Literature DB >> 33665163

Surgical Complexity and Outcome During the Implementation Phase of a Robotic Colorectal Surgery Program-A Retrospective Cohort Study.

Catharina Müller1, Johannes Laengle1, Stefan Riss1, Michael Bergmann1, Thomas Bachleitner-Hofmann1.   

Abstract

BACKGROUND: Robotic surgery holds particular promise for complex oncologic colorectal resections, as it can overcome many limitations of the laparoscopic approach. However, similar to the situation in laparoscopic surgery, appropriate case selection (simple vs. complex) with respect to the actual robotic expertise of the team may be a critical determinant of outcome. The present study aimed to analyze the clinical outcome after robotic colorectal surgery over time based on the complexity of the surgical procedure.
METHODS: All robotic colorectal resections (n = 85) performed at the Department of Surgery, Medical University of Vienna, between the beginning of the program in April 2015 until December 2019 were retrospectively analyzed. To compare surgical outcome over time, the cohort was divided into 2 time periods based on case sequence (period 1: patients 1-43, period 2: patients 44-85). Cases were assigned a complexity level (I-IV) according to the type of resection, severity of disease, sex and body mass index (BMI). Postoperative complications were classified using the Clavien-Dindo classification.
RESULTS: In total, 47 rectal resections (55.3%), 22 partial colectomies (25.8%), 14 abdomino-perineal resections (16.5%) and 2 proctocolectomies (2.4%) were performed. Of these, 69.4% (n = 59) were oncologic cases. The overall rate of major complications (Clavien Dindo III-V) was 16.5%. Complex cases (complexity levels III and IV) were more often followed by major complications than cases with a low to medium complexity level (I and II; 25.0 vs. 5.4%, p = 0.016). Furthermore, the rate of major complications decreased over time from 25.6% (period 1) to 7.1% (period 2, p = 0.038). Of note, the drop in major complications was associated with a learning effect, which was particularly pronounced in complex cases as well as a reduction of case complexity from 67.5% to 45.2% in the second period (p = 0.039).
CONCLUSIONS: The risk of major complications after robotic colorectal surgery increases significantly with escalating case complexity (levels III and IV), particularly during the initial phase of a new colorectal robotic surgery program. Before robotic proficiency has been achieved, it is therefore advisable to limit robotic colorectal resection to cases with complexity levels I and II in order to keep major complication rates at a minimum.
Copyright © 2021 Müller, Laengle, Riss, Bergmann and Bachleitner-Hofmann.

Entities:  

Keywords:  DaVinci Si; case complexity; colorectal cancer; colorectal surgery; learning curve; robotic surgery

Year:  2021        PMID: 33665163      PMCID: PMC7923881          DOI: 10.3389/fonc.2020.603216

Source DB:  PubMed          Journal:  Front Oncol        ISSN: 2234-943X            Impact factor:   6.244


  24 in total

Review 1.  Have early postoperative complications from laparoscopic rectal cancer surgery improved over the past 20 years?

Authors:  R Shearer; M Gale; O E Aly; E H Aly
Journal:  Colorectal Dis       Date:  2013       Impact factor: 3.788

2.  Safe adoption of robotic colorectal surgery using structured training: early Irish experience.

Authors:  Mohammed Aradaib; Paul Neary; Adnan Hafeez; Reza Kalbassi; Amjad Parvaiz; Diarmuid O'Riordain
Journal:  J Robot Surg       Date:  2018-12-10

Review 3.  Learning curve and case selection in laparoscopic colorectal surgery: systematic review and international multicenter analysis of 4852 cases.

Authors:  Danilo Miskovic; Melody Ni; Susannah M Wyles; Paris Tekkis; George B Hanna
Journal:  Dis Colon Rectum       Date:  2012-12       Impact factor: 4.585

4.  The multiphasic learning curve for robot-assisted rectal surgery.

Authors:  Kevin Kaity Sng; Masayasu Hara; Jae-Won Shin; Byung-Eun Yoo; Kyung-Sook Yang; Seon-Hahn Kim
Journal:  Surg Endosc       Date:  2013-03-19       Impact factor: 4.584

5.  Robotic Colorectal Surgery Learning Curve and Case Complexity.

Authors:  Darcy D Shaw; Moriah Wright; Lindsay Taylor; Noelle L Bertelson; Maniamparampil Shashidharan; Prem Menon; Vijay Menon; Samuel Wood; Charles A Ternent
Journal:  J Laparoendosc Adv Surg Tech A       Date:  2018-05-07       Impact factor: 1.878

6.  Total mesorectal excision: a comparison of oncological and functional outcomes between robotic and laparoscopic surgery for rectal cancer.

Authors:  Annibale D'Annibale; Graziano Pernazza; Igor Monsellato; Vito Pende; Giorgio Lucandri; Paolo Mazzocchi; Giovanni Alfano
Journal:  Surg Endosc       Date:  2013-01-05       Impact factor: 4.584

7.  Robotic vs laparoscopic rectal surgery in high-risk patients.

Authors:  J Ahmed; H Cao; S Panteleimonitis; J Khan; A Parvaiz
Journal:  Colorectal Dis       Date:  2017-12       Impact factor: 3.788

8.  Robotic colorectal surgery: previous laparoscopic colorectal experience is not essential.

Authors:  Tanvir Singh Sian; G M Tierney; H Park; J N Lund; W J Speake; N G Hurst; H Al Chalabi; K J Smith; S Tou
Journal:  J Robot Surg       Date:  2017-07-18

9.  Robotic versus laparoscopic low anterior resection of rectal cancer: short-term outcome of a prospective comparative study.

Authors:  Seung Hyuk Baik; Hye Youn Kwon; Jin Soo Kim; Hyuk Hur; Seung Kook Sohn; Chang Hwan Cho; Hoguen Kim
Journal:  Ann Surg Oncol       Date:  2009-03-17       Impact factor: 5.344

Review 10.  Robotic Surgery for Rectal Cancer: An Update in 2015.

Authors:  Jung Myun Kwak; Seon Hahn Kim
Journal:  Cancer Res Treat       Date:  2016-02-03       Impact factor: 4.679

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