mean overall baseline score of 17.3 (95% CI 15.1–1.4) compared to an overall final assessment mean score of 23.8 (95% CI 21.6–25.9), p  = 0.003. The GAS component improved incrementally for all trainees at each candidate assessment ( p  < 0.001). Employing a parallel, component-based approach to training in robotic TME surgery is safe and feasible and can be used to train multiple trainees of differing grades simultaneously, whilst maintaining high-quality clinical outcomes.