Evaluation of konjac noodle as a microsurgery training model: learning curve analysis

Abstract

ABSTRACT Background: classical models of microsurgical anastomosis training are expensive and have ethical implications. Some alternatives join low cost and easiness to store. However, the translation of knowledge acquired by training in these methods into the traditional ones is not clear. This project aims to assess the feasibility of konjac noodles as a reliable microsurgery-training model. Methods: 10 neurosurgery residents performed an end-to-end anastomosis in a 2-3mm placenta artery. The anastomoses were evaluated quantitatively, recording time; and qualitatively, applying a validated score (Anastomosis Lapse Index - ALI) by three experienced neurosurgeons and verifying the presence of gross leakage through the infusion of fluorescein. Subsequently, they performed 10 non-consecutive sessions of anastomosis training in the konjac noodle. Eventually, a final anastomosis in the placenta model was performed and the same parameters were scored. Results: we observed a 17min reduction in the mean time to perform the anastomosis in the placenta model after the training in the konjac (p<0.05). There was a non-significant 20% reduction in gross leakage, but the training sessions were not able to consistently improve the ALI score. Conclusions: we demonstrate a reduction in anastomosis performing time in placental arteries after training sessions in the konjac noodle model, which can be regarded as a feasible low-cost method, particularly useful in centers with surgical microscopes only in the operation room.

Keywords

• Learning Curve
• Microsurgery
• Simulation Training
• Anastomosis
• Surgical