What is the definition of sports-related concussion : A systematic review
- McCrory, Paul, Feddermann-Demont, Nina, Dvorak, Jiri, Cassidy, David, McIntosh, Andrew, Vos, Pieter, Echemendia, Ruben, Meeuwisse, Willem, Tarnutzer, Alexander
- Authors: McCrory, Paul , Feddermann-Demont, Nina , Dvorak, Jiri , Cassidy, David , McIntosh, Andrew , Vos, Pieter , Echemendia, Ruben , Meeuwisse, Willem , Tarnutzer, Alexander
- Date: 2017
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 51, no. 11 (2017), p. 877-887
- Full Text:
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- Description: Objectives: Various definitions for concussion have been proposed, each having its strengths and weaknesses. We reviewed and compared current definitions and identified criteria necessary for an operational definition of sports-related concussion (SRC) in preparation of the 5th Concussion Consensus Conference (Berlin, Germany). We also assessed the role of biomechanical studies in informing an operational definition of SRC. Design: This is a systematic literature review. Data sources: Data sources include MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Clinical Trials and SPORT Discus (accessed 14 September 2016). Eligibility criteria for selecting studies: Eligibility criteria were studies reporting (clinical) criteria for diagnosing SRC and studies containing SRC impact data. Results: Out of 1601 articles screened, 36 studies were included (2.2%), 14 reported on criteria for SRC definitions and 22 on biomechanical aspects of concussions. Six different operational definitions focusing on clinical findings and their dynamics were identified. Biomechanical studies were obtained almost exclusively on American football players. Angular and linear head accelerations linked to clinically confirmed concussions demonstrated considerable individual variation. Summary/conclusions: SRC is a traumatic brain injury that is defined as a complex pathophysiological process affecting the brain, induced by biomechanical forces with several common features that help define its nature. Limitations identified include that the current criteria for diagnosing SRC are clinically oriented and that there is no gold/standard to assess their diagnostic properties. A future, more valid definition of SRC would better identify concussed players by demonstrating high predictive positive/negative values. Currently, the use of helmet-based systems to study the biomechanics of SRC is limited to few collision sports. New approaches need to be developed to provide objective markers for SRC. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved.
- Authors: McCrory, Paul , Feddermann-Demont, Nina , Dvorak, Jiri , Cassidy, David , McIntosh, Andrew , Vos, Pieter , Echemendia, Ruben , Meeuwisse, Willem , Tarnutzer, Alexander
- Date: 2017
- Type: Text , Journal article , Review
- Relation: British Journal of Sports Medicine Vol. 51, no. 11 (2017), p. 877-887
- Full Text:
- Reviewed:
- Description: Objectives: Various definitions for concussion have been proposed, each having its strengths and weaknesses. We reviewed and compared current definitions and identified criteria necessary for an operational definition of sports-related concussion (SRC) in preparation of the 5th Concussion Consensus Conference (Berlin, Germany). We also assessed the role of biomechanical studies in informing an operational definition of SRC. Design: This is a systematic literature review. Data sources: Data sources include MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Clinical Trials and SPORT Discus (accessed 14 September 2016). Eligibility criteria for selecting studies: Eligibility criteria were studies reporting (clinical) criteria for diagnosing SRC and studies containing SRC impact data. Results: Out of 1601 articles screened, 36 studies were included (2.2%), 14 reported on criteria for SRC definitions and 22 on biomechanical aspects of concussions. Six different operational definitions focusing on clinical findings and their dynamics were identified. Biomechanical studies were obtained almost exclusively on American football players. Angular and linear head accelerations linked to clinically confirmed concussions demonstrated considerable individual variation. Summary/conclusions: SRC is a traumatic brain injury that is defined as a complex pathophysiological process affecting the brain, induced by biomechanical forces with several common features that help define its nature. Limitations identified include that the current criteria for diagnosing SRC are clinically oriented and that there is no gold/standard to assess their diagnostic properties. A future, more valid definition of SRC would better identify concussed players by demonstrating high predictive positive/negative values. Currently, the use of helmet-based systems to study the biomechanics of SRC is limited to few collision sports. New approaches need to be developed to provide objective markers for SRC. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved.
Time-to-event analysis for sports injury research part 1 : Time-varying exposures
- Nielsen, Rasmus, Bertelsen, Michael, Ramskov, Daniel, Møller, Merete, Hulme, Adam, Theisen, Daniel, Finch, Caroline, Fortington, Lauren, Mansournia, Mohammad, Parner, Erik
- 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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- Reviewed:
- 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).
- 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
- Full Text:
- Reviewed:
- 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
- Nielsen, Rasmus, Bertelsen, Michael, Ramskov, Daniel, Møller, Merete, Hulme, Adam, Theisen, Daniel, Finch, Caroline, Fortington, Lauren, Mansournia, Mohammad, Parner, Erik
- 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
- Full Text:
- Reviewed:
- 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.
- 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
- Full Text:
- Reviewed:
- 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.
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