A critical evaluation of biomechanical risk factors for ACL injuries during dynamic activities

Abstract

For injury screening to effectively identify individuals with at-risk behaviours, risk factors should be identified and validated carefully through appropriate prospective study designs. In the context of injury prevention in sport, the main aim of screening is to draw a line between those who are at risk of getting injured and those who are not. In order to effectively screen for anterior cruciate ligament (ACL) injury risk, injury screening should not be based on a singular observation in a single task as it is unlikely to effectively identify those who are at risk with acceptable sensitivity and specificity. Observations of ACL injury could be evaluated through a more mechanism-informed risk factors as this may provide a better justification of an individual’s movement pattern. If an individual who is at risk would demonstrate a particular behaviour across different tasks, this collection of variables characterising an individuals’ at-risk behaviours across tasks could form an individual’s “movement signature”. This thesis therefore aimed to critically evaluate the biomechanical risk factors for non-contact ACL injury during dynamic sporting activities and to explore some novel approaches to characterising movement characteristics for screening. Through a systematic review, the first study in this thesis critically evaluated the current research trends on the in vivo biomechanical risk factors of the ACL injury in dynamic activities and identified a lack of high quality (level 1), prospective evidence. Only one prospective cohort study was identified; therefore, more prospective cohort studies are required as research since the time of this systematic review did not provide further prospective evidence. Study two sought to develop more prospective evidence but unfortunately no ACL injuries were observed therefore, no new biomechanical risk factors for ACL injury could be identified. Utilizing the data collected from the prospective cohort, study three led to the development of a novel approach of injury screening by verifying the existence of individual movement signatures. The task-invariant movement signatures were also able to identify at-risk movement behaviour. Further exploration of mechanism informed multi-planar variables in study four showed that task-invariant movement signatures also exist in multi-planar variables, and may better inform at-risk behaviours. This thesis has furthered the understanding of biomechanical risk factors and moved towards the development of more effective injury screening tools.