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Ability of Preseason Body Composition and Physical Fitness to Predict the Risk of Injury in Male Collegiate Hockey Players

BACKGROUND: Injuries in collegiate ice hockey can result in significant time lost from play. The identification of modifiable risk factors relating to a player’s physical fitness allows the development of focused training and injury prevention programs targeted at reducing these risks. PURPOSE: To d...

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Detalles Bibliográficos
Autores principales: Grant, John A., Bedi, Asheesh, Kurz, Jennifer, Bancroft, Richard, Gagnier, Joel J., Miller, Bruce S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272692/
https://www.ncbi.nlm.nih.gov/pubmed/25553212
http://dx.doi.org/10.1177/1941738114540445
Descripción
Sumario:BACKGROUND: Injuries in collegiate ice hockey can result in significant time lost from play. The identification of modifiable risk factors relating to a player’s physical fitness allows the development of focused training and injury prevention programs targeted at reducing these risks. PURPOSE: To determine the ability of preseason fitness outcomes to predict in-season on-ice injury in male collegiate ice hockey players. STUDY DESIGN: Prognostic cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: Athlete demographics, percentage body fat, aerobic capacity (300-m shuttle run; 1-, 1.5-, 5-mile run), and strength assessment (sit-ups, push-ups, grip strength, bench press, Olympic cleans, squats) data were collected at the beginning of 8 successive seasons for 1 male collegiate ice hockey team. Hockey-related injury data and player-level practice/game athlete exposure (AE) data were also prospectively collected. Seventy-nine players participated (203 player-years). Injury was defined as any event that resulted in the athlete being unable to participate in 1 or more practices or games following the event. Multivariable logistic regression was performed to determine the ability of the independent variables to predict the occurrence of on-ice injury. RESULTS: There were 132 injuries (mean, 16.5 per year) in 55 athletes. The overall injury rate was 4.4 injuries per 1000 AEs. Forwards suffered 68% of the injuries. Seventy percent of injuries occurred during games with equal distribution between the 3 periods. The mean number of days lost due to injury was 7.8 ± 13.8 (range, 1-127 days). The most common mechanism of injury was contact with another player (54%). The odds of injury in a forward was 1.9 times (95% CI, 1.1-3.4) that of a defenseman and 3 times (95% CI, 1.2-7.7) that of a goalie. The odds of injury if the player’s body mass index (BMI) was ≥25 kg/m(2) was 2.1 times (95% CI, 1.1-3.8) that of a player with a BMI <25 kg/m(2). The odds ratios for bench press, maximum sit-ups, and Olympic cleans were statistically significant but close to 1.0, and therefore the clinical relevance is unknown. CONCLUSION: Forwards have higher odds of injury relative to other player positions. BMI was predictive of on-ice injury. Aerobic fitness and maximum strength outcomes were not strongly predictive of on-ice injury.