Statistical modelling for recurrent events: an application to sports injuries

Ullah, Shahid; Gabbett, Tim J.; Finch, Caroline F.

doi:10.1136/bjsports-2011-090803

Cited by 71 publications

(77 citation statements)

References 58 publications

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“…The SIC model needs further evaluation through application to other datasets, but the only way to do that is to put it out for evaluation by other epidemiologists. There will still be challenges in knowing how to best analyse the data classified according to the SIC model, but the frailty survival model approach recently advocated by Ullah and colleagues5 27 and multistate process survival models show promise.

What are the new findings?

This paper presents a new model to categorise subsequent (multiple, recurrent, exacerbation or new) sports injuries, derived from statistical considerations of dependencies between different injuries and sports medicine clinical considerations.

Greater capacity to classify subsequent injuries will allow improved understanding of the effect of initial injury on reinjury and injury exacerbations for both clinical management and injury prevention.

…”

Section: Discussionmentioning

confidence: 99%

Categorising sports injuries in epidemiological studies: the subsequent injury categorisation (SIC) model to address multiple, recurrent and exacerbation of injuries

2013

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ObjectiveSports injuries are often recurrent and there is wide recognition that a subsequent injury (of either the same or a different type) can be strongly influenced by a previous injury. Correctly categorising subsequent injuries (multiple, recurrent, exacerbation or new) requires substantial clinical expertise, but there is also considerable value in combining this expertise with more objective statistical criteria. This paper presents a new model, the subsequent injury categorisation (SIC) model, for categorising subsequent sports injuries that takes into account the need to include both acute and overuse injuries and ten different dependency structures between injury types.MethodsThe suitability of the SIC model was demonstrated with date ordered sports injury data from a large injury database from community Australian football players over one playing season. A subsequent injury was defined to have occurred in the subset of players with two or more reported injuries.Results282 players sustained 469 subsequent injuries of which 15.6% were coded to categories representing injuries that were directly related to previous index injuries. This demonstrates that players can sustain a number of injuries over one playing season. Many of these will be unrelated to previous injuries but subsequent injuries that are related to previous injury occurrences are not uncommon.ConclusionThe handling of subsequent sports injuries is a substantial challenge for the sports medicine field—both in terms of injury treatment and in epidemiological research to quantify them. Application of the SIC model allows for multiple different injury types and relationships within players, as well as different index injuries.

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What are the new findings?

…”

Section: Discussionmentioning

confidence: 99%

Categorising sports injuries in epidemiological studies: the subsequent injury categorisation (SIC) model to address multiple, recurrent and exacerbation of injuries

2013

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“…Though not frequently used, multilevel (ie, mixed) modelling approaches may allow for these analyses, since they can account for correlated outcomes (repeated measures among players), and include random effects to predict individual athletes’ risks 74–76. The frailty model which also allows random effects for players and the ability to control for the dependencies of recurrent injuries and repeated measures also shows promise 77 78…”

Section: Where To From Here—research Implicationsmentioning

confidence: 99%

How do training and competition workloads relate to injury? The workload—injury aetiology model

2016

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Injury aetiology models that have evolved over the previous two decades highlight a number of factors which contribute to the causal mechanisms for athletic injuries. These models highlight the pathway to injury, including (1) internal risk factors (eg, age, neuromuscular control) which predispose athletes to injury, (2) exposure to external risk factors (eg, playing surface, equipment), and finally (3) an inciting event, wherein biomechanical breakdown and injury occurs. The most recent aetiological model proposed in 2007 was the first to detail the dynamic nature of injury risk, whereby participation may or may not result in injury, and participation itself alters injury risk through adaptation. However, although training and competition workloads are strongly associated with injury, existing aetiology models neither include them nor provide an explanation for how workloads alter injury risk. Therefore, we propose an updated injury aetiology model which includes the effects of workloads. Within this model, internal risk factors are differentiated into modifiable and non-modifiable factors, and workloads contribute to injury in three ways: (1) exposure to external risk factors and potential inciting events, (2) fatigue, or negative physiological effects, and (3) fitness, or positive physiological adaptations. Exposure is determined solely by total load, while positive and negative adaptations are controlled both by total workloads, as well as changes in load (eg, the acute:chronic workload ratio). Finally, we describe how this model explains the load-injury relationships for total workloads, acute:chronic workload ratios and the training load-injury paradox.

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“…The paper compares different types of survival analysis models for subsequent event data through their application to prospectively collected professional rugby league injury data over one season. It shows how such models can be applied and explains why current common methods of analysis are inadequate for subsequent sports injury data 2. Extension of this modelling approach to risk factor identification has been published elsewhere 6…”

Section: Ioc Research Centres Of Excellencementioning

confidence: 99%

“…Together with clinical colleagues, the ACRISP epidemiologists and biostatisticians are advancing the design of, and reporting from, sports injury surveillance systems; contributing to international efforts to improve the coding/classification of sports injuries; informing international consensus statements for sports injury surveillance; and providing guidance on the appropriate statistical analysis of injury data. The two ACRISP research papers in this issue of BJSM IPHP are key recent outputs from this work until now 1 2…”

Section: Ioc Research Centres Of Excellencementioning

confidence: 99%

“…The second paper from ACRISP in this issue gives an overview of the statistical issues that need to be considered when analysing subsequent injury data 2. The paper compares different types of survival analysis models for subsequent event data through their application to prospectively collected professional rugby league injury data over one season.…”

Section: Ioc Research Centres Of Excellencementioning

confidence: 99%

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The IOC Centres of Excellence bring prevention to Sports Medicine

et al. 2014

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The protection of an athlete´s health and preventing injuries and illnesses in sport are top priorities for the International Olympic Committee (IOC) and its Medical Commission. The IOC therefore partners with selected research centres around the world and supports research in the field of sports medicine. This has enabled the IOC to develop an international network of expert scientists and clinicians in sports injury and disease prevention research. The IOC wants to promote injury and disease prevention and the improvement of physical health of the athlete by: (i) establishing long-term research programs on injury and disease prevention (including studies on basic epidemiology, risk factors, injury mechanisms and intervention), (ii) fostering collaborative relationships with individuals, institutions and organizations to improve athletes' health, (iii) implementing and collaborating with applied, on-going and novel research and development within the framework and long-term strategy of the IOC, and (iv) setting up knowledge translation mechanisms to share scientific research results with the field throughout the Olympic Movement and sports community and to convert these results into concrete actions to protect the health of the athletes. In 2009, the IOC also identified 4 research centres that had an established track record in research, educational and clinical activities to achieve these ambitious: (i) the Australian Centre

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Statistical modelling for recurrent events: an application to sports injuries

Cited by 71 publications

References 58 publications

Categorising sports injuries in epidemiological studies: the subsequent injury categorisation (SIC) model to address multiple, recurrent and exacerbation of injuries

Categorising sports injuries in epidemiological studies: the subsequent injury categorisation (SIC) model to address multiple, recurrent and exacerbation of injuries

How do training and competition workloads relate to injury? The workload—injury aetiology model

The IOC Centres of Excellence bring prevention to Sports Medicine

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