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    Injuries in Australian Rules Football: An Overview of Injury Rates, Patterns, and Mechanisms Across All Levels of Play
    Saw, R ; Finch, CF ; Samra, D ; Baquie, P ; Cardoso, T ; Hope, D ; Orchard, JW (SAGE PUBLICATIONS INC, 2018)
    CONTEXT: The nature of Australian rules football (Australian football) predisposes both unique and common injuries compared with those sustained in other football codes. The game involves a combination of tackling, kicking, high-speed running (more than other football codes), and jumping. Two decades of injury surveillance has identified common injuries at the professional level (Australian Football League [AFL]). OBJECTIVE: To provide an overview of injuries in Australian rules football, including injury rates, patterns, and mechanisms across all levels of play. STUDY DESIGN: A narrative review of AFL injuries, football injury epidemiology, and biomechanical and physiological attributes of relevant injuries. RESULTS: The overall injury incidence in the 2015 season was 41.7 injuries per club per season, with a prevalence of 156.2 missed games per club per season. Lower limb injuries are most prevalent, with hamstring strains accounting for 19.1 missed games per club per season. Hamstring strains relate to the volume of high-speed running required in addition to at times having to collect the ball while running in a position of hip flexion and knee extension. Anterior cruciate ligament injuries are also prevalent and can result from contact and noncontact incidents. In the upper limb, shoulder sprains and dislocations account for 11.5 missed games per club per season and largely resulted from tackling and contact. Concussion is less common in AFL than other tackling sports but remains an important injury, which has notably become more prevalent in recent years, theorized to be due to a more conservative approach to management. Although there are less injury surveillance data for non-AFL players (women, community-level, children), many of these injuries appear to also be common across all levels of play. CLINICAL RELEVANCE: An understanding of injury profiles and mechanisms in Australian football is crucial in identifying methods to reduce injury risk and prepare players for the demands of the game.
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    Coding OSICS sports injury diagnoses in epidemiological studies: does the background of the coder matter?
    Finch, CF ; Orchard, JW ; Twomey, DM ; Saleem, MS ; Ekegren, CL ; Lloyd, DG ; Elliott, BC (BMJ PUBLISHING GROUP, 2014-04)
    OBJECTIVE: To compare Orchard Sports Injury Classification System (OSICS-10) sports medicine diagnoses assigned by a clinical and non-clinical coder. DESIGN: Assessment of intercoder agreement. SETTING: Community Australian football. PARTICIPANTS: 1082 standardised injury surveillance records. MAIN OUTCOME MEASUREMENTS: Direct comparison of the four-character hierarchical OSICS-10 codes assigned by two independent coders (a sports physician and an epidemiologist). Adjudication by a third coder (biomechanist). RESULTS: The coders agreed on the first character 95% of the time and on the first two characters 86% of the time. They assigned the same four-digit OSICS-10 code for only 46% of the 1082 injuries. The majority of disagreements occurred for the third character; 85% were because one coder assigned a non-specific 'X' code. The sports physician code was deemed correct in 53% of cases and the epidemiologist in 44%. Reasons for disagreement included the physician not using all of the collected information and the epidemiologist lacking specific anatomical knowledge. CONCLUSIONS: Sports injury research requires accurate identification and classification of specific injuries and this study found an overall high level of agreement in coding according to OSICS-10. The fact that the majority of the disagreements occurred for the third OSICS character highlights the fact that increasing complexity and diagnostic specificity in injury coding can result in a loss of reliability and demands a high level of anatomical knowledge. Injury report form details need to reflect this level of complexity and data management teams need to include a broad range of expertise.