Shared genetic risk between Alzheimer’s disease (AD) and concussion may help explain the association between concussion and elevated risk for dementia. However, there has been little investigation into whether AD risk genes also associate with concussion severity/recovery, and the limited findings are mixed. We used AD polygenic risk scores (PRS) and APOE genotypes to investigate associations between AD genetic risk and concussion severity/recovery in the NCAA-DoD Grand Alliance CARE Consortium (CARE) dataset. There were 1,917 injuries in the dataset upon project initiation. After removing repeated injuries, related participants, and those without genetic/outcome data, we had 931 participants. Outcomes were number of days to return to play (RTP) as a recovery measure, and four severity measures (scores on SAC and BESS, SCAT symptom severity and total number of symptoms). We calculated PRS using a published score (de Rojas et al., 2021) and performed a linear regression (MLR) of RTP by PRS in normal (<24 days) and long (>24 days) RTP subgroups. We then compared severity measures by PRS using MLR. Next, we used t-tests to examine outcomes by APOE genotype in military and civilian subgroups. We also performed chi-squared tests of RTP category (normal vs. long) by APOE genotype. Finally, we analyzed outcomes by PRS in European or African genetic ancestry subgroups using MLR. Higher PRS was associated with longer injury to RTP interval in the normal RTP (<24 days) subgroup (estimate = 0.0412, SE = 0.182, p = 0.0237). 1 SD increase in PRS resulted in a 0.412 day (9.89 hours) increase to the interval. This may be clinically meaningful in the collegiate athlete environment. We did not identify any other significant differences. Our preliminary results provide limited evidence for an impact of AD PRS on concussion recovery, though the pattern was inconsistent and its clinical significance is uncertain. Future studies should attempt to replicate these findings in larger samples with longer follow-up using PRS calculated from multiple/diverse populations, which will be especially relevant for diverse datasets like CARE.

Background: Individuals with ADHD may perform poorly on tasks targeting executive functioning skills such as the ImPACT, which requires the test-taker to employ judgement in non-routine situations Objective: To determine whether ADHD serves as a mediating variable for increasing the likelihood of an invalid score. Materials and Methods: A total of 39,140 collegiate athletes and United States military cadets consented to the Concussion Assessment, Research, and Education (CARE) Consortium study. Participants completed the CARE Baseline Packet which included various sections through which study participants provide self-report data, including demographic, personal, and family history sections. The personal history portion of the CARE Baseline Packet addressed the participant’s neurological history, including self-reported diagnosis of ADHD and history of traumatic brain injury. Variables utilized for the current study included age, gender, race, ethnicity, the participant’s primary college sport, use of mouthguards for athletes competing in sports requiring them, and the presence of an ADHD diagnosis. Participants responded to a question, inquiring if they had ever been diagnosed by a medical professional with ADHD, ultimately producing a dichotomous yes/no response. Results: We found that participants with ADHD were more likely to produce invalid baseline scores (ß = −0.884; p < 0.001). Similar results were found when controlling for sex, race, age, sport played, mouthguard use, and number of previous concussions (ß = −0.786; p < 0.001). Sex, race, sport played, and mouthguard use each played a significant role in determining profile validity, independent of ADHD diagnosis. With ADHD removed from the model, age negatively affected the likelihood of a valid score (ß = −0.052; p = 0.048). Conclusions: Our study suggests that the relationship between age and ImPACT validity is explained by the presence of ADHD. Results support adjusting ImPACT’s validity thresholds for individuals with ADHD.

PurposeFollowing sport-related concussions, early head impact exposure and premature return to sport are known to increase the risk of repeat concussion in football athletes, yet athletes' true post-injury head impact exposure profiles (i.e., characteristics of recorded head impacts over a given time period) and biomechanical progression have not been explored. Accordingly, this study explored how head impact exposure in American college football athletes was altered during their return to sport from concussion, particularly within the same athletic season.MethodsThis analysis compared daily volume of head impacts following concussion with pre-injury levels using head impact exposure profiles of 52 concussed collegiate football athletes from six NCAA Division I programs, and further compared these athletes to team- and position-matched controls to minimize season- or team-related factors. In addition, this study provided an analysis of the possible association between duration of recovery and change in head impact exposure following concussion using continuous linear regression.ResultsWhen comparing to pre-injury levels, 75% of concussed athletes reduced their head impact exposure in their immediate return to sport, whereas over 40% of concussed athletes did not reach their pre-injury level of head impact exposure at any point during the remainder of the concussion season segment. Furthermore, concussed athletes significantly decreased their head impact exposure over their immediate return-to-sport period when compared with team- and position-matched healthy, nonconcussed athletes over the same time period. Finally, longer postconcussion recovery times were associated with larger decreases in head impact exposure after return to sport.ConclusionsThis study provides evidence for a shift in head impact exposure after returning from concussion, seen most strongly in the immediate days after return to sport. These findings align with the recent shift toward more conservative postconcussion management seen across multiple sports and playing levels.

