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Concussion tolerance and head impact exposure are highly variable among football players. Recent findings highlight that head impact data analyses need to be performed at the subject level. In this paper, we describe a method of characterizing concussion risk between individuals using a new survival analysis technique developed with real-world head impact data in mind. Our approach addresses the limitations and challenges seen in previous risk analyses of football head impact data. Specifically, this demonstrative analysis appropriately models risk for a combination of left-censored recurrent events (concussions) and right-censored recurrent non-events (head impacts without concussion). Furthermore, the analysis accounts for uneven impact sampling between players. In brief, we propose using the Consistent Threshold method to develop subject-specific risk curves and then determine average risk point estimates between subjects at injurious magnitude values. We describe an approach for selecting an optimal cumulative distribution function to model risk between subjects by minimizing injury prediction error. We illustrate that small differences in distribution fit can result in large predictive errors. Given the vast amounts of on-field data researchers are collecting across sports, this approach can be applied to develop population-specific risk curves that can ultimately inform interventions that reduce concussion incidence.

ObjectiveTo study longitudinal recovery trajectories of white matter after sports-related concussion (SRC) by performing diffusion tensor imaging (DTI) on collegiate athletes who sustained SRC.MethodsCollegiate athletes (n = 219, 82 concussed athletes, 68 contact-sport controls, and 69 non–contact-sport controls) were included from the Concussion Assessment, Research and Education Consortium. The participants completed clinical assessments and DTI at 4 time points: 24 to 48 hours after injury, asymptomatic state, 7 days after return-to-play, and 6 months after injury. Tract-based spatial statistics was used to investigate group differences in DTI metrics and to identify white-matter areas with persistent abnormalities. Generalized linear mixed models were used to study longitudinal changes and associations between outcome measures and DTI metrics. Cox proportional hazards model was used to study effects of white-matter abnormalities on recovery time.ResultsIn the white matter of concussed athletes, DTI-derived mean diffusivity was significantly higher than in the controls at 24 to 48 hours after injury and beyond the point when the concussed athletes became asymptomatic. While the extent of affected white matter decreased over time, part of the corpus callosum had persistent group differences across all the time points. Furthermore, greater elevation of mean diffusivity at acute concussion was associated with worse clinical outcome measures (i.e., Brief Symptom Inventory scores and symptom severity scores) and prolonged recovery time. No significant differences in DTI metrics were observed between the contact-sport and non–contact-sport controls.ConclusionsChanges in white matter were evident after SRC at 6 months after injury but were not observed in contact-sport exposure. Furthermore, the persistent white-matter abnormalities were associated with clinical outcomes and delayed recovery time.

Researchers have been collecting head impact data from instrumented football players to characterize the biomechanics of concussion for the past 15 years, yet the link between biomechanical input and clinical outcome is still not well understood. We have previously shown that even though concussive biomechanics might be unremarkable in large datasets of head impacts, the impacts causing injury are of high magnitude for the concussed individuals relative to their impact history. This finding suggests a need to account for differences in tolerance at the individual level. In this study, we identified control subjects for our concussed subjects who demonstrated traits we believed were correlated to factors thought to affect injury tolerance, including height, mass, age, race, and concussion history. A total of 502 college football players were instrumented with helmet-mounted accelerometer arrays and provided complete baseline assessment data, 44 of which sustained a total of 49 concussion. Biomechanical measures quantifying impact frequency and acceleration magnitude were compared between groups. On average, we found that concussed subjects experienced 93.8 more head impacts (p = 0.0031), 10.2 more high magnitude impacts (p = 0.0157), and 1.9 × greater risk-weighted exposure (p = 0.0175) than their physically matched controls. This finding provides further evidence that head impact data need to be considered at the individual level and that cohort wide assessments may be of little value in the context of concussion. Published version

