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Multidimensional analyses of the learning curve of robotic low anterior resection for rectal cancer: 3-phase learning process comparison

Authors
 Eun Jung Park  ;  Chang Woo Kim  ;  Min Soo Cho  ;  Seung Hyuk Baik  ;  Dong Wook Kim  ;  Byung Soh Min  ;  Kang Young Lee  ;  Nam Kyu Kim 
Citation
 SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES, Vol.28(10) : 2821-2831, 2014 
Journal Title
 SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES 
ISSN
 0930-2794 
Issue Date
2014
MeSH
Adult ; Aged ; Anastomosis, Surgical ; Female ; Humans ; Laparoscopy ; Learning Curve* ; Male ; Middle Aged ; Operative Time ; Rectal Neoplasms/surgery* ; Robotic Surgical Procedures*
Keywords
Learning curve ; Robotic surgery ; Rectal cancer ; CUSUM
Abstract
BACKGROUND: Robotic surgery has advantages to perform rectal cancer by its ergonomic designs and advanced technologies. However, it was uncertain whether these core robotic technologies could shorten the learning curve. The aim of this study is to investigate the learning curve of robotic rectal cancer surgery and to compare the learning curve phases with respect to perioperative clinicopathologic outcomes. METHODS: From April 2006 to August 2011, a total of 130 consecutive patients who were diagnosed with rectal cancer underwent a robotic low anterior resection (LAR) using the hybrid technique by a single surgeon at Severance Hospital. The moving average method and the cumulative sum (CUSUM) were used to analyze the learning curve. The risk-adjusted CUSUM (RA-CUSUM) analysis was used to evaluate the points, which showed completion of surgical procedures in terms of R1 resection, conversion, postoperative complications, harvested lymph nodes less than 12, and local recurrence. Perioperative clinical outcomes and pathologic results were compared among the learning curve phases. RESULTS: According to the CUSUM, the learning curve was divided into three phases: phase 1 [the initial learning period (1st-44th case), n = 44], phase 2 [the competent period (45th-78th case), n = 34], and phase 3 [the challenging period (79th-130th case), n = 52]. RA-CUSUM showed the minimum value at the 75th case, which suggested technical competence to satisfy feasible perioperative outcomes. The total operation time tended to decrease after phase 1 and so did the surgeon console time and docking time. Postoperative complications and pathologic outcomes were not significantly different among the learning phases. CONCLUSIONS: The learning curve of robotic LAR consisted of three phases. The primary technical competence was achieved at phase 1 of the 44th case according to the CUSUM. The technical completion to assure feasible perioperative outcomes was achieved at phase 2 at the 75th case by the RA-CUSUM method.
Full Text
http://link.springer.com/article/10.1007%2Fs00464-014-3569-8
DOI
10.1007/s00464-014-3569-8
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Nam Kyu(김남규) ORCID logo https://orcid.org/0000-0003-0639-5632
Kim, Chang Woo(김창우)
Min, Byung Soh(민병소) ORCID logo https://orcid.org/0000-0003-0180-8565
Park, Eun Jung(박은정) ORCID logo https://orcid.org/0000-0002-4559-2690
Baik, Seung Hyuk(백승혁) ORCID logo https://orcid.org/0000-0003-4183-2332
Lee, Kang Young(이강영)
Cho, Min Soo(조민수)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/100103
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