Intercollegiate ice hockey injuries

Pelletier, Robert L.; Montelpare, William; Stark, Ryan M.

doi:10.1177/036354659302100114

Cited by 71 publications

(21 citation statements)

References 14 publications

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“…Multiple studies have reported ice hockey injury rates across different age groups, skill levels, and countries. 7 , 13 , 14 , 17 , 18 , 20 , 24 , 29 - 31 , 34 , 35 , 37 , 38 While a consensus on injury rate is difficult to determine, given the use of different definitions of injury and athlete exposure, a trend for a higher risk of injury during games compared with practices is consistent across all studies. 7 , 14 , 17 , 18 , 20 , 30 , 37 , 38 Whether the risk of injury depends on the player position, however, has not been agreed on.…”

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confidence: 93%

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

et al. 2014

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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/m2 was 2.1 times (95% CI, 1.1-3.8) that of a player with a BMI <25 kg/m2. 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.

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confidence: 93%

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

et al. 2014

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“…Concussion in ice hockey accounts for 6-14% of all sport-related injuries and has an incidence of 1.5 to 18.7 per 1000 player -game hours (Covassin, Swanik, & Sachs, 2003;Jørgensen & Schmidt-Olsen, 1986;Koh, Cassidy, & Watkinson, 2003;Pelletier, Montelpare, & Stark, 1993;Tegner & Lorentzon, 1996). While symptoms typically resolve spontaneously over a short period of time, some cases require a lengthy period of time to fully recover (Binder, Rohling, & Larrabee, 1997;McCrory et al, 2013) and may lead to the early onset of dementia (Guskiewicz et al, 2005) and chronic traumatic encephalopathy (Stern et al, 2011).…”

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confidence: 99%

Defining the effective impact mass of elbow and shoulder strikes in ice hockey

Rousseau

Hoshizaki

2015

Sports Biomechanics

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Reconstruction of real-life events can be used to investigate the relationship between the mechanical parameters of the impact and concussion risk. Striking mass has typically been approximated as being the mass of the body part coming into contact with the head without accounting for the force applied by the striking athlete. Thus, the purpose of this study was to measure the effective impact mass of three common striking techniques in ice hockey. Fifteen participants were instructed to strike a suspended 50th percentile Hybrid III headform at least three times with their elbow or shoulder. Effective impact mass was calculated by measuring the change in velocity of the player and the headform. Mean effective impact mass for the extended elbow, tucked-in elbow, and shoulder check conditions were 4.8, 3.0, and 12.9 kg, respectively. Peak linear accelerations were lower than the values associated with concussion in American football which could be a reflection of the methodology used in this study as well as inherent differences between both sports.

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“…3,5,9,10,16 Athlete exposure was defined as an officially scheduled on-ice practice or game in which the athlete at least partially participated. The mechanism of injury was categorized by impact with another player, ice, puck/stick, or board/goal or by noncontact acute injury.…”

Section: Methodsmentioning

confidence: 99%

“…1,3,10,13,15,16 MCL injuries result in substantial time lost from competition, ranking third behind syndesmosis sprains and concussions. 1,3,5,12,13 Over 3 seasons of elite Swedish hockey, MCL injuries represented 5 of 8 injuries resulting in more than 30 days lost from competition.…”

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Incidence and Injury Characteristics of Medial Collateral Ligament Injuries in Male Collegiate Ice Hockey Players

Grant

Bedi

Kurz³

et al. 2013

Sports Health

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Background:Medial collateral ligament (MCL) injuries are the second most common injury resulting in player lost time in elite-level ice hockey.Purpose:To determine the incidence and injury characteristics of knee MCL sprain in male collegiate ice hockey players.Study Design:Case control.Methods:Athlete exposure data demographics, mechanism of injury, player position, time of injury occurrence (game vs practice), grade of MCL sprain, concomitant injuries, and lost time for cases were extracted from a computerized injury database of 8 college hockey seasons at 1 university. MCL injury rates were calculated. Injury characteristics were descriptively summarized. Simple linear regression was utilized to determine the relationship between the grade of MCL injury and player lost time.Results:There were 13 MCL injuries in 10 players. The overall incidence rate was 0.44 injuries per 1000 athlete exposures. Two players suffered reinjuries. Defensemen and forwards were equally represented. Contact with another player or the ice was the mechanism of injury in 77% of players. Grade 2 injuries were most common. The grade of injury predicted time lost from play (P < 0.01).Conclusion and Clinical Relevance:The lost time relates directly to the severity of injury.

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Intercollegiate ice hockey injuries

Cited by 71 publications

References 14 publications

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

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

Defining the effective impact mass of elbow and shoulder strikes in ice hockey

Incidence and Injury Characteristics of Medial Collateral Ligament Injuries in Male Collegiate Ice Hockey Players

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