Robotic-assisted Roux-en-Y gastric bypass: update from 2 high-volume centers
- PMID: 22361807
- DOI: 10.1016/j.soard.2011.11.022
Robotic-assisted Roux-en-Y gastric bypass: update from 2 high-volume centers
Abstract
Background: Laparoscopic Roux-en-Y gastric bypass (RYGB) is a challenging operation in the most experienced hands. Robotic surgery allows the capabilities of the minimally invasive surgeon to be extended. An increasing number of robotic gastric bypasses are being performed each year with the assumption that the complication rates are decreased. The objectives of the present study were to review the results of robotic-assisted RYGB (RARYGB) from 2 high-volume centers, including 1 university and 1 private practice.
Methods: We report the most recently compiled, largest series of RARYGB in the world to show the effectiveness, morbidity, and mortality of this method. Databases were searched for patients undergoing RARYGB from 2002 to 2010, and the endpoints were recorded.
Results: A total of 1100 RARYGBs matched our search. The patients had a mean preoperative age of 46.9 years, mean weight of 131.9 kg, and mean body mass index of 47.9 kg/m(2). The mean operative time was 155 minutes. There were no conversions. The mean body mass index was 39.8 kg/m(2) at 3 months postoperatively (79% follow-up). Complications were few, and included 2 cases of pulmonary embolism (.19%), 3 cases of deep venous thrombosis (.27%), 1 case of gastrojejunal anastomotic leak (.09%), and 9 cases of staple line bleeding (.82%). No patients died.
Conclusion: RARYGB is safe and effective. Although the operative time might be increased, the complication rates, most notably of anastomotic leak, are extremely low.
Copyright © 2013 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.
Comment in
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Comment on: Robotic-assisted Roux-en-Y gastric bypass: update from 2 high-volume centers.Surg Obes Relat Dis. 2013 Mar-Apr;9(2):288-9. doi: 10.1016/j.soard.2012.01.005. Epub 2012 Jan 16. Surg Obes Relat Dis. 2013. PMID: 22342765 No abstract available.
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