OGC P31 Learning curve for robot-assisted minimally invasive esophagectomy: A systematic review. (7th December 2022) - Pickering, Oliver; van Boxel, Gijs; Carter, Nick; Mercer, Stuart; Knight, Benjamin; Pucher, Philip
Abstract: Background: Robot- assisted minimally invasive esophagectomy (RAMIE) is gaining increasing popularity as an operative approach. Learning curves to achieve surgical competency in robotic-assisted techniques have shown significant variation in learning curve lengths and outcomes. It is vital to understand the impact of RAMIO implementation on patient outcomes during the initial adoption phase. This systematic review aims to summarise the current literature on learning curves for RAMIE. Methods: A systematic review was conducted in line with MOOSE (Meta-analyses Of Observational Studies in Epidemiology) guidelines. Electronic databases PubMed, MEDLINE, and Cochrane Library were searched, and articles reporting on learning curves in RAMIE were identified and scrutinized. Studies were included if an assessment of the learning curve was reported, regardless of statistical method was used. Results: Fifteen studies reporting on 1767 patients were included. Nine studies reported on surgeons with prior experience of robot-assisted surgery prior to adopting RAMIE, with only four studies outlining a specified RAMIO adoption pathway. Learning curves were most commonly reported for lymph node yields and operative times, with significant variation in learning curve lengths (18–73 cases and 20–80 cases respectively). Only a minority of studies (3/9) demonstrated learning curves for patient outcomes (30-day morbidity, 21–51 cases; vocal cord paralysis rates, 12–80 cases). Conclusions: RAMIE adoption appears possible with minimal impact on clinical outcomes. Robust training through formal programmes or proctorship may be crucial to minimise the adverse effects on operative efficiency and patient care.