Frequency and Location of Head Impacts in Division I Men's Lacrosse Players

Miyashita, Theresa; Diakogeorgiou, Eleni; Marrie, Kaitlyn; Danaher, Rosemary

doi:10.3928/19425864-20160503-01

Cited by 13 publications

(19 citation statements)

References 27 publications

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“…Similarly, our findings demonstrated midfielders to suffer the greatest number of direct head impacts, followed by attackers and defenders. Our findings are also similar to those of Miyashita et al 24 in that we found goalies to sustain the fewest number of direct head impacts, with the majority due to being struck by the ball. However, we were able to account for athlete exposure by position, enabling the calculation of impact rates by position.…”

Section: Discussionsupporting

confidence: 91%

“…In comparison with other lacrosse research, the magnitudes for game-related head impacts in our study are challenging to contextualize. The median PLA of head impacts measured in our study was lower than that reported by Miyashita et al 24 (∼48.8 g ) but higher than that reported by Reynolds et al 29 (∼24.7 g ) during collegiate men’s Division I lacrosse game play. However, our median PLA was similar to a recent report in Division III game play (∼32.5 g ).…”

Section: Discussioncontrasting

confidence: 78%

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Game-Related Impacts in High School Boys’ Lacrosse

Caswell

Kelshaw

Lincoln

et al. 2019

Orthopaedic Journal of Sports Medicine

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Background: The rate of concussions in boys’ lacrosse is reported to be the third highest among high school sports in the United States, but no studies have described game-related impacts among boys’ lacrosse players. Purpose: To characterize verified game-related impacts, both overall and those directly to the head, in boys’ varsity high school lacrosse. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 77 male participants (mean age, 16.6 ± 1.2 years; mean height, 1.77 ± 0.05 m; mean weight, 73.4 ± 12.2 kg) were instrumented with sensors and were videotaped during 39 games. All verified game-related impacts ≥20 g were summarized in terms of frequency, peak linear acceleration (PLA), and peak rotational velocity (PRV). Descriptive statistics and impact rates per player-game (PG) with corresponding 95% CIs were calculated. Results: Overall, 1100 verified game-related impacts were recorded (PLA: median, 33.5 g [interquartile range (IQR), 25.7-51.2]; PRV: median, 1135.5 deg/s [IQR, 790.0-1613.8]) during 795 PGs. The rate for all verified game-related impacts was 1.38 impacts per PG (95% CI, 1.30-1.47). Of these, 680 (61.8%) impacts (PLA: median, 35.9 g [IQR, 26.7-55.5]; PRV: 1170.5 deg/s [IQR, 803.2-1672.8]) were directly to the head (impact rate, 0.86 impacts/PG [95% CI, 0.79-0.92]). Overall, midfielders (n = 514; 46.7%) sustained the most impacts, followed by attackers (n = 332; 30.2%), defenders (n = 233; 21.2%), and goalies (n = 21; 1.9%). The most common mechanisms for overall impacts and direct head impacts were contact with player (overall: n = 706 [64.2%]; head: n = 397 [58.4%]) and stick (overall: n = 303 [27.5%]; head: n = 239 [35.1%]), followed by ground (overall: n = 73 [6.6%]; head: n = 26 [3.8%]) and ball (overall: n = 15 [1.4%]; head: n = 15 [2.2%]). Direct head impacts were associated with a helmet-to-helmet collision 31.2% of the time, and they were frequently (53.7%) sustained by the players delivering the impact. Nearly half (48.8%) of players delivering contact used their helmets to initiate contact that resulted in a helmet-to-helmet impact. Players receiving a head impact from player contact were most often unprepared (75.9%) for the collision. Conclusion: The helmet is commonly used to initiate contact in boys’ high school lacrosse, often targeting defenseless opponents. Interventions to reduce head impacts should address rules and coaching messages to discourage intentional use of the helmet and encourage protection of defenseless opponents.

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Section: Discussionsupporting

confidence: 91%

Section: Discussioncontrasting

confidence: 78%

Game-Related Impacts in High School Boys’ Lacrosse

Caswell

Kelshaw

Lincoln

et al. 2019

Orthopaedic Journal of Sports Medicine

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“…In contrast, several studies raised the linear acceleration trigger threshold to 20 g in an attempt to reduce low magnitude false positives. [5][6][7]14,22,26,29 Press et al 33 found that the positive predictive value of the xPatch algorithm increased from 16% to 66% when the threshold was increased from 10 g to 20 g, respectively. Similarly, Carey et al 4 evaluated the xPatch during adult semi-professional male rugby league games and determined 31% of sensor-recorded events above 10 g were false positives from video confirmation, which decreased to 6% for events above 20 g. However, it is likely that the particular recording threshold of linear and angular acceleration magnitude and duration varies by sport and sensor.…”

