Narrow Results

We discuss a combination of established and modern techniques in the investigation and management of traumatic flexor digitorum profundus rupture ('Rugger Jersey Finger') in seven cases (male rugby players ranging from 15 to 30 years of age; mean = 26). We discuss the use of X-ray and ultrasound investigation followed by various surgical repairs including intraosseous sutures, suture anchors, tendon lengthening and "pull-through suture over button" repairs. Functional outcome at outpatient follow-up is discussed in each case. Type I, II and Vb injuries were identified. Patients presenting early attained good functional outcome. Six patients received surgery within ten days of injury and attained satisfactory outcome at follow-up. One patient presented late and required a tendon lengthening procedure to manage myostatic contracture. Ultrasound imaging proved valuable in diagnosis and pre-operative planning. Numerous surgical repairs were used and all associated with a positive outcome providing there is adequate patient compliance.

In competitive sports, players are always at high risk for injuries. Sports injuries in rugby sports are directly related to the team’s game performance, especially when the player has an old sports injury or psychological stress. By considering the athlete as a dynamic system and quantifying the features associated with sports injuries, machine learning can be used to predict and assess the associated risks. In this paper, a simplified GRU is proposed to construct the mapping relationship between sports injury features and rugby game results. The comparison experiments with other machine learning models show that this model has better robustness in the prediction tasks of sports injuries and competition results of teenage rugby players.