A novel three-in-one silicone model for basic microsurgery training
Background Microsurgery simulation is an important aspect of surgical training. Animal models have been widely used in simulation training, but they have some limitations including ethical restrictions, cost and availability. This has led to the use of synthetic models that can reduce reliance on an...
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Veröffentlicht in: | European journal of plastic surgery 2020-10, Vol.43 (5), p.621-626 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Background
Microsurgery simulation is an important aspect of surgical training. Animal models have been widely used in simulation training, but they have some limitations including ethical restrictions, cost and availability. This has led to the use of synthetic models that can reduce reliance on animals in line with the 3R (refinement, reduction and replacement) principles. The aim of this paper was to evaluate the face validity of Surgitate™ three-in-one (artery, vein and nerve) silicone model.
Methods
Fourteen candidates performed one end-to-end anastomosis on artery, vein and nerve. The face validity of the vessel was assessed via questionnaires detailing their previous microsurgical experience and their feedback of using this model using the Likert scale. Data management and analysis were performed using IBM SPSS software (25.0).
Results
Participants tended to value this model in the earlier stages of microsurgical training particularly in the acquisition of basic microsurgical skills. It could be particularly useful in enhancing suturing skills as a replacement or reduction in the use of chicken models. The model has some drawbacks preluding its utilization into more advanced stages of surgical training. Further studies are needed to validate the model using more objective measures.
Conclusion
We present a novel synthetic model that can be potentially introduced to early stages of microsurgery training. The model would be ideal to meet the 3R principles of the use of animal models and as an alternative to the commonly used synthetic models.
Level of evidence: Not ratable. |
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ISSN: | 0930-343X 1435-0130 |
DOI: | 10.1007/s00238-020-01666-4 |