Salvatore A Parascandola1, Michael L Horsey1, Salini Hota2, Jessie Osborne Paull1, Ada Graham3, Natalie Pudalov4, Savannah Smith4, Richard Amdur5, Vincent Obias5. 1. Walter Reed National Military Medical Center, Bethesda, MD, USA. 2. Eastern Virginia Medical School, Norfolk, VA, USA. 3. Department of Colorectal Surgery, George Washington University Hospital, Washington, DC, USA. 4. George Washington University School of Medicine and Health Sciences, Washington, DC, USA. 5. Department of Surgery, George Washington University Medical Faculty Associates, Washington, DC, USA.
Abstract
AIM: This study aimed to present our experience with robotic colorectal surgery since its establishment at our institution in 2009. By examining the outcomes of over 500 patients, our experience provides a basis for assessing the introduction of a robotic platform in a colorectal practice. Specific measures investigated include intraoperative data and postoperative outcomes for all operations using the robotic platform. In addition, for our most commonly performed operations we wished to analyse the learning curve to improve operative proficiency. This is the largest single-surgeon robotic database analysed to date. METHOD: A prospectively maintained database of patients who underwent robotic colorectal surgery by a single surgeon at the George Washington University Hospital was retrospectively reviewed. Demographic data and perioperative outcomes were assessed. Additionally, an operating time learning curve analysis was performed. RESULTS: Inclusion criteria identified 502 patients who underwent robotic colorectal surgery between October 2009 and December 2018. The most common indications for surgery were diverticulitis (22.9%), colon adenocarcinoma (22.1%) and rectal adenocarcinoma (19.5%). The most common operations were anterior/low anterior resection (33.9%), right hemicolectomy/ileocaecectomy (24.9%) and left hemicolectomy/sigmoidectomy (21.9%). The rate of conversion to open surgery was 4.8%. The most common postoperative complications were wound infection (5.0%), anastomotic leakage (4.0%) and abscess formation (2.8%). The operating time learning curve plateaued at 55-65 cases for anterior and low anterior resection and 35-45 cases for left hemicolectomy and sigmoidectomy. A clear learning curve was not seen in right hemicolectomy. CONCLUSION: Robotic-assisted surgery can be performed in a diverse colorectal practice with low rates of conversion and postoperative complications. Plateau performance was achieved after 65 anterior/low anterior resections and 45 left and sigmoid colectomies.
AIM: This study aimed to present our experience with robotic colorectal surgery since its establishment at our institution in 2009. By examining the outcomes of over 500 patients, our experience provides a basis for assessing the introduction of a robotic platform in a colorectal practice. Specific measures investigated include intraoperative data and postoperative outcomes for all operations using the robotic platform. In addition, for our most commonly performed operations we wished to analyse the learning curve to improve operative proficiency. This is the largest single-surgeon robotic database analysed to date. METHOD: A prospectively maintained database of patients who underwent robotic colorectal surgery by a single surgeon at the George Washington University Hospital was retrospectively reviewed. Demographic data and perioperative outcomes were assessed. Additionally, an operating time learning curve analysis was performed. RESULTS: Inclusion criteria identified 502 patients who underwent robotic colorectal surgery between October 2009 and December 2018. The most common indications for surgery were diverticulitis (22.9%), colon adenocarcinoma (22.1%) and rectal adenocarcinoma (19.5%). The most common operations were anterior/low anterior resection (33.9%), right hemicolectomy/ileocaecectomy (24.9%) and left hemicolectomy/sigmoidectomy (21.9%). The rate of conversion to open surgery was 4.8%. The most common postoperative complications were wound infection (5.0%), anastomotic leakage (4.0%) and abscess formation (2.8%). The operating time learning curve plateaued at 55-65 cases for anterior and low anterior resection and 35-45 cases for left hemicolectomy and sigmoidectomy. A clear learning curve was not seen in right hemicolectomy. CONCLUSION: Robotic-assisted surgery can be performed in a diverse colorectal practice with low rates of conversion and postoperative complications. Plateau performance was achieved after 65 anterior/low anterior resections and 45 left and sigmoid colectomies.
Authors: Jörn-Markus Gass; Diana Daume; Fiorenzo Angehrn; Martin Bolli; Romano Schneider; Daniel Steinemann; Francesco Mongelli; Andreas Scheiwiller; Lana Fourie; Beatrice Kern; Markus von Flüe; Jürg Metzger Journal: Surg Endosc Date: 2022-01-13 Impact factor: 3.453