Background and objectives: After a concussion diagnosis, the most important issue for patients and loved ones is how long it will take them to recover. The main objective of this study is to develop a prognostic model of concussion recovery. This model would benefit many patients worldwide, allowing for early treatment intervention. Methods: The Concussion Assessment, Research and Education (CARE) consortium study enrolled collegiate athletes from 30 sites (NCAA athletic departments and US Department of Defense service academies), 4 of which participated in the Advanced Research Core, which included diffusion-weighted MRI (dMRI) data collection. We analyzed the dMRI data of 51 injuries of concussed athletes scanned within 48 h of injury. All athletes were cleared to return-to-play by the local medical staff following a standardized, graduated protocol. The primary outcome measure is days to clearance of unrestricted return-to-play. Injuries were divided into early (return-to-play < 28 days) and late (return-to-play >= 28 days) recovery based on the return-to-play clinical records. The late recovery group meets the standard definition of Persisting Post-Concussion Symptoms (PPCS). Data were processed using automated, state-of-the-art, rigorous methods for reproducible data processing using brainlife.io. All processed data derivatives are made available at https://brainlife.io/project/63b2ecb0daffe2c2407ee3c5/dat aset. The microstructural properties of 47 major white matter tracts, 5 callosal, 15 subcortical, and 148 cortical structures were mapped. Fractional Anisotropy (FA) and Mean Diffusivity (MD) were estimated for each tract and structure. Correlation analysis and Receiver Operator Characteristic (ROC) analysis were then performed to assess the association between the microstructural properties and return-to-play. Finally, a Logistic Regression binary classifier (LR-BC) was used to classify the injuries between the two recovery groups. Results: The mean FA across all white matter volume was negatively correlated with return-to-play (r = -0.38, p = 0.00001). No significant association between mean MD and return-to-play was found, neither for FA nor MD for any other structure. The mean FA of 47 white matter tracts was negatively correlated with return-to-play (r mu = -0.27; r sigma = 0.08; r(min) = -0.1; r(max)= -0.43). Across all tracts, a large mean ROC Area Under the Curve (AUC(FA)) of 0.71 +/- 0.09 SD was found. The top classification performance of the LR-BC was AUC = 0.90 obtained using the 16 statistically significant white matter tracts. Discussion: Utilizing a free, open-source, and automated cloud-based neuroimaging pipeline and app (https://bra inlife.io/docs/tutorial/using-clairvoy/), a prognostic model has been developed, which predicts athletes at risk for slow recovery (PPCS) with an AUC=0.90, balanced accuracy = 0.89, sensitivity = 1.0, and specificity = 0.79. The small number of participants in this study (51 injuries) is a significant limitation and supports the need for future large concussion dMRI studies and focused on recovery.

Sporting helmets contain force attenuating materials which reduce traumatic head injury risk and may influence sport-related concussion (SRC) sequelae. The purpose of this study was to examine the association of sport helmet status with SRC-clinical presentation and recovery trajectories in men's collegiate athletes. Sport helmet status was based on the nature of sports being either helmeted/non-helmeted. 1070 SRCs in helmeted (HELM) sports (Men's-Football, Ice Hockey, and Lacrosse), and 399 SRCs in non-helmeted (NOHELM) sports (Men's-Basketball, Cheerleading, Cross Country/Track & Field, Diving, Gymnastics, Soccer, Swimming, Tennis, and Volleyball) were analyzed. Multivariable negative binomial regression models analyzed associations between sport helmet status and post-injury cognition, balance, and symptom severity, adjusting for covariate effects (SRC history, loss of consciousness, anterograde/retrograde amnesia, event type). Kaplan-Meier curves evaluated median days to: initiation of return to play (iRTP) protocol, and unrestricted RTP (URTP) by sport helmet status. Log-rank tests were used to evaluate differential iRTP/URTP between groups. Two independent multivariable Weibull accelerated failure time models were used to examine differential iRTP and URTP between groups, after adjusting for aforementioned covariates and symptom severity score. Overall, the median days to iRTP and URTP was 6.3 and 12.0, respectively, and was comparable across NOHELM- and HELM-SRCs. Post-injury symptom severity was lower (Score Ratio 0.90, 95%CI 0.82, 0.98), and cognitive test performance was higher (Score Ratio 1.03, 95%CI 1.02, 1.05) in NOHELM-compared to HELM-SRCs. Estimated time spent recovering to iRTP/URTP was comparable between sport helmet status groups. Findings suggest that the grouping of sports into helmeted and non-helmeted show slight differences in clinical presentation but not recovery.

