Learning Acetabular Fracture Classification using a Three-Dimensional Interactive Software: A Randomized Controlled Trial |
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| Authors: | Huixiang Wang Fei Lyu Kapil Sugand Sheungting Wong Yanping Lin Qiugen Wang |
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| Institution: | 1. Orthopedic Traumatology, Trauma Center, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, Peoples’ Republic of China;2. Musculoskeletal Laboratory (MSk Lab), Charing Cross Hospital, Faculty of Medicine, Imperial College, London, United Kingdom;3. Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, Peoples’ Republic of China |
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| Abstract: | Acetabular fractures are a real challenge for junior doctors as well as experienced orthopedic surgeons. Correct fracture classification is crucial for appreciating the fracture type, surgical planning, and predicting prognosis. Although three-dimensional (3D) tutorial is believed to improve the understanding of the complex anatomy structure, there have been few applications and randomized controlled trials to confirm it in orthopedics. This study aims to develop a 3D interactive software system for teaching acetabular fracture classification and evaluate its efficacy. Participants were randomly but evenly allocated into either the experimental group (who learned the acetabular fracture classification using a 3D software) or the control group (who used a traditional two-dimensional 2D] tutorial). Both groups were then tasked to classify 10 acetabular fractures and complete a five-point Likert scale on their satisfaction of each learning modality. To calculate significance (P < 0.05), independent t-test was used for normally distributed data whereas Mann-Whitney U test for non-normally distributed data. The experimental group significantly outperformed the control group (t (28) = 2.526, P = 0.017) with identifying correct acetabular fracture classification. Moreover, Likert scale score in the experimental group was also significantly higher than in the control group (Z = 2.477, P = 0.013). This 3D classification software has objectively and subjectively showed an advantage over the traditional 2D tutorial, resulting in an improved classification accuracy and higher Likert scale score. The 3D software has the potential to improve both clinical knowledge as well as identifying correct patient management in orthopedics. |
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| Keywords: | medical education orthopedic education musculoskeletal education acetabular fracture fracture classification three-dimensional rendering two-dimensional rendering classification software |
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