Literature DB >> 20047195

Set-up and docking of the da Vinci surgical system: prospective analysis of initial experience.

Pouya Iranmanesh1, Philippe Morel, Oliver J Wagner, Ihsan Inan, François Pugin, Monika E Hagen.   

Abstract

BACKGROUND: Set-up and docking of the da Vinci surgical system are assumed to extend overall operating times. We hypothesized that these tasks could be achieved in adequate times. Therefore, a prospective analysis of set-up and docking times of the da Vinci Surgical System was conducted.
METHODS: We prospectively analysed set-up and docking times with the da Vinci surgical system in our division.
RESULTS: Ninety-six patients were operated on over 30 months in our institution. Median set-up time was 22 (range 9-50) min and median docking time was 10 (range 2-70) min. Surgeons with previous docking experience were significantly faster than inexperienced surgeons: 8 (range 2-50) vs. 17.5 (range 10-70) min. Both set-up and docking showed a fast learning curve.
CONCLUSION: The data support the conclusion that both set-up and docking of the robot can be achieved in adequate times and have a low impact on overall operating time. (c) 2010 John Wiley & Sons, Ltd.

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Mesh:

Year:  2010        PMID: 20047195     DOI: 10.1002/rcs.288

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


  13 in total

1.  Early clinical experience with the da Vinci Xi Surgical System in general surgery.

Authors:  Monika E Hagen; Minoa K Jung; Frederic Ris; Jassim Fakhro; Nicolas C Buchs; Leo Buehler; Philippe Morel
Journal:  J Robot Surg       Date:  2016-12-27

2.  Robotic versus open pancreaticoduodenectomy: a comparative study at a single institution.

Authors:  Nicolas Christian Buchs; Pietro Addeo; Francesco Maria Bianco; Subhashini Ayloo; Enrico Benedetti; Pier Cristoforo Giulianotti
Journal:  World J Surg       Date:  2011-12       Impact factor: 3.352

3.  Learning curve and robot set-up/operative times in singly docked totally robotic Roux-en-Y gastric bypass.

Authors:  Subhashini Ayloo; Eduardo Fernandes; Nabajit Choudhury
Journal:  Surg Endosc       Date:  2014-01-03       Impact factor: 4.584

4.  Reducing cost of surgery by avoiding complications: the model of robotic Roux-en-Y gastric bypass.

Authors:  Monika E Hagen; Francois Pugin; Gilles Chassot; Olivier Huber; Nicolas Buchs; Pouya Iranmanesh; Philippe Morel
Journal:  Obes Surg       Date:  2012-01       Impact factor: 4.129

Review 5.  Robot-assisted pancreatic surgery: a systematic review of the literature.

Authors:  Marin Strijker; Hjalmar C van Santvoort; Marc G Besselink; Richard van Hillegersberg; Inne H M Borel Rinkes; Menno R Vriens; I Quintus Molenaar
Journal:  HPB (Oxford)       Date:  2012-10-17       Impact factor: 3.647

6.  Robotic Pancreaticoduodenectomy: Single-Surgeon Initial Experience.

Authors:  Mingjun Wang; Yunqiang Cai; Yongbin Li; Bing Peng
Journal:  Indian J Surg       Date:  2016-10-21       Impact factor: 0.656

7.  Barriers to safety and efficiency in robotic surgery docking.

Authors:  Lucy Cofran; Tara Cohen; Myrtede Alfred; Falisha Kanji; Eunice Choi; Stephen Savage; Jennifer Anger; Ken Catchpole
Journal:  Surg Endosc       Date:  2021-01-19       Impact factor: 4.584

8.  The Initial Learning Curve for Robot-Assisted Sleeve Gastrectomy: A Surgeon's Experience While Introducing the Robotic Technology in a Bariatric Surgery Department.

Authors:  Ramon Vilallonga; José Manuel Fort; Oscar Gonzalez; Enric Caubet; Angeles Boleko; Karl John Neff; Manel Armengol
Journal:  Minim Invasive Surg       Date:  2012-09-17

9.  Early experience with the da Vinci surgical system robot in gynecological surgery at King Abdulaziz University Hospital.

Authors:  Khalid H Sait
Journal:  Int J Womens Health       Date:  2011-07-26

10.  Learning curve analysis of robot-assisted radical hysterectomy for cervical cancer: initial experience at a single institution.

Authors:  Ga Won Yim; Sang Wun Kim; Eun Ji Nam; Sunghoon Kim; Young Tae Kim
Journal:  J Gynecol Oncol       Date:  2013-10-02       Impact factor: 4.401

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