Objective To test whether higher head injury biomechanics are associated with symptom resolution time (SRT) and return-to-participation time (RTP). Design Retrospective cohort study. Setting Six United States NCAA Division 1 colleges. Participants We studied 51 college American football players who sustained an incident concussion while participating in a multi-site study. There were no exclusion criteria based on age, sex, or race. Interventions (or Assessment of Risk Factors) Head injury linear accelerations were categorized as mild (<66g), moderate (66g-106g), or severe (>106g). Head impact locations, event type, and player race/ethnicity were included as model covariates. Outcome Measures SRT and RTP were measured in days. Kruskal-Wallis tests examined SRT and RTP differences by head impact severity. Multivariable negative binomial regression models analyzed associations between higher head impact severity and SRT and RTP. Effect estimates (ratios) with 95% confidence intervals (CI) excluding 1.00 were considered significant. Main Results Median linear acceleration was 66.7g, with 9 cases (17.7%) resulting from a severe (>106g) linear acceleration. Median SRT and RTP were 6.1 days (IQR=5.8) and 12.3 days (IQR=7.8), respectively. No SRT (χ2=1.9; p=0.38) or RTP (χ2=0.38; p=0.83) differences were observed across impact severities. Multivariable models revealed no associations between higher head impact severity and SRT (Ratio=0.96; 95%CI=[0.71,1.30]) or RTP (Ratio=0.91; 95%CI=[0.62,1.34]), after adjusting for covariate effects. Conclusions Head injury biomechanics do not predict injury recovery. Future work should consider the role pre-injury repeated head impact exposure has on predicting SRT and RTP time given injury head impacts alone are not associated with SRT or RTP.

Background:Current protein biomarkers are only moderately predictive at identifying individuals with mild traumatic brain injury or concussion.Therefore,more accurate diagnostic markers are needed for sport-related concussion.Methods:This was a multicenter,prospective,case-control study of athletes who provided blood samples and were diagnosed with a concussion or were a matched non-concussed control within the National Collegiate Athletic Association-Department of Defense Concussion Assessment,Research,and Education Consortium conducted between 2015 and 2019.The blood was collected within 48 h of injury to identify protein abnormalities at the acute and subacute timepoints.Athletes with concussion were divided into 6 h post-injury（0-6 h post-injury） and after 6 h postinjury（7-48 h post-injury） groups.We applied a highly multiplexed proteomic technique that used a DNA aptamers assay to target 1305proteins in plasma samples from athletes with and without sport-related concussion.Results:A total of 140 athletes with concussion（79.3% males;aged 18.71±1.10 years,mean±SD） and 21 non-concussed athletes（76.2%males;19.14±1.10 years） were included in this study.We identified 338 plasma proteins that significantly differed in abundance（319 upregulated and 19 downregulated） in concussed athletes compared to non-concussed athletes.The top 20 most differentially abundant proteins discriminated concussed athletes from non-concussed athletes with an area under the curve（AUC） of 0.954（95% confidence interval:0.922-0.986）.Specifically,after 6 h of injury,the individual AUC of plasma erythrocyte membrane protein band 4.1（EPB41） and alpha-synuclein（SNCA） were 0.956 and 0.875,respectively.The combination of EPB41 and SNCA provided the best AUC（1.000）,which suggests this combination of candidate plasma biomarkers is the best for diagnosing concussion in athletes after 6 h of injury.Conclusion:Our data suggest that proteomic profiling may provide novel diagnostic protein markers and that a combination of EPB41 and SNCA is the most predictive biomarker of concussion after 6 h of injury.

