Robotic-assisted approaches to GERD following sleeve gastrectomy

Sleeve gastrectomy (SG) is the most common bariatric operation in the United States but increases the incidence of gastroesophageal reflux disease (GERD). The aim of our study was to describe our experience with robotic-assisted management of intractable GERD after SG.

A systematic review of a prospectively maintained database was performed of consecutive patients undergoing robotic-assisted magnetic sphincter augmentation placement after sleeve gastrectomy (MSA-S group) or conversion to Roux-en-Y gastric bypass (RYGB group) for GERD from 2015 to 2019 at our tertiary- care bariatric center. These were compared to a consecutive group of patients undergoing robotic-assisted magnetic sphincter augmentation placement (MSA group) for GERD without a history of bariatric surgery from 2016 to 2019. The primary outcome was perioperative morbidity. Secondary outcomes were operative time (OT), 90-day re-intervention rate, length of stay, symptom resolution and weight change.

There were 51 patients included in this study; 18 patients in the MSA group, 13 patients in the MSA-S group, and 20 patients in the RYGB group. There was no significant difference in age, gender, ASA score, preoperative endoscopic findings, or DeMeester scores (P > 0.05). BMI was significantly higher in patients undergoing RYGB compared to MSA or MSA-S (P < 0.0001). There were significant differences in OT between the MSA and RYGB groups (P < 0.0001) and MSA-S and RYGB groups (P = 0.009), but not MSA group to MSA-S group (P = 0.51). There was no significant difference in intraoperative and postoperative morbidity (P = 1.0 and P = 0.60, respectively). 30-day morbidity: 5.6% (MSA), 15.4% (MSA-S) and 15% (RYGB). There was no difference on PPI discontinuation among groups, with more than 80% success rate in all.

The use of the robotic platform in the different approaches available for treatment of GERD after SG appears to be a feasible option with low morbidity and high success rate. Further data is needed to support our findings.