Literature DB >> 28881887

Learning curve for robotic esophagectomy and dissection of bilateral recurrent laryngeal nerve nodes for esophageal cancer.

S Y Park1,2, D J Kim1, D R Kang3, S J Haam2.   

Abstract

Dissection of bilateral recurrent laryngeal nerve (RLN) nodes is a technically demanding procedure, but robotic systems have been useful for RLN node dissection. This retrospective study investigated the learning curve for bilateral RLN node dissection in esophageal-cancer patients using a robotic system for esophageal cancer. We retrospectively reviewed 33 consecutive patients who received a robotic esophagectomy and total lymphadenectomy by single surgeon. The patients were divided into either group 1 (initial 20 cases) or group 2 (later 13 cases). The mean patient age was 61.88 ± 9.03 years and 28 (84.8%) patients were male. Most cases were pathologically diagnosed as squamous cell carcinoma. The lesion locations included 3 (9.1%) in the upper esophagus, 12 (63.6%) in the mid esophagus, and 9 (27.3%) in the lower esophagus. Eleven (33.3%) cases were stage I, 7 (21.2%) were stage II, and 15 (45.5%) were stage III. One case in group 2 (3%) suffered operative mortality. Operation time, robot console time, and blood loss were similar between the two groups. The timing of right and left RLN node dissection, the number of total dissected lymph nodes, and the percentage of dissected right and left RLN nodes were also comparable. However, the incidence of vocal cord palsy was significantly lower in group 2 (55% vs. 0%, p= 0.02). The incidence of other operative complications did not vary between the two groups. Even though operative outcomes and incidence of other complications were comparable between the two groups, the incidence of vocal cord palsy decreased significantly after 20 cases. Thus, we conclude that a minimum of 20 cases is required before a surgeon is experienced enough to perform safe dissection of bilateral RLN nodes.
© The Authors 2017. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  esophageal cancer; learning curve; lymphadenectomy; robotic surgery

Mesh:

Year:  2017        PMID: 28881887     DOI: 10.1093/dote/dox094

Source DB:  PubMed          Journal:  Dis Esophagus        ISSN: 1120-8694            Impact factor:   3.429


  6 in total

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2.  Extended thoracic lymph node dissection in robotic-assisted minimal invasive esophagectomy (RAMIE) for patients with superior mediastinal lymph node metastasis.

Authors:  Sylvia van der Horst; Michiel F G de Maat; Pieter C van der Sluis; Jelle P Ruurda; Richard van Hillegersberg
Journal:  Ann Cardiothorac Surg       Date:  2019-03

3.  Robotic-assisted minimally invasive oesophagectomy for cancer: An initial experience.

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4.  Robotic-assisted single-incision gastric mobilization for minimally invasive oesophagectomy for oesophageal cancer: preliminary results.

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Journal:  Eur J Cardiothorac Surg       Date:  2020-08-01       Impact factor: 4.191

5.  From McKeown to Ivor Lewis, the learning curve for thoracic lymphadenectomy over the first 100 robotic esophagectomy cases: a retrospective study.

Authors:  Ze-Guo Zhuo; Gang Li; Tie-Niu Song; Gu-Ha Alai; Xu Shen; Yun Wang; Yi-Dan Lin
Journal:  J Thorac Dis       Date:  2021-03       Impact factor: 2.895

6.  Robot-assisted minimally invasive esophagectomy (RAMIE) vs. hybrid minimally invasive esophagectomy: propensity score matched short-term outcome analysis of a European high-volume center.

Authors:  Benjamin Babic; Dolores T Müller; Jin-On Jung; Lars M Schiffmann; Paula Grisar; Thomas Schmidt; Seung-Hun Chon; Wolfgang Schröder; Christiane J Bruns; Hans F Fuchs
Journal:  Surg Endosc       Date:  2022-05-03       Impact factor: 3.453

  6 in total

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