ObjectiveThe aim of this study was to investigate phosphorylated tau (p-tau181) protein in plasma in a cohort of mild traumatic brain injury (mTBI) patients and a cohort of concussed athletes.MethodsThis pilot study comprised two independent cohorts. The first cohort—part of a Traumatic Head Injury Neuroimaging Classification (THINC) study—with a mean age of 46 years was composed of uninjured controls (UIC, n = 30) and mTBI patients (n = 288) recruited from the emergency department with clinical computed tomography (CT) and research magnetic resonance imaging (MRI) findings. The second cohort—with a mean age of 19 years—comprised 133 collegiate athletes with (n = 112) and without (n = 21) concussions. The participants enrolled in the second cohort were a part of a multicenter, prospective, case-control study conducted by the NCAA-DoD Concussion Assessment, Research and Education (CARE) Consortium at six CARE Advanced Research Core (ARC) sites between 2015 and 2019. Blood was collected within 48 h of injury for both cohorts. Plasma concentration (pg/ml) of p-tau181 was measured using the Single Molecule Array ultrasensitive assay.ResultsConcentrations of plasma p-tau181 in both cohorts were significantly elevated compared to controls within 48 h of injury, with the highest concentrations of p-tau181 within 18 h of injury, with an area under the curve (AUC) of 0.690–0.748, respectively, in distinguishing mTBI patients and concussed athletes from controls. Among the mTBI patients, the levels of plasma p-tau181 were significantly higher in patients with positive neuroimaging (either CT+/MRI+, n = 74 or CT−/MRI+, n = 89) compared to mTBI patients with negative neuroimaging (CT−/MRI−, n = 111) findings and UIC (P-values < 0.05).ConclusionThese findings indicate that plasma p-tau181 concentrations likely relate to brain injury, with the highest levels in patients with neuroimaging evidence of injury. Future research is needed to replicate and validate this protein assay's performance as a possible early diagnostic biomarker for mTBI/concussions.

Background Molecular-based approaches to understanding concussion pathophysiology provide complex biological information that can advance concussion research and identify potential diagnostic and/or prognostic biomarkers of injury. Objective The aim of this study was to identify gene expression changes in peripheral blood that are initiated following concussion and are relevant to concussion response and recovery. Methods We analyzed whole blood transcriptomes in a large cohort of concussed and control collegiate athletes who were participating in the multicenter prospective cohort Concussion Assessment, Research, and Education (CARE) Consortium study. Blood samples were collected from collegiate athletes at preseason (baseline), within 6 h of concussion injury, and at four additional prescribed time points spanning 24 h to 6 months post-injury. RNA sequencing was performed on samples from 230 concussed, 130 contact control, and 102 non-contact control athletes. Differential gene expression and deconvolution analysis were performed at each time point relative to baseline. Results Cytokine and immune response signaling pathways were activated immediately after concussion, but at later time points these pathways appeared to be suppressed relative to the contact control group. We also found that the proportion of neutrophils increased and natural killer cells decreased in the blood following concussion. Conclusions Transcriptome signatures in the blood reflect the known pathophysiology of concussion and may be useful for defining the immediate biological response and the time course for recovery. In addition, the identified immune response pathways and changes in immune cell type proportions following a concussion may inform future treatment strategies.

Weight and age interact to modify cognitive effects of head acceleration events after two seasons of youth football Abstract This is a follow-up study of youth American football players in a second season of play. Season-one findings identified a relationship between a head acceleration measure (HITsp) and cognitive score changes with weight modifying the effect in 9 to 10 year-olds. Sixty-eight youth completed a second season of play wearing helmet-mounted sensors and were assessed with neuropsychological tests pre- and post-season. Regression analysis of the full sample demonstrated a small but significant negative effect of HAE on cognition as indexed by test score changes: R2 = .06, F = 4.06, p = .024. Outcome differences between those who started playing at ages nine to 10, compared to those who started between 11 and 13 were identified: t(66) = -3.39, p<.01, d = -.84, 95th CI -2.77 to -.72. Regression models including players’ weights found that the relationship of weight to outcome was different by group: greater negative cognitive effects were found in younger-heavier players (R2 = 0.21, F =3.21, p = 0.03) and older-lighter players (R2 = 0.18, F =4.26, p <.001). These findings confirmed a negative relationship of HAE and cognitive change and point to player weight as an important developmental factor to consider in understanding concussion biomechanics.

