Development and Validation of a Novel Skills Training Model for PCNL, an ESUT project

Main Article Content

Giorgio Bozzini
Matteo Maltagliati https://orcid.org/0000-0001-9621-7332
Lorenzo Berti
Riccardo Vismara
Francesco Sanguedolce
Alfonso Crisci
Gianfranco Beniamino Fiore
Alberto Redaelli
Antonio Luigi Pastore
Ali Gozen
Alberto Breda
Cesare Scoffone
Kamran Ahmed
Alexander Mueller
Stefano Gidaro
Evangelos Liatsikos

Keywords

PCNL, Training model, Urology, Validation

Abstract

Background and aim:

The aim of this study is to validate a totally non biologic training model that combines the use of ultrasound and X ray to train Urologists and Residents in Urology in PerCutaneous NephroLithotripsy (PCNL).


Methods:

The training pathway was divided into three modules: Module 1, related to the acquisition of basic UltraSound (US) skill on the kidney; Module 2, consisting of correct Nephrostomy placement; and Module 3, in which a complete PCNL was performed on the model. Trainees practiced on the model first on Module 1, than in 2 and in 3. The pathway was repeated at least three times. Afterward, they rated the performance of the model and the improvement gained using a global rating score questionnaire.


Results:

A total of 150 Urologists took part in this study. Questionnaire outcomes on this training model showed a mean 4.21 (range 1-5) of positive outcome overall. Individual constructive validity showed statistical significance between the first and the last time that trainees practiced on the PCNL model among the three different modules. Statistical significance was also found between residents, fellows and experts scores. Trainees increased their skills during the training modules.


Conclusion:

This PCNL training model allows for the acquisition of technical knowledge and skills as US basic skill, Nephrostomy placement and entire PCNL procedure. Its structured use could allow a better and safer training pathway to increase the skill in performing a PCNL.

Downloads

Download data is not yet available.
Abstract 37 | PDF Downloads 33

References

1. Ghani KR, Andonian S, Bultitude M et al. (2016) Percutaneous nephrolithotomy: update, trends, and future durections. Eur Urol 2016;70: 382-96.
Abdallah MM, Salem SM, Badreldin MR, Gamaleldin AA. (2013) The use of a biological model for comparing two techniques of fluoroscopy-guided percutaneous puncture: A randomised cross-over study. Arab J Urol. 2013 Mar;11(1):79-84.
2. Aydin A, Shafi AM, Khan MS, Dasgupta P, Ahmed K. (2016) Current Status of Simulation and Training Models in Urological Surgery: A Systematic Review. J Urol. 2016 Aug;196(2):312-20.
3. Häcker A, Wendt-Nordahl G, Honeck P, Michel MS, Alken P, Knoll T. (2007) A biological model to teach percutaneous nephrolithotomy technique with ultrasound- and fluoroscopy-guided access. J Endourol. 2007;21:545–50.
4. Jutzi S, Imkamp F, Kuczyk MA, Walcher U, Nagele U, Herrmann TR. (2014) New ex vivo organ model for percutaneous renal surgery using a laparoendoscopic training box: The sandwich model. World J Urol. 2014;32:783–9.
5. Redaelli A, Fiore B, Cipollini C, Ghilardi S, Vismara R, De Lorenzo D, Bozzini G. (2015) Devices for surgical training. United States Patent Application 20150037776.
6. Mishra S, Jagtap J, Sabnis RB, Desai MR. (2013) Training in percutaneous nephrolithotomy. Curr Opin Urol. 2013 Mar;23(2):147-51.
7. Reznick RK, H.(2006) MacRaeTeaching surgical skills—changes in the wind N Engl J Med, 355 (25), pp. 2664-2669.
8. Seymour NE, A.G. Gallagher, S.A. Roman, et al.(2002) Virtual reality training improves operating room performance: results of a randomized, double-blinded study. Ann Surg, 236 (4), pp. 458-463.
9. Mayberry JC. (2003) Residency reform Halsted-style. J Am Coll Surg, 197 (3) (2003), pp. 433-435.
10. Bridges M, D.L. Diamond. (1999) The financial impact of teaching surgical residents in the operating room. Am J Surg, 177 (1) (1999), pp. 28-32.
11. Cooke DT, R. Jamshidi, J. Guitron, J. Karamichalis. (2008) The virtual surgeon: using medical simulation to train the modern surgical resident. Bull Am Coll Surg, 93 (7) (2008), pp. 26-31.
12. Van Hove PD, G.J. Tuijthof, E.G. Verdaasdonk, L.P. Stassen, J. Dankelman. (2010) Objective assessment of technical surgical skills. Br J Surg, 97 (7), pp. 972-987.
13. Lentz GM, L.S. Mandel, B.A. Goff. (2005) A six-year study of surgical teaching and skills evaluation for obstetric/gynecologic residents in porcine and inanimate surgical simulators. Am J Obstet Gynecol, 193 (6), pp. 2056-2061.
14. DiMaggio PJ, A.L. Waer, T.J. Desmarais, et al. (2010) The use of a lightly preserved cadaver and full thickness pig skin to teach technical skills on the surgery clerkship—a response to the economic pressures facing academic medicine today. Am J Surg, 200 (1) (2010), pp. 162-166.
15. Sarmah P, Voss J, Ho A, Veneziano D, Somani B. (2017) Low vs. high fidelity: the importance of 'realism' in the simulation of a stone treatment procedure. Curr Opin Urol. 2017 Jul;27(4):316-322.
16. Bruyère F, Leroux C, Brunereau L, Lermusiaux P. (2008) Rapid prototyping model for percutaneous nephrolithotomy training. J Endourol. 2008 Jan;22(1):91-6.
17. Strohmaier WL, Giese A. (2009) Improved ex vivo training model for percutaneous renal surgery. Urol Res. 2009 Apr;37(2):107-10.
18. Turney BW. (2014) A new model with an anatomically accurate human renal collecting system for training in fluoroscopy-guided percutaneous nephrolithotomy access. J Endourol. 2014 Mar;28(3):360-3.
19. Sinha M, Krishnamoorthy V. (2015) Use of a vegetable model as a training tool for PCNL puncture. Indian J Urol. 2015 Apr-Jun;31(2):156-9.
20. Atalay HA, Canat HL, Ülker V, Alkan İ, Özkuvanci Ü, Altunrende F. (2017) Impact of personalized three-dimensional -3D- printed pelvicalyceal system models on patient information in percutaneous nephrolithotripsy surgery: a pilot study. Int Braz J Urol. 2017 May-Jun;43(3):470-475.
21. Maldonado-Alcaraz E, Gonzalez-Meza Garcia F, Serrano-Brambila EA. (2015) Evaluation of 2 inanimate models to improve percutaneous fluoroscopy-guided renal access time. Cir Cir. 2015 Sep-Oct: 83:402-8.

Most read articles by the same author(s)