Literature DB >> 14752634

Qualitative and quantitative analysis of the learning curve of a simulated surgical task on the da Vinci system.

J D Hernandez1, S D Bann, Y Munz, K Moorthy, V Datta, S Martin, A Dosis, F Bello, A Darzi, T Rockall.   

Abstract

BACKGROUND: Robotic telemanipulation systems provide solutions to the problems of less dexterity and visual constraints of minimally invasive surgery (MIS). However, their influence over surgeons' dexterity and learning curve needs to be assessed. We present motion analysis as an objective method to measure performance and learning progress.METHODS. Thirteen surgeons completed five synthetic small bowel anastomoses using the da Vinci system. Objective Structured Assessment of Technical Skills (OSATS) allowed qualitative analysis. Quantitative analysis used API software of the system to retrieve real-time robotic signal data of time, path length, and number of movements. Wilcoxon signed ranks test was used for statistical analysis. A p value <0.05 was considered significant.RESULTS. OSATS global scores were 18.6 points for the first attempt and 26 for the fifth attempt ( p < 0.02, Cronbach's alpha = 0.894). Paired data of motion analysis for attempts 1 vs 5 showed significant change: time taken 3507 sec and 2287 sec ( p < 0.008), total number of movements 2411 and 1387 ( p = 0.01), total path length 21,630 cm and 13,941 cm ( p = 0.01).CONCLUSIONS. A rapid learning curve to a competent level using the da Vinci system is possible aided by the system's intuitive motion. Motion analysis is a useful tool to measure performance in the da Vinci system compared to OSATS and time alone.

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Year:  2004        PMID: 14752634     DOI: 10.1007/s00464-003-9047-3

Source DB:  PubMed          Journal:  Surg Endosc        ISSN: 0930-2794            Impact factor:   4.584


  32 in total

1.  Telesurgical laparoscopic cholecystectomy between two countries.

Authors:  W K Cheah; B Lee; J E Lenzi; P M Goh
Journal:  Surg Endosc       Date:  2000-08-09       Impact factor: 4.584

Review 2.  Robotics and allied technologies in endoscopic surgery.

Authors:  G F Buess; M O Schurr; S C Fischer
Journal:  Arch Surg       Date:  2000-02

3.  The use of electromagnetic motion tracking analysis to objectively measure open surgical skill in the laboratory-based model.

Authors:  V Datta; S Mackay; M Mandalia; A Darzi
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Review 4.  Robot-assisted surgical systems: a new era in laparoscopic surgery.

Authors:  J P Ruurda; Th J M V van Vroonhoven; I A M J Broeders
Journal:  Ann R Coll Surg Engl       Date:  2002-07       Impact factor: 1.891

5.  Robotic-assisted laparoscopic microsurgical tubal anastomosis: a human pilot study.

Authors:  T Falcone; J M Goldberg; H Margossian; L Stevens
Journal:  Fertil Steril       Date:  2000-05       Impact factor: 7.329

6.  Transcontinental robot-assisted remote telesurgery: feasibility and potential applications.

Authors:  Jacques Marescaux; Joel Leroy; Francesco Rubino; Michelle Smith; Michel Vix; Michele Simone; Didier Mutter
Journal:  Ann Surg       Date:  2002-04       Impact factor: 12.969

7.  Robotic-enhanced arterial revascularization for multivessel coronary artery disease.

Authors:  R Cichon; U Kappert; J Schneider; I Schramm; V Gulielmos; S M Tugtekin; S Schüler
Journal:  Ann Thorac Surg       Date:  2000-09       Impact factor: 4.330

8.  Mortality and complications associated with laparoscopic cholecystectomy. A meta-analysis.

Authors:  J A Shea; M J Healey; J A Berlin; J R Clarke; P F Malet; R N Staroscik; J S Schwartz; S V Williams
Journal:  Ann Surg       Date:  1996-11       Impact factor: 12.969

Review 9.  The surgical option for gastroesophageal reflux disease.

Authors:  R A Hinder; G Perdikis; P J Klinger; K R DeVault
Journal:  Am J Med       Date:  1997-11-24       Impact factor: 4.965

10.  Comparison of laparoscopic cholecystectomy with open cholecystectomy in a single center.

Authors:  L F Williams; W C Chapman; R A Bonau; E C McGee; R W Boyd; J K Jacobs
Journal:  Am J Surg       Date:  1993-04       Impact factor: 2.565

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  36 in total

Review 1.  Review of methods for objective surgical skill evaluation.

Authors:  Carol E Reiley; Henry C Lin; David D Yuh; Gregory D Hager
Journal:  Surg Endosc       Date:  2010-07-07       Impact factor: 4.584

2.  Robot-assisted laparoscopic Roux-en-Y gastric bypass.

Authors:  M R Ali; B Bhaskerrao; B M Wolfe
Journal:  Surg Endosc       Date:  2004-12-30       Impact factor: 4.584

3.  Performance vs. learning curves: what is motor learning and how is it measured?

Authors:  A Dubrowski
Journal:  Surg Endosc       Date:  2005-09       Impact factor: 4.584

4.  Robotic ocular surgery.

Authors:  A Tsirbas; C Mango; E Dutson
Journal:  Br J Ophthalmol       Date:  2006-10-04       Impact factor: 4.638

5.  Validated robotic laparoscopic surgical training in a virtual-reality environment.

Authors:  Dimitrios Katsavelis; Ka-Chun Siu; Bernadette Brown-Clerk; Irene H Lee; Yong Kwon Lee; Dmitry Oleynikov; Nick Stergiou
Journal:  Surg Endosc       Date:  2008-04-10       Impact factor: 4.584

6.  Objective evaluation of expert and novice performance during robotic surgical training tasks.

Authors:  Timothy N Judkins; Dmitry Oleynikov; Nick Stergiou
Journal:  Surg Endosc       Date:  2008-04-29       Impact factor: 4.584

7.  Robotic anatomic lung resections: the initial experience and description of learning in 102 cases.

Authors:  Alper Toker; Mehmet Oğuzhan Özyurtkan; Erkan Kaba; Kemal Ayalp; Özkan Demirhan; Elena Uyumaz
Journal:  Surg Endosc       Date:  2015-06-20       Impact factor: 4.584

Review 8.  Learning tools and simulation in robotic surgery: state of the art.

Authors:  Nicolas C Buchs; François Pugin; Francesco Volonté; Philippe Morel
Journal:  World J Surg       Date:  2013-12       Impact factor: 3.352

9.  Battle of the bots: a comparison of the standard da Vinci and the da Vinci Surgical Skills Simulator in surgical skills acquisition.

Authors:  Kevin Brown; Natalie Mosley; James Tierney
Journal:  J Robot Surg       Date:  2016-08-29

10.  Robotics versus laparoscopy--an experimental study of the transfer effect in maiden users.

Authors:  Magnus Anderberg; Johan Larsson; Christina C Kockum; Einar Arnbjörnsson
Journal:  Ann Surg Innov Res       Date:  2010-04-06
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