PURPOSE:Contact sport athletes are exposed to a unique environment where they sustain repeated head impacts throughout the season and can sustain hundreds of head impacts over a few months. Accordingly, recent studies outlined the role that head impact exposure (HIE) has in concussion biomechanics and in the development of cognitive and brain-based changes. Those studies focused on time-bound effects by quantifying exposure leading up to the concussion, or cognitive changes after a season in which athletes had high HIE. However, HIE may have a more prolonged effect. This study identified associations between HIE and concussion incidence during different periods of the college football fall season. METHODS:This study included 1120 athlete seasons from six National Collegiate Athletic Association Division I football programs across 5 yr. Athletes were instrumented with the Head Impact Telemetry System to record daily HIE. The analysis quantified associations of preseason/regular season/total season concussion incidence with HIE during those periods. RESULTS:Strong associations were identified between HIE and concussion incidence during different periods of the season. Preseason HIE was associated with preseason and total season concussion incidence, and total season HIE was associated with total season concussion incidence. CONCLUSIONS:These findings demonstrate a prolonged effect of HIE on concussion risk, wherein elevated preseason HIE was associated with higher concussion risk both during the preseason and throughout the entire fall season. This investigation is the first to provide evidence supporting the hypothesis of a relationship between elevated HIE during the college football preseason and a sustained decreased tolerance for concussion throughout that season.

The relationship between head impact and subsequent brain injury for American football players is not well-defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multi-season study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9-14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43 and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95th percentile peak linear acceleration (PLA, g) competition: 45.6 vs 61.9; 95th percentile PLA practice: 42.6 vs 58.8; 95th percentile peak rotational acceleration (PRA, rad·s-2) competition: 2262 vs 4422; 95th percentile PRA practice: 2081 vs 4052; 95th percentile HITsp competition: 25.4 vs 32.8; 95th percentile HITsp practice: 23.9 vs 30.2). Impacts during competition were more frequent and of greater magnitude than during practice at both levels. Quantified comparisons of head impact frequency and magnitude between youth and collegiate athletes reveal HIE differences as a function of age, and expanded insight better informs the development of age-appropriate guidelines for helmet design, prevention measures, standardized testing, brain injury diagnosis, and recovery management.

More than six million people participate in whitewater kayaking and rafting in the United States each year. Unfortunately, with these six million whitewater participants come 50 deaths annually, making it one of the highest fatality rates of all sports. As the popularity in whitewater activities grows, the number of injuries, including concussions, also increases. The objective of this study was to create a new rating system for whitewater helmets by evaluating the biomechanical performance and risk of head injury of whitewater helmets using the Summation of Tests for the Analysis of Risk (STAR) system. All watersport helmets that passed the EN: 1385: 2012 standard and that were clearly marketed for whitewater use were selected for this study. Two samples of each helmet model were tested on a custom pendulum impactor under conditions known to be associated with the highest risk of head injury and death. A 50th percentile male NOCSAE headform instrumented with three linear accelerometers and a triaxial angular rate sensor coupled with a Hybrid III 50th percentile neck were used for data collection. A total of 126 tests were performed using six different configurations. These included impacts to the front, side, and rear using two speeds of 3.1 and 4.9 m/s that modeled whitewater river flow rates. Each helmet's STAR score was calculated using the combination of exposure and injury risk that was determined from the linear and rotational head accelerations. The resulting head impact accelerations predicted a very high risk of concussion for all impact locations at the 4.9 m/s speed. The STAR score varied between helmets indicating that some helmets provide better protection than others. Overall, these results show a clear need for improvement in whitewater helmets, and the methodologies developed in this research project should provide manufacturers a design tool for improving these products.

Despite advances in the understanding of human tolerances to brain injury, injury metrics used in automotive safety and protective equipment standards have changed little since they were first implemented nearly a half-century ago. Although numerous metrics have been proposed as improvements over the ones currently used, evaluating the predictive capability of these metrics is challenging. The purpose of this review is to summarize existing head injury metrics that have been proposed for both severe head injuries, such as skull fractures and traumatic brain injuries (TBI), and mild traumatic brain injuries (mTBI) including concussions. Metrics have been developed based on head kinematics or intracranial parameters such as brain tissue stress and strain. Kinematic metrics are either based on translational motion, rotational motion, or a combination of the two. Tissue-based metrics are based on finite element model simulations or in vitro experiments. This review concludes with a discussion of the limitations of current metrics and how improvements can be made in the future.