Section: Filtering Algorithmsmentioning

confidence: 99%

“…10,34,35,40,41 Recent technological advances have enabled the development of head impact sensors to estimate the head impact exposure of human subjects in vivo. 31 A wide variety of head impact sensors is currently available, such as instrumented helmets (e.g., GForceTracker), 5,7,26 headbands (e.g., SIM-G), 18,32,43 mouthguards (e.g., MIG) 16,46 and skin patches (e.g., xPatch). 23,28,33 Increasingly, research studies have used such technology to collect head impact data in sports, commonly American football.…”

Section: Introductionmentioning

confidence: 99%

Head Impact Sensor Studies In Sports: A Systematic Review Of Exposure Confirmation Methods

et al. 2020

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To further the understanding of long-term sequelae as a result of repetitive head impacts in sports, in vivo head impact exposure data are critical to expand on existing evidence from animal model and laboratory studies. Recent technological advances have enabled the development of head impact sensors to estimate the head impact exposure of human subjects in vivo. Previous research has identified the limitations of filtering algorithms to process sensor data. In addition, observer and/or video confirmation of sensor-recorded events is crucial to remove false positives. The purpose of the current study was to conduct a systematic review to determine the proportion of published head impact sensor data studies that used filtering algorithms, observer confirmation and/or video confirmation of sensor-recorded events to remove false positives. Articles were eligible for inclusion if collection of head impact sensor data during live sport was reported in the methods section. Descriptive data, confirmation methods and algorithm use for included articles were coded. The primary objective of each study was reviewed to identify the primary measure of exposure, primary outcome and any additional covariates. A total of 168 articles met the inclusion criteria, the publication of which has increased in recent years. The majority used filtering algorithms (74%). The majority did not use observer and/or video confirmation for all sensor-recorded events (64%), which suggests estimates of head impact exposure from these studies may be imprecise.

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“…One study implemented the GForceTracker in men's collegiate lacrosse to study head impact frequency and location; goalies had the highest magnitude of impact whereas face-off players had the lowest (Miyashita et al, 2016). Other technologies developed to integrate with headbands or skull caps include the Shockbox (Impakt Protective Inc., Kanata, ON), the Checklight (Reebok International, Ltd., Canton, MA and MC10 Inc., Cambridge, MA) and the SIM-P and SIM-G (Triax Technologies Inc., Norwalk, CT) (Cummiskey, 2015).…”

Section: Other Wearable Sensorsmentioning

confidence: 99%

Evaluation of the Efficacy of Head and Brain Injury Risk Functions

Sanchez¹

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Head and brain injury risk functions have been proposed over the years in order to estimate the probability of brain injury from head impact using kinematic and injury data from various sources, such as PMHS and animal testing. Yet, researchers have reiterated the need for human head kinematic data for creating and evaluating injury risk functions and risk assessment values given that other types of data may lack the physiologic and anthropometric response required. To this end, this thesis aimed to collect human head kinematics to evaluate existing injury risk functions. A literature review revealed what measures of human head motion have been previously published, including direct measures of head kinematics (e.g., wearable sensors used on-field with contact athletes) and indirect measures of head motion (e.g., computational and experimental reconstructions of real-life impacts). Three data sources (n = 443) were selected from the literature based on inclusion criteria. Data were evaluated for consistency and used to calculate kinematic and strain-based injury risks. The injury risk values were used to evaluate the efficacy of each of 16 injury risk functions using four separate analytical tools. Correlations between the injury risk functions and strain metrics showed that strain-and rotationally-based injury risk functions had the strongest correlations. Area under ROC curves assessed each function's ability to separate injurious and non-injurious impacts; all risk functions were better than random guessing. Likelihood estimates ranked the injury risk functions on their ability to correctly predict the dataset's injury outcomes, with GAMBIT showing the best predictive capability according to this measure. The number of expected injuries was calculated for each risk function; however, most did not correctly estimate the number of observed injuries (n = 31). Results from these four assessment tools, however, were mixed, with no single risk function performing best. The lack of consensus in the assessment tools may be a result of the data used to develop the risk functions. Studies have noted unbiased exposure data is needed to estimate the absolute injury risk from impact; however, most injury risk functions (and the data in this thesis) were based on case-control data. Statistical simulations were conducted to create injury risk functions based on several sampling scenarios. These results from these simulations demonstrated that researchers should be wary of risk curves derived solely from case-controlled data given that these may be over-predictive of injury probabilities compared to the absolute risk of a population. Despite the issues with the risk functions, this thesis provides a verified data set that is a necessary step for injury risk function evaluation.

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Frequency and Location of Head Impacts in Division I Men's Lacrosse Players

Cited by 13 publications

References 27 publications

Game-Related Impacts in High School Boys’ Lacrosse

Game-Related Impacts in High School Boys’ Lacrosse

Head Impact Sensor Studies In Sports: A Systematic Review Of Exposure Confirmation Methods

Evaluation of the Efficacy of Head and Brain Injury Risk Functions

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