Time-to-event analysis for sports injury research part 1 : Time-varying exposures
- Authors: Nielsen, Rasmus , Bertelsen, Michael , Ramskov, Daniel , Møller, Merete , Hulme, Adam , Theisen, Daniel , Finch, Caroline , Fortington, Lauren , Mansournia, Mohammad , Parner, Erik
- Date: 2019
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 53, no. 1 (2019), p. 61-68
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- Description: Background: 'How much change in training load is too much before injury is sustained, among different athletes?' is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. Aim: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. Content: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. Conclusion: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data. © 2019 Author(s).
Time-to-event analysis for sports injury research part 2 : Time-varying outcomes
- Authors: Nielsen, Rasmus , Bertelsen, Michael , Ramskov, Daniel , Møller, Merete , Hulme, Adam , Theisen, Daniel , Finch, Caroline , Fortington, Lauren , Mansournia, Mohammad , Parner, Erik
- Date: 2019
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 53, no. 1 (2019), p. 70-78
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- Description: Background: Time-to-event modelling is underutilised in sports injury research. Still, sports injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the sports injury domain. Content: In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete. Conclusion: Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future sports injury research, we need stratified analyses if the target of our research is to respond to the question: 'how much change in training load is too much before injury is sustained, among athletes with different characteristics?' Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.
Is subsequent lower limb injury associated with previous injury? A systematic review and meta-analysis
- Authors: Toohey, Liam , Drew, Michael , Cook, Jill , Finch, Caroline , Gaida, Jamie
- Date: 2017
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 51, no. 23 (2017), p. 1670-1678
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- Description: Background Previous injury is a strong risk factor for recurrent lower limb injury in athletic populations, yet the association between previous injury and a subsequent injury different in nature or location is rarely considered. Objective To systematically review data on the risk of sustaining a subsequent lower limb injury different in nature or location following a previous injury. Methods Eight medical databases were searched. Studies were eligible if they reported lower limb injury occurrence following any injury of a different anatomical site and/or of a different nature, assessed injury risk, contained athletic human participants and were written in English. Two reviewers independently applied the eligibility criteria and performed the risk of bias assessment. Meta-analysis was conducted using a random effects model. Results Twelve studies satisfied the eligibility criteria. Previous history of an ACL injury was associated with an increased risk of subsequent hamstring injury (three studies, RR=2.25, 95% CI 1.34 to 3.76), but a history of chronic groin injury was not associated with subsequent hamstring injury (three studies, RR=1.14, 95% CI 0.29 to 4.51). Previous lower limb muscular injury was associated with an increased risk of sustaining a lower limb muscular injury at a different site. A history of concussion and a variety of joint injuries were associated with an increased subsequent lower limb injury risk. Conclusions The fact that previous injury of any type may increase the risk for a range of lower limb subsequent injuries must be considered in the development of future tertiary prevention programmes. Systematic review registration number CRD42016039904 (PROSPERO). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
The new concussion in sport guidelines are here. But how do we get them out there?
- Authors: Finch, Caroline , White, Peta
- Date: 2017
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 51, no. 24 (2017), p. 1734-1736
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Towards the reduction of injury and illness in athletes : Defining our research priorities
- Authors: Finch, Caroline , Bahr, Roald , Drezner, Jonathan , Dvorak, Jiri , Engebretsen, Lars , Hewett, Timothy , Junge, Astrid , Khan, Karim , Macauley, Domhnall , Matheson, Gordon , McCrory, Paul , Verhagen, Evert
- Date: 2017
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 51, no. 16 (2017), p. 1178-1182
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
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Sports-related workload and injury risk : Simply knowing the risks will not prevent injuries : Narrative review
- Authors: Drew, Michael , Cook, Jill , Finch, Caroline
- Date: 2016
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 50, no. 21 (2016), p. 1306-1309
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
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- Description: Training loads contribute to sports injury risk but their mitigation has rarely been considered in a sports injury prevention framework. A key concept behind monitoring training loads for injury prevention is to screen for those at increased risk of injury so that workloads can be adjusted to minimise these risks. This review describes how advances in management of workload can be applied as a preventive measure. Primary prevention involves screening for preparticipation load risk factors, such as low training loads, prior to a training period or competition. Secondary prevention involves screening for workloads that are known to precede an injury developing so that modification can be undertaken to mitigate this risk. Tertiary prevention involves rehabilitation practices that include a graded return to training programme to reduce the risk of sustaining a subsequent injury. The association of training loads with injury incidence is now established. Prevention measures such as rule changes that affect the workload of an athlete are universal whereas those that address risk factors of an asymptomatic subgroup are more selective. Prevention measures, when implemented for asymptomatic individuals exhibiting possible injury risk factors, are indicated for an athlete at risk of developing a sports injury. Seven key indicated risks and associated prevention measures are proposed.