Literature DB >> 22556136

The role of a well-trained team on the early learning curve of robot-assisted laparoscopic procedures: the example of radical prostatectomy.

Thierry Lebeau1, Morgan Rouprêt, Karim Ferhi, Emmanuel Chartier-Kastler, Marc-Olivier Bitker, François Richard, Christophe Vaessen.   

Abstract

BACKGROUND: The robot-assisted laparoscopic approach for radical prostatectomy (RARP) is being performed increasingly worldwide to treat localized prostate cancer (PCa). The aim of this study was to compare the learning curves of two surgeons with different surgical experiences.
METHODS: A prospective collection of peri-operative data was made: age, body mass index, PSA, clinical stage, biopsy Gleason score, operative time (OT), blood loss (BL), pathological stages, final Gleason scores, and complications. Patients were included, in two groups. The first group comprised the first 100 patients undergoing RARP by an expert laparoscopic surgeon. The second group of 100 patients was operated on by a junior surgeon without robotic console experience. Post-operative complications were defined according to the Clavien grading system for surgical morbidity
RESULTS: For groups 1 and 2 median age was 63 and 62 years, respectively; median pre-operative PSA level was 10 and 8, respectively; the median BMI was 24 and 25, respectively. The median operative time (OT) was 179 and 160 min, respectively (p > 0.05); and median blood loss was 217 and 346 ml, respectively (p = 0.04). The overall transfusion rate was 1.5% and two major complications were recorded in group 1 and four in group 2.
CONCLUSIONS: RARP is safe and reproducible even during the initial learning curve. Overcoming the learning curve is multifactorial and is necessarily dependent on the surgeon. However, joining a well-trained team probably affects positively the performance of the surgeon. The value of expert centers to train new surgeons to RARP needs to be evaluated.
Copyright © 2011 John Wiley & Sons, Ltd.

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Mesh:

Year:  2012        PMID: 22556136     DOI: 10.1002/rcs.435

Source DB:  PubMed          Journal:  Int J Med Robot        ISSN: 1478-5951            Impact factor:   2.547


  9 in total

1.  The surgical approach can be determined from the pathological specimen obtained after open or robot-assisted laparoscopic radical prostatectomy.

Authors:  Sarah J Drouin; Eva Comperat; Justine Varinot; Christophe Vaessen; Marc-Olivier Bitker; Emmanuel Chartier-Kastler; Pierre Mozer; Shahrokh F Shariat; Olivier Cussenot; Morgan Rouprêt
Journal:  World J Urol       Date:  2013-05-31       Impact factor: 4.226

2.  Capsular incision in normal prostatic tissue during robot-assisted radical prostatectomy: a new concept or a waste of time?

Authors:  Nicolas Koutlidis; Céline Duperron; Mathilde Funes de la Vega; Eric Mourey; Frédéric Michel; Luc Cormier
Journal:  World J Urol       Date:  2013-10-29       Impact factor: 4.226

3.  [Robot-assisted pancreatic resection].

Authors:  B Müssle; M Distler; J Weitz; T Welsch
Journal:  Chirurg       Date:  2017-06       Impact factor: 0.955

4.  Robotic-assisted and laparoscopic ventral rectopexy in the treatment of rectal prolapse: a matched-pairs study of operative details and complications.

Authors:  J Mäkelä-Kaikkonen; T Rautio; K Klintrup; H Takala; M Vierimaa; P Ohtonen; J Mäkelä
Journal:  Tech Coloproctol       Date:  2013-07-10       Impact factor: 3.781

5.  Developing a robotic colorectal cancer surgery program: understanding institutional and individual learning curves.

Authors:  Hamza Guend; Maria Widmar; Sunil Patel; Garrett M Nash; Philip B Paty; José G Guillem; Larissa K Temple; Julio Garcia-Aguilar; Martin R Weiser
Journal:  Surg Endosc       Date:  2016-11-04       Impact factor: 4.584

6.  Robot assisted laparoscopic radical prostatectomy: assistant's seniority has no influence on perioperative course.

Authors:  Yasmin Abu-Ghanem; Tomer Erlich; Jacob Ramon; Zohar Dotan; Dorit E Zilberman
Journal:  J Robot Surg       Date:  2016-11-09

7.  Learning curves for robotic pancreatic surgery-from distal pancreatectomy to pancreaticoduodenectomy.

Authors:  Bor-Uei Shyr; Shih-Chin Chen; Yi-Ming Shyr; Shin-E Wang
Journal:  Medicine (Baltimore)       Date:  2018-11       Impact factor: 1.889

Review 8.  Systematic review of learning curves in robot-assisted surgery.

Authors:  N A Soomro; D A Hashimoto; A J Porteous; C J A Ridley; W J Marsh; R Ditto; S Roy
Journal:  BJS Open       Date:  2019-11-29

9.  Effective implementation and adaptation of structured robotic colorectal programme in a busy tertiary unit.

Authors:  A Thomas; K Altaf; D Sochorova; U Gur; A Parvaiz; Shakil Ahmed
Journal:  J Robot Surg       Date:  2020-11-03
  9 in total

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