Development and Validation of a Novel and Cost-Effective Animal Tissue Model for Training Transurethral Resection of the Prostate.

J Surg Educ

Cuschieri Skills Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom. Electronic address:

Published: June 2018

Objectives: To develop and validate a new and cost-effective animal tissue training model for practicing resection skills of transurethral resection of the prostate (TURP).

Methods And Materials: A porcine kidney was prepared and restructured to simulate the relevant anatomy of the human prostate. The restructured prostate was connected to an artificial urethra and bladder. Face, content, and construct validity of the model was carried out using a 5-point Likert scale questionnaire, and comparison in task performance between participants and experts was made using observational clinical human reliability analysis.

Results: A total of 24 participants and 11 experts who practiced TURP skills on this model from October 2014 to December 2015 were recruited. The mean score on specific feature of the anatomy and color, sensation of texture and feeling of resection, conductibility of current, and efficacy and safety of the model were 4.34 ± 0.37, 4.51 ± 0.63, 4.13 ± 0.53, and 4.35 ± 0.71, respectively, by participants whereas they were 4.22 ± 0.23, 4.30 ± 0.48, 4.11 ± 0.62, and 4.56 ± 0.77, respectively, by the experts on a scale of 1 (unrealistic) to 5 (very realistic). Participants committed more technical errors than the experts (11 vs 7, p < 0.001), produced more movements of the instruments (51 vs 33, p < 0.001), and required longer operating time (11.4 vs 6.2min, p < 0.001).

Conclusions: A newly developed restructured animal tissue model for training TURP was reported. Validation study on the model demonstrates that this is a very realistic and effective model for skills training of TURP. Trainees committed more technical errors, more unproductive movements, and required longer operating time.

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http://dx.doi.org/10.1016/j.jsurg.2017.03.004DOI Listing

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