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Preseason periodic health examination (PHE) is used routinely in elite football (soccer) and can be used to inform injury prevention strategies. Indirect muscle injuries (IMI) are a considerable burden to elite teams. This investigation aims to evaluate whether measurements from PHE can be used in a multivariable model to predict IMI risk in elite players, or to establish prognostic factors that are associated with IMIs.
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BACKGROUND Indirect muscle injuries (IMIs) are a considerable burden to elite football (soccer) teams and prevention of these injuries offers many benefits. Preseason medical, musculoskeletal and performance screening (termed periodic health examination (PHE)) is used to help determine players at risk of injuries such as IMIs, where identification of PHE-derived prognostic factors (PF) may inform IMI prevention strategies. Furthermore, using several PFs in combination within a multivariable prognostic model may allow individualised IMI risk estimation and specific targeting of prevention strategies, based upon an individual's PF profile. No such models have been developed in elite football and the current IMI prognostic factor evidence is limited. This study aims to: 1) to develop and internally validate a prognostic model for individualised IMI risk prediction during a season in elite footballers, using the extent of the prognostic evidence and clinical reasoning; 2) explore potential PHE-derived PFs associated with IMI outcomes in elite footballers, using available PHE data from a professional team.
METHODS A retrospective review has been completed of PHE and injury data, routinely collected over 5 years (from 1st July 2013 to 19th May 2018) from a population of elite male players at an English Premier League football club. Of 60 candidate PFs, 15 were excluded. Ten factors will be included in model development, identified from a systematic review, missing data assessment, measurement reliability evaluation and clinical reasoning. A full multivariable logistic regression model will be fitted, to ensure adjustment before backward elimination. The performance and internal validation of the model will be assessed. The remaining 35 candidate PFs are eligible for further exploration, using univariable logistic regression to obtain unadjusted risk estimates. Exploratory PFs will be grouped according to type and incorporated into multivariable logistic regression models to determine risk estimates.
DISCUSSION This study will offer insights into clinical usefulness of a model to predict IMI risk in elite football and highlight the practicalities of model development in this setting. Exploration may identify other relevant PFs for future confirmatory studies, model updating, or influence future injury prevention research.
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321 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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