ObjectiveTo investigate the plasma proteomic profiling in identifying biomarkers related to return to sport (RTS) following a sport-related concussion (SRC).MethodsThis multicenter, prospective, case-control study was part of a larger cohort study conducted by the NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium, athletes (n = 140) with blood collected within 48 h of injury and reported day to asymptomatic were included in this study, divided into two groups: (1) recovery <14-days (n = 99) and (2) recovery ≥14-days (n = 41). We applied a highly multiplexed proteomic technique that uses DNA aptamers assay to target 1,305 proteins in plasma samples from concussed athletes with <14-days and ≥14-days.ResultsWe identified 87 plasma proteins significantly dysregulated (32 upregulated and 55 downregulated) in concussed athletes with recovery ≥14-days relative to recovery <14-days groups. The significantly dysregulated proteins were uploaded to Ingenuity Pathway Analysis (IPA) software for analysis. Pathway analysis showed that significantly dysregulated proteins were associated with STAT3 pathway, regulation of the epithelial mesenchymal transition by growth factors pathway, and acute phase response signaling.ConclusionOur data showed the feasibility of large-scale plasma proteomic profiling in concussed athletes with a <14-days and ≥ 14-days recovery. These findings provide a possible understanding of the pathophysiological mechanism in neurobiological recovery. Further study is required to determine whether these proteins can aid clinicians in RTS decisions.

Sport-related concussion (SRC) is an important public health issue. White-matter alterations after SRC are widely studied by neuroimaging approaches, such as diffusion magnetic resonance imaging (MRI). Although the exact anatomical location of the alterations may differ, significant white-matter alterations are commonly observed in long fiber tracts, but are never proven. In the present study, we performed streamline tractography to characterize the association between tract length and white-matter microstructural alterations after SRC. Sixty-eight collegiate athletes diagnosed with acute concussion (24-48 h post-injury) and 64 matched contact-sport controls were included in this study. The athletes underwent diffusion tensor imaging (DTI) in 3.0 T MRI scanners across three study sites. DTI metrics were used for tract-based spatial statistics to map white-matter regions-of-interest (ROIs) with significant group differences. Whole-brain white-mater streamline tractography was performed to extract "affected" white-matter streamlines (i.e., streamlines passing through the identified ROIs). In the concussed athletes, streamline counts and DTI metrics of the affected white-matter fiber tracts were summarized and compared with unaffected white-matter tracts across tract length in the same participant. The affected white-matter tracts had a high streamline count at length of 80-100 mm and high length-adjusted affected ratio for streamline length longer than 80 mm. DTI mean diffusivity was higher in the affected streamlines longer than 100 mm with significant associations with the Brief Symptom Inventory score. Our findings suggest that long fibers in the brains of collegiate athletes are more vulnerable to acute SRC with higher mean diffusivity and a higher affected ratio compared with the whole distribution.

Sport-related concussions can result from a single high magnitude impact that generates concussive symptoms, repeated subconcussive head impacts aggregating to generate concussive symptoms, or a combined effect from the two mechanisms. The array of symptoms produced by these mechanisms may be clinically interpreted as a sport-related concussion. It was hypothesized that head impact exposure resulting in concussion is influenced by severity, total number, and frequency of subconcussive head impacts. The influence of total number and magnitude of impacts was previously explored, but frequency was investigated to a lesser degree. In this analysis, head impact frequency was investigated over a new metric called ‘time delta’, the time difference from the first recorded head impact of the day until the concussive impact. Four exposure metrics were analyzed over the time delta to determine whether frequency of head impact exposure was greater for athletes on their concussion date relative to other dates of contact participation. Those metrics included head impact frequency, head impact accrual rate, risk weighted exposure (RWE), and RWE accrual rate. Athletes experienced an elevated median number of impacts, RWE, and RWE accrual rate over the time delta on their concussion date compared to non-injury sessions. This finding suggests elevated frequency of head impact exposure on the concussion date compared to other dates that may precipitate the onset of concussion.

Author(s): Duma, Stefan M; Rowson, Bethany; King, Michael R; Efimov, Igor; Saterbak, Ann; Chesler, Naomi C