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Development of a risk prediction model among professional hockey players with visible signs of concussion
  1. Jared M Bruce1,
  2. Ruben J Echemendia1,2,
  3. Willem Meeuwisse3,
  4. Michael G Hutchison4,
  5. Mark Aubry5,
  6. Paul Comper4
  1. 1 Department of Psychology, University of Missouri - Kansas City, Kansas City, MO, USA
  2. 2 Psychological and Neurobehavioral Associates, State College, Pennsylvania, USA
  3. 3 Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
  4. 4 Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, Ontario, Canada
  5. 5 Ottawa Sport Medicine Center, Ottawa, Ontario, Canada
  1. Correspondence to Jared M Bruce, Department of Psychology, University of Missouri-Kansas City, 5030 Cherry Hall, Room 313, Kansas City, MO 64110, USA; brucejm{at}umkc.edu

Abstract

Background Little research examines how to best identify concussed athletes. The purpose of the present study was to develop a preliminary risk decision model that uses visible signs (VS) and mechanisms of injury (MOI) to predict the likelihood of subsequent concussion diagnosis.

Methods Coders viewed and documented VS and associated MOI for all NHL games over the course of the 2013–2014 and 2014–2015 regular seasons. After coding was completed, player concussions were identified from the NHL injury surveillance system and it was determined whether players exhibiting VS were subsequently diagnosed with concussions by club medical staff as a result of the coded event.

Results Among athletes exhibiting VS, suspected loss of consciousness, motor incoordination or balance problems, being in a fight, having an initial hit from another player’s shoulder and having a secondary hit on the ice were all associated with increased risk of subsequent concussion diagnosis. In contrast, having an initial hit with a stick was associated with decreased risk of subsequent concussion diagnosis. A risk prediction model using a combination of the above VS and MOI was superior to approaches that relied on individual VS and associated MOI (sensitivity=81%, specificity=72%, positive predictive value=26%).

Conclusions Combined use of VS and MOI significantly improves a clinician’s ability to identify players who need to be evaluated for possible concussion. A preliminary concussion prediction log has been developed from these data. Pending prospective validation, the use of these methods may improve early concussion detection and evaluation.

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Footnotes

  • Contributors JMB and RJE took primary responsibility for the design and execution of this study, including primary responsibility for writing the manuscript. JMB took primary responsibility for data analyses. WM was involved in the design of the study and contributed to the writing and critical editing of the manuscript. MGH was involved in the design of the study and contributed to the writing and critical editing of the manuscript. PC contributed to the design of the study and review of the manuscript. MA contributed to the design of the study and review of the manuscript.

  • Competing interests RJE is Co-Chair of the NHL/NHLPA Concussion Subcommittee. He receives financial compensation for consulting services from the NHL, Major League Soccer, US Soccer Federation, NCAA, and Princeton University. JMB is a part-time employee of the NHL who assists the NHL/NHLPA Concussion Subcommittee with program evaluation. He also works as a consultant to Sporting KC and the Princeton University Department of Athletic Medicine. WM is an employee of the NHL and a member of the NHL/NHLPA Concussion Subcommittee and Co-Chair of the NHL/NHLPA Joint Health and Safety Committee. PC is the co-chair of the NHL/PA Concussion Subcommittee and a consultant to the NHLPA, for which he receives remuneration. MH is a member of the NHL/NHLPA Concussion Subcommittee and a consultant to the NHLPA, for which he receives remuneration. MA is a member of the NHL/NHLPA Concussion Subcommittee.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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