Redefining The Learning Curve For Robotic Ivor Lewis Esophagectomy | 81240
ISSN: 2161-069X

Journal of Gastrointestinal & Digestive System
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Recommended Conferences
Google scholar citation report
Citations : 1337

Journal of Gastrointestinal & Digestive System received 1337 citations as per google scholar report

Journal of Gastrointestinal & Digestive System peer review process verified at publons
Indexed In
  • Index Copernicus
  • Google Scholar
  • Sherpa Romeo
  • Open J Gate
  • Genamics JournalSeek
  • China National Knowledge Infrastructure (CNKI)
  • Electronic Journals Library
  • RefSeek
  • Hamdard University
  • OCLC- WorldCat
  • SWB online catalog
  • Virtual Library of Biology (vifabio)
  • Publons
  • Geneva Foundation for Medical Education and Research
  • Euro Pub
Share This Page

Redefining the learning curve for robotic Ivor Lewis esophagectomy

Co-Organized Event 13th International Conference on Clinical Gastroenterology & Hepatology & 2nd International Conference on Digestive Diseases

Meredith Kenneth

Florida State University College of Medicine, USA

ScientificTracks Abstracts: J Gastrointest Dig Syst

DOI: 10.4172/2161-069X-C1-058

Background: Minimally invasive esophagectomy (MIE) has demonstrated superior outcomes compared to open approaches. The myriad of techniques has precluded the recommendation of a standard approach. The robotic approach has increased steadily and we have previously published our series defining the learning curve for this approach. The purpose of this study is to redefine the learning curve for robotic-assisted esophagogastrectomy with respect to operative time, conversion rates, and patient safety. Methods: We have prospectively followed all patients undergoing robotic-assisted esophagogastrectomy and compared operations performed at our institutions by a single surgeon in successive cohorts. Our measures of proficiency included: operative times, conversion rates, and complications. Statistical analyses were undertaken utilizing Spearman regression analysis and Mann-Whitney U test. Significance was accepted with 95% confidence. Results: We identified 203 patients (166 (81.8%) male: 37 (18.2%) female) with a median age of 67.2 (30-90) years who underwent robotic-assisted esophagogastrectomy for malignant esophageal disease. One-hundred sixty six were adenocarcinoma, 26 were squamous cell carcinoma and 11 were other. R0 resections was performed in 202 (99.5%) of patients. The median lymph node harvest was 18 (6-63) and neoadjuvant chemoradiation was administered to 157 (77.4 %) patients. A significant reduction in operative times (p<0.005) following completion of 20 procedures was identified (514 ±106 min vs. 415± 91 min compared to subsequent 80 cases and further reduced with the subsequent 100 cases 397±71.9 min) p<0.001. Complications decreased after the initial learning curve of 29 cases, p=0.04. However there was an increase in complications after 90 cases in which there was an increase in the Charleson morbidity index, p<0.01 indicating higher risk patients which tapered after case 115. Conclusions: For surgeons proficient in performing minimally-invasive esophagogastrectomies, the learning curve for a robotic-assisted procedure appears to begin near proficiency after 20 cases however as more complex cases are undertaken there appears to be an additional learning curve which is surpassed after 115 cases. Recent Publications 1. Kothari N, Mellon E, Frakes J, Hoffe S, Shridhar R, Pimiento J, Tram N, Saeed N, Meredith K L and Almhanna K (2016) Outcomes in patients with brain metastasis from esophageal cancer. Journal of Gastrointestinal Oncology doi: 10.21037/jgo.2016.03.12. 2. Saeed N, Chuong M, Hoffe S, Shridhar R, Almhanna K and Meredith K L (2017) CT-Based Assessment of Visceral Adiposity and Outcomes for Esophageal Adenocarcinoma. Journal of Gastrointestinal Oncology 8(5).

Meredith is a Professor of Surgery at Florida State University College of Medicine and serves as Medical Director of Gastrointestinal Oncology at the Sarasota Memorial Institute for Cancer Care. He is a Surgical Oncologist with a focus on foregut malignancies. His clinical interests include minimally invasive approaches to resection of gastrointestinal malignancies including robotics. He has lectured and taught surgeons across the world about his robotic approaches and has pioneered robotic approaches to esophageal and pancreatic resections. He has published extensively and given over 200 presentations at the local, regional, national and international meetings.