Literature DB >> 22542929

A high fidelity model for single-incision laparoscopic cholecystectomy.

Richard M Kwasnicki1, Trystan M Lewis, Dimitris Reissis, Muthuswamy Sarvesvaran, Paraskevas A Paraskeva.   

Abstract

Single-incision laparoscopic surgery (SILS) is a safe approach for cholecystectomy, with the potential to minimise the iatrogenic trauma sustained from the operation. However, a number of reports show SILS to be technically challenging and as such there is expected to be a significant learning curve for expert surgeons adopting the new technique, as well as for junior surgical trainees. There are inherent risks to patient safety associated with practicing and developing new skills in a real-life theatre environment. However, thus far, there have been no realistic SILS training models available. We tested the feasibility of conducting SILS cholecystectomies on a cadaveric porcine model with standard operating equipment, which may provide a platform to facilitate safe training and assessment protocols. In this paper we provide an account of the training model technique, and review the literature surrounding SILS training and performance evaluation.
Copyright © 2012 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22542929     DOI: 10.1016/j.ijsu.2012.04.015

Source DB:  PubMed          Journal:  Int J Surg        ISSN: 1743-9159            Impact factor:   6.071


  2 in total

1.  Training model for laparoscopic Heller and Dor fundoplication: a tool for laparoscopic skills training and assessment-construct validity using the GOALS score.

Authors:  Omar Bellorin; Anna Kundel; Saurabh Sharma; Alexander Ramirez-Valderrama; Paul Lee
Journal:  Surg Endosc       Date:  2015-10-30       Impact factor: 4.584

2.  Model Surgical Training: Skills Acquisition in Fetoscopic Laser Photocoagulation of Monochorionic Diamniotic Twin Placenta Using Realistic Simulators.

Authors:  Tuangsit Wataganara; Arundhati Gosavi; Katika Nawapun; Pradip D Vijayakumar; Nisarat Phithakwatchara; Mahesh Choolani; Lin Lin Su; Arijit Biswas; Citra N Z Mattar
Journal:  J Vis Exp       Date:  2018-03-21       Impact factor: 1.355

  2 in total

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