Introduction Regulatory efforts toward reducing concussion risk have begun to focus on decreasing the number of head impacts (i.e., head impact burden) sustained by athletes in contact sports. To that end, in 2018, the NCAA decreased the number of preseason on-field team activities for Division I teams from 29 to 25. The objective of the current study was to quantify changes in practice schedule and head impact exposure between the 2017 and 2018 football preseasons. Methods Athletes from five NCAA Division I football teams (n = 426) were consented and enrolled. Results On average, athletes participated in 10% fewer contact practices in 2018. However, the effect of this ruling on preseason head impact burden was mixed. Across all athletes, the total preseason head impact burden was essentially the same from 2017 to 2018. However, this study revealed significant team-by-team differences in preseason head impact burden, with one team demonstrating a 35% increase in the average number of recorded head impacts from 2017 to 2018, despite a modest decrease in the number of contact practices. Other teams had similar or decreased head impact burden. Conclusions Team-based differences in total preseason head impact burden were attributable to changes in daily practice schedule, with longer practice durations and more intense contact practice sessions contributing to increases in daily head impact exposure that, in turn, led to greater preseason head impact burden. Results of this study have highlighted the difficulty in decreasing contact sport head impact exposure through rule changes targeted at limiting on-field team activities. Future efforts aimed specifically at contact practice duration, daily head impact exposure, or limiting time in specific drills may be more effective at reducing total preseason head impact burden.

Repetitive head impact exposure sustained by athletes of contact sports has been hypothesized to be a mechanism for concussion and a possible explanation for the high degree of variability in sport-related concussion biomechanics. In an attempt to limit repetitive head impact exposure during the football preseason, the NCAA eliminated two-a-day practices in 2017, while maintaining the total number of team practice sessions. The objective of this study was to quantify head impact exposure during the preseason and regular season in Division I college football athletes to determine whether the 2017 NCAA ruling decreased head impact exposure. 342 unique athletes from five NCAA Division I Football Bowl Subdivision (FBS) programs were consented and enrolled. Head impacts were recorded using the Head Impact Telemetry (HIT) System during the entire fall preseasons and regular seasons in 2016 and 2017. Despite the elimination of two-a-day practices, the number of preseason contact days increased in 2017, with an increase in average hourly impact exposure (i.e., contact intensity), resulting in a significant increase in total head impact burden (+ 26%) for the 2017 preseason. This finding would indicate that the 2017 NCAA ruling was not effective at reducing the head impact burden during the football preseason. Additionally, athletes sustained a significantly higher number of recorded head impacts per week (+ 40%) during the preseason than the regular season, implicating the preseason as a time of elevated repetitive head impact burden. With increased recognition of a possible association between repetitive head impact exposure and concussion, increased preseason exposure may predispose certain athletes to a higher risk of concussion during the preseason and regular season. Accordingly, efforts at reducing concussion incidence in contact sports should include a reduction in overall head impact exposure.

Biomechanical data collected from head impacts in football have been used to characterize exposure and predict injury risk. This study sought to specifically quantify the factors that contribute towards player head impact exposure in college football practices. All players included in this study were outfitted with football helmets instrumented with accelerometer arrays (Head Impact Telemetry System). Head impact exposure was defined by the number of head impacts each player experienced in practice, the number of practice head impacts normalized by the number of practice sessions (practice head impact rate), and the 95th percentile linear and rotational resultant head impact accelerations. Practice head impact rate was observed to vary significantly with player position (p

Concussion is a brain injury induced by biomechanical forces that is broadly defined as a complex pathophysiological process affecting the brain. The intricate link between biomechanical input and concussion injury response is poorly understood. We aimed to test the hypothesis that greater biomechanical forces would result in the presentation of more concussion-related symptoms that would take longer to resolve. The objective of this study was to investigate the relationship between an array of biomechanical parameters measured for concussive impacts and the presentation and resolution of concussion symptoms. A total of 319 collegiate football players from six universities were recruited to participate in this study. Certified athletic trainers and/or team physicians at each site diagnosed and treated concussions sustained by subjects through participation in football. The subjects' helmets were instrumented with accelerometer arrays that measured linear and rotational head accelerations for each impact experienced during games and practices. Correlations between biomechanical measurements associated with concussion symptom presentation and recovery were quantified. A total of 22 subjects collectively sustained 25 concussions, with three subjects sustaining two concussions each. Biomechanical measures associated with injury were not found to be correlated with number of symptoms, Sport Concussion Assessment Tool 3 Symptom Severity Score, or time to symptom resolution. Linear and rotational accelerations associated with injury were not correlated with symptom severity for any of the 22 individual symptoms evaluated. Further, we found no association between impact location and presence of any individual symptom when ignoring severity grade. While concussive impacts did not stand out relative to impacts that did not result in injury, concussive impacts were among the most severe for each individual player. This suggests tolerance to head acceleration might be individual-specific, meaning similar biomechanical inputs can produce different injury presentations between individuals. Future investigations should consider individual-specific analyses of tolerance to head acceleration and injury response.