| Literature DB >> 36074220 |
Marc M Huttman1,2, Harry F Robertson3, Alexander N Smith4, Sarah E Biggs5, Ffion Dewi5, Lauren K Dixon1,5, Emily N Kirkham1,6, Conor S Jones1,7, Jozel Ramirez1,5, Darren L Scroggie1, Benjamin E Zucker1,5, Samir Pathak1,8, Natalie S Blencowe9.
Abstract
Robot-assisted anti-reflux surgery (RA-ARS) is increasingly being used to treat refractory gastro-oesophageal reflux disease. The IDEAL (Idea, Development, Exploration, Assessment, Long-term follow up) Collaboration's framework aims to improve the evaluation of surgical innovation, but the extent to which the evolution of RA-ARS has followed this model is unclear. This study aims to evaluate the standard to which RA-ARS has been reported during its evolution, in relation to the IDEAL framework. A systematic review from inception to June 2020 was undertaken to identify all primary English language studies pertaining to RA-ARS. Studies of paraoesophageal or giant hernias were excluded. Data extraction was informed by IDEAL guidelines and summarised by narrative synthesis. Twenty-three studies were included: two case reports, five case series, ten cohort studies and six randomised controlled trials. The majority were single-centre studies comparing RA-ARS and laparoscopic Nissen fundoplication. Eleven (48%) studies reported patient selection criteria, with high variability between studies. Few studies reported conflicts of interest (30%), funding arrangements (26%), or surgeons' prior robotic experience (13%). Outcome reporting was heterogeneous; 157 distinct outcomes were identified. No single outcome was reported in all studies.The under-reporting of important aspects of study design and high degree of outcome heterogeneity impedes the ability to draw meaningful conclusions from the body of evidence. There is a need for further well-designed prospective studies and randomised trials, alongside agreement about outcome selection, measurement and reporting for future RA-ARS studies.Entities:
Keywords: Anti-reflux surgery; Fundoplication; IDEAL framework; Outcome reporting; Robotic surgery
Year: 2022 PMID: 36074220 DOI: 10.1007/s11701-022-01453-2
Source DB: PubMed Journal: J Robot Surg ISSN: 1863-2483