Sports-related concussion and its subsequent management have become a top priority within the sports medicine research spectrum. In order to properly understand the complex nature of concussion management, multiple aspects of the injury were explored including the psychobiological nature of the injury, risk for further injury, diagnostic concerns, and return to play decision making. While much research has been dedicated to these areas, one in particular, return to play, is the focus of this current research study. To date, there has not been a method for accurately predicting return to play time after an athlete has sustained sports-related concussion. In order to advance the understanding of return to play and the clinical management of concussion, the current study applied a unique statistical methodology to empirically develop an equation to predict average return to play time using a set of post-injury variables. This equation predicted average return to play time with significant accuracy and resulted in a strong correlation between predicted return to play time and observed return to play time. Importantly, the predication equation was moderately stable across multiple samples. The results suggest that return to play time can be successfully predicted via a set of post-injury variables. Thus, the understanding of concussion severity as well as the clinical management of the injury can be improved by providing clinicians with a better estimate of the length of time an athlete will be unable to participate in a given activity before full recovery.
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