Intérêt et performances d’un pelvitrainer portable pour l’entraînement à la laparoscopie

A low-cost and high-fidelity animal model for nonpalpable implant removal: A pilot study

Our preliminary results seem to confirm that our low‐cost animal model training for deep contraceptive implant removal might be an easy‐to‐use and reproducible training program.

Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills

Background. A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Methods. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts’ behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital “Raymundo Abarca Alarcón,” constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. Results. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. Conclusion. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

Implementation of laparoscopy surgery training via simulation in a low-income country

OBJECTIVE

The objective of this study was to evaluate laparoscopy training using pelvitrainers for gynaecological surgeons in a low-income country.

METHODS

The study was carried out in Madagascar from April 2016 to January 2017. The participants were gynaecological surgeons who had not previously performed laparoscopy. Each surgeon was timed to evaluate the execution times of four proposed exercises, based on the fundamentals of laparoscopic surgery (FLS) programme's skills manual, as follows: exercise 1, involving a simple object transfer; exercises 2 and 3, comprising complex object transfers; and exercise 4, a precision cutting exercise. The 8-month training and evaluation programme was divided into different stages, and the four following evaluations were compared: a pretest (T0), assessment at the end of the first training (T1) and auto-evaluation at 2 months (T2) and 8 months (T3).

RESULTS

Eight participants were included. The median time was significantly reduced (P<0.05) at each evaluation for exercises 1, 2 and 4 compared to the pretest. For exercise 3, there was no difference between T0 and T1 (P=0.07). After 8 months of training, all participants progressed in all exercises.

CONCLUSION

Our study showed that it is possible and beneficial to develop a programme for teaching laparoscopic surgery in low-income countries before providing the necessary equipment.

A low-cost alternative for nasolaryngoscopy simulation training equipment: a randomised controlled trial

OBJECTIVES

Flexible nasolaryngoscopy is a key diagnostic procedure used in many specialities. Simulation-based teaching is beneficial for endoscopy training, but it is expensive. This study assessed whether an inexpensive simulation model is an effective training method for flexible nasolaryngoscopy.

METHODS

A three-armed, randomised, controlled trial was performed. One group received no simulation training, while two others were trained with either a high-cost or a low-cost model. All candidates then performed flexible nasolaryngoscopy on a volunteer. Their ability to perform this task was assessed by the patient discomfort score and time taken by a blinded expert.

RESULTS

Simulation-based teaching reduced patient discomfort and improved candidate skill level. Low-cost model training did not have a negative effect when compared with high-cost model training.

CONCLUSION

Simulated flexible nasolaryngoscopy training may be more accessible with the use of an effective low-cost model.