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The robotic colorectal experience: an outcomes and learning curve analysis of 502 patients.
Parascandola, Salvatore A; Horsey, Michael L; Hota, Salini; Paull, Jessie Osborne; Graham, Ada; Pudalov, Natalie; Smith, Savannah; Amdur, Richard; Obias, Vincent.
Afiliação
  • Parascandola SA; Walter Reed National Military Medical Center, Bethesda, MD, USA.
  • Horsey ML; Walter Reed National Military Medical Center, Bethesda, MD, USA.
  • Hota S; Eastern Virginia Medical School, Norfolk, VA, USA.
  • Paull JO; Walter Reed National Military Medical Center, Bethesda, MD, USA.
  • Graham A; Department of Colorectal Surgery, George Washington University Hospital, Washington, DC, USA.
  • Pudalov N; George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
  • Smith S; George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
  • Amdur R; Department of Surgery, George Washington University Medical Faculty Associates, Washington, DC, USA.
  • Obias V; Department of Surgery, George Washington University Medical Faculty Associates, Washington, DC, USA.
Colorectal Dis ; 23(1): 226-236, 2021 Jan.
Article em En | MEDLINE | ID: mdl-33048409
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.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Neoplasias Retais / Laparoscopia / Procedimentos Cirúrgicos Robóticos Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Colorectal Dis Assunto da revista: GASTROENTEROLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Neoplasias Retais / Laparoscopia / Procedimentos Cirúrgicos Robóticos Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Colorectal Dis Assunto da revista: GASTROENTEROLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos