The Influence of Headform Friction and Inertial Properties on Oblique Impact Helmet Testing.

Helmet-testing headforms replicate the human head impact response, allowing the assessment of helmet protection and injury risk. However, the industry uses three different headforms with varying inertial and friction properties making study comparisons difficult because these headforms have different inertial and friction properties that may affect their impact response. This study aimed to quantify the influence of headform coefficient of friction (COF) and inertial properties on oblique impact response. The static COF of each headform condition (EN960, Hybrid III, NOCSAE, Hybrid III with a skull cap, NOCSAE with a skull cap) was measured against the helmet lining material used in a KASK prototype helmet. Each headform condition was tested with the same helmet model at two speeds (4.8 & 7.3 m/s) and two primary orientations (y-axis and x-axis rotation) with 5 repetitions, totaling 100 tests. The influence of impact location, inertial properties, and friction on linear and rotational impact kinematics was investigated using a MANOVA, and type II sums of squares were used to determine how much variance in dependent variables friction and inertia accounted for. Our results show significant differences in impact response between headforms, with rotational head kinematics being more sensitive to differences in inertial rather than frictional properties. However, at high-speed impacts, linear head kinematics are more affected by changes in frictional properties rather than inertial properties. Helmet testing protocols should consider differences between headforms' inertial and frictional properties during interpretation. These results provide a framework for cross-comparative analysis between studies that use different headforms and headform modifiers.

Head Exposure to Acceleration Database in Sport (HEADSport): a kinematic signal processing method to enable instrumented mouthguard (iMG) field-based inter-study comparisons.

Objective: Instrumented mouthguard (iMG) systems use different signal processing approaches limiting field-based inter-study comparisons, especially when artefacts are present in the signal. The objective of this study was to assess the frequency content and characteristics of head kinematic signals from head impact reconstruction laboratory and field-based environments to develop an artefact attenuation filtering method (HEADSport filter method). Methods: Laboratory impacts (n=72) on a test-dummy headform ranging from 25 to 150 g were conducted and 126 rugby union players were equipped with iMGs for 209 player-matches. Power spectral density (PSD) characteristics of the laboratory impacts and on-field head acceleration events (HAEs) (n=5694) such as the 95th percentile cumulative sum PSD frequency were used to develop the HEADSport method. The HEADSport filter method was compared with two other common filtering approaches (Butterworth-200Hz and CFC180 filter) through signal-to-noise ratio (SNR) and mixed linear effects models for laboratory and on-field events, respectively. Results: The HEADSport filter method produced marginally higher SNR than the Butterworth-200Hz and CFC180 filter and on-field peak linear acceleration (PLA) and peak angular acceleration (PAA) values within the magnitude range tested in the laboratory. Median PLA and PAA (and outlier values) were higher for the CFC180 filter than the Butterworth-200Hz and HEADSport filter method (p<0.01). Conclusion: The HEADSport filter method could enable iMG field-based inter-study comparisons and is openly available at https://github.com/GTBiomech/HEADSport-Filter-Method.

Gene Expression Alterations in Peripheral Blood Following Sport-Related Concussion in a Prospective Cohort of Collegiate Athletes: A Concussion Assessment, Research and Education (CARE) Consortium Study.

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.

Plasma phosphorylated tau181 as a biomarker of mild traumatic brain injury: findings from THINC and NCAA-DoD CARE Consortium prospective cohorts.

Objective: The 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. Methods: This 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. Results: Concentrations 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). Conclusion: These 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.

Are EPB41 and alpha-synuclein diagnostic biomarkers of sport-related concussion? Findings from the NCAA and Department of Defense CARE Consortium.

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 post-injury (7-48 h post-injury) groups. We applied a highly multiplexed proteomic technique that used a DNA aptamers assay to target 1305 proteins 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.

Proteomic Profiling of Plasma Biomarkers Associated With Return to Sport Following Concussion: Findings From the NCAA and Department of Defense CARE Consortium.

Objective: To investigate the plasma proteomic profiling in identifying biomarkers related to return to sport (RTS) following a sport-related concussion (SRC). Methods: This 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. Results: We 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. Conclusion: Our 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.

Time Delta Head Impact Frequency: An Analysis on Head Impact Exposure in the Lead Up to a Concussion: Findings from the NCAA-DOD Care Consortium.

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.

American Football Helmet Effectiveness Against a Strain-Based Concussion Mechanism.

Brain strain is increasingly being used in helmet design and safety performance evaluation as it is generally considered as the primary mechanism of concussion. In this study, we investigate whether different helmet designs can meaningfully alter brain strains using two commonly used metrics, peak maximum principal strain (MPS) of the whole brain and cumulative strain damage measure (CSDM). A convolutional neural network (CNN) that instantly produces detailed brain strains is first tested for accuracy for helmeted head impacts. Based on N = 144 impacts in 12 impact conditions from three random and representative helmet models, we conclude that the CNN is sufficiently accurate for helmet testing applications, for elementwise MPS (success rate of 98.6%), whole-brain peak MPS and CSDM (coefficient of determination of 0.977 and 0.980, with root mean squared error of 0.015 and 0.029, respectively). We then apply the technique to 23 football helmet models (N = 1104 impacts) to reproduce elementwise MPS. Assuming a concussion would occur when peak MPS or CSDM exceeds a threshold, we sweep their thresholds across the value ranges to evaluate the number of predicted hypothetical concussions that different helmets sustain across the impact conditions. Relative to the 12 impact conditions tested, we find that the "best" and "worst" helmets differ by an average of 22.5% in terms of predicted concussions, ranging from 0 to 42% (the latter achieved at the threshold value of 0.28 for peak MPS and 0.4 for CSDM, respectively). Such a large variation among helmets in strain-based concussion predictions demonstrate that helmet designs can still be optimized in a clinically meaningful way. The robustness and accuracy of the CNN tool also suggest its potential for routine use for helmet design and safety performance evaluation in the future. The CNN is freely available online at https://github.com/Jilab-biomechanics/CNN-brain-strains .

Ready for impact? A validity and feasibility study of instrumented mouthguards (iMGs).

OBJECTIVES: Assess the validity and feasibility of current instrumented mouthguards (iMGs) and associated systems. METHODS: Phase I; four iMG systems (Biocore-Football Research Inc (FRI), HitIQ, ORB, Prevent) were compared against dummy headform laboratory criterion standards (25, 50, 75, 100 g). Phase II; four iMG systems were evaluated for on-field validity of iMG-triggered events against video-verification to determine true-positives, false-positives and false-negatives (20±9 player matches per iMG). Phase III; four iMG systems were evaluated by 18 rugby players, for perceptions of fit, comfort and function. Phase IV; three iMG systems (Biocore-FRI, HitIQ, Prevent) were evaluated for practical feasibility (System Usability Scale (SUS)) by four practitioners. RESULTS: Phase I; total concordance correlation coefficients were 0.986, 0.965, 0.525 and 0.984 for Biocore-FRI, HitIQ, ORB and Prevent. Phase II; different on-field kinematics were observed between iMGs. Positive predictive values were 0.98, 0.90, 0.53 and 0.94 for Biocore-FRI, HitIQ, ORB and Prevent. Sensitivity values were 0.51, 0.40, 0.71 and 0.75 for Biocore-FRI, HitIQ, ORB and Prevent. Phase III; player perceptions of fit, comfort and function were 77%, 6/10, 55% for Biocore-FRI, 88%, 8/10, 61% for HitIQ, 65%, 5/10, 43% for ORB and 85%, 8/10, 67% for Prevent. Phase IV; SUS (preparation-management) was 51.3-50.6/100, 71.3-78.8/100 and 83.8-80.0/100 for Biocore-FRI, HitIQ and Prevent. CONCLUSION: This study shows differences between current iMG systems exist. Sporting organisations can use these findings when evaluating which iMG system is most appropriate to monitor head acceleration events in athletes, supporting player welfare initiatives related to concussion and head acceleration exposure.

Head Impact Exposure in Youth and Collegiate American Football.

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.

Dual-Task Gait Performance Following Head Impact Exposure in Male and Female Collegiate Rugby Players.

Background: Gait impairments have been well-studied in concussed athletes. However, the sex-specific effect of cumulative head impacts on gait is not well understood. When a cognitive task is added to a walking task, dual-task gait assessments can help amplify deficits in gait and are representative of tasks in everyday life. Dual-task cost is the difference in performance from walking (single-task) to walking with a cognitive load (dual-task). Purpose: The objectives of this study were to explore the differences between sexes in 1) dual-task gait metrics, 2) gait metric changes from pre-season to post-concussion and post-season, and 3) the dual-task costs associated with gait metrics. Study Design: Cross-sectional study. Methods: Over two seasons, 77 female athlete-seasons and 64 male athlete-seasons from collegiate club rugby teams participated in this study. Subjects wore inertial sensors and completed walking trials with and without a cognitive test at pre-season, post-season, and post-concussion (if applicable). Results: Females athletes showed improvement in cadence (mean = 2.7 step/min increase), double support time (mean = -0.8% gait cycle time decrease), gait speed (mean = 0.1 m/s increase), and stride length (mean = 0.2 m increase) in both task conditions over the course of the season (p < 0.030). Male athletes showed no differences in gait metrics over the course of the season, except for faster gait speeds and longer stride lengths in the dual-task condition (p < 0.034). In all four gait characteristics, at baseline and post-season, females had higher dual-task costs (mean difference = 4.4, p < 0.003) than the males. Conclusions: This results of this study showed little evidence suggesting a relationship between repetitive head impact exposure and gait deficits. However, there are sex-specific differences that should be considered during the diagnosis and management of sports-related concussion. Level of Evidence: Level 2b.

Association between Preseason/Regular Season Head Impact Exposure and Concussion Incidence in NCAA Football.

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.

In-Season Concussion Symptom Reporting in Male and Female Collegiate Rugby Athletes.

Symptom inventories are generally only collected after a suspected concussion, but regular in-season monitoring may allude to clinical symptoms associated with repetitive subconcussive impacts and potential undiagnosed concussions. Despite sex-specific differences in symptom presentation and outcome of concussion, no return-to-play protocol takes sex into account. The objective of this study was to monitor a cohort of contact-sport athletes and compare the frequency and severity of in-season concussion-like symptom reporting between sexes. Graded symptom checklists from 144 female and 104 male athlete-seasons were administered weekly to quantify the effect of subconcussive impacts on frequency and severity of in-season symptom reporting. In-season, mean symptom severity score (SSS) (p = 0.026, mean difference of 1.8), mean number of symptoms (p = 0.044, mean difference of 0.9), max SSS (p < 0.001, mean difference of 19.2), and max number of symptoms (p < 0.001, mean difference of 6.8) were higher in the females. The females' survey results showed differences between elevated and concussed SSS (p < 0.005, mean difference of 28.1) and number of symptoms reported (p = 0.001, mean difference of 6.6). The males did not have a difference in SSS (p = 0.97, mean difference of 1.12) nor in number of symptoms (p = 0.35, mean difference of 1.96) from elevated to concussed athletes. Rugby players report concussion-like symptoms in the absence of a diagnosed concussion in-season. Female athletes reported elevated symptom frequencies with greater severities than the males, but both sexes reported considerable levels throughout the season.

Relating on-field youth football head impacts to pneumatic ram laboratory testing procedures.

A youth-specific football helmet testing standard has been proposed to address the physical and biomechanical differences between adult and youth football players. This study sought to relate the proposed youth standard-defined laboratory impacts to on-field head impacts collected from youth football players. Head impact data from 112 youth football players (ages 9-14) were collected through the use of helmet-mounted accelerometer arrays. These head impacts were filtered to only include those that resided in corridors near prescribed National Operating Committee on Standards for Athletic Equipment (NOCSAE) impact locations. Peak linear head acceleration and peak rotational head acceleration magnitudes collected from pneumatic ram impactor tests as specified by the proposed NOCSAE youth standard were compared to the distribution of on-field head impacts. All laboratory impact tests were among the top 10% in terms of magnitude for Severity Index and peak rotational acceleration of matched location head impacts experienced by youth football players. As concussive head impacts are among the most severe impacts experienced on the field, a safety standard geared toward mitigating concussion should assess the most severe on-field head impacts. This proposed testing standard may be refined as more becomes known regarding the biomechanics of concussion among youth athletes.

Laboratory Reconstructions of Real-world Bicycle Helmet Impacts.

The best way to prevent severe head injury when cycling is to wear a bike helmet. To reduce the rate of head injury in cycling, knowing the nature of real-world head impacts is crucial. Reverse engineering real-world bike helmet impacts in a laboratory setting is an alternative to measuring head impacts directly. This study aims to quantify bike helmet damage using computed tomography (CT) and reconstruct real-world damage with a custom, oblique test rig to recreate real-world impacts. Damaged helmets were borrowed from a helmet manufacturer who runs a helmet warranty program. Each helmet was CT-scanned and the damage metrics were quantified. Helmets of the same model and size were used for in-lab reconstructions of the damaged helmets where normal velocity, tangential velocity, peak linear acceleration (PLA) and peak rotational velocity (PRV) could be measured. The damage metrics of the in-lab dropped helmets were quantified using the same CT scanning process. For each case, a multiple linear regression (MLR) equation was created to define a relationship between the quantified damage metrics of the in-lab tested helmets and the associated measured impact velocities and kinematics. These equations were used to predict the impact kinematics and velocities from the corresponding real-world damaged helmet based on the damage metrics from the original damaged helmet. Average normal velocity (3.5 m/s), tangential velocity (2.5 m/s), PLA (108.0 g), PRV (15.7 rad/s) were calculated based on a sample of 23 helmets. Within these head impact cases, five notes reported a concussion. The difference between the average PLA and PRV for concussive cases versus other impacts were not significantly different, although the average impact kinematics for the concussive cases (PLA = 111.4 g, PRV = 18.5 rad/s) were slightly higher than the remaining cases (PLA = 107.1 g, PRV = 15.0 rad/s). The concussive cases were not indicative of high magnitude impact kinematics.

A price-performance analysis of the protective capabilities of wholesale bicycle helmets.

OBJECTIVE: Although bicycle helmets are an effective countermeasure against head injury, many cyclists do not wear one. One avenue for facilitating widespread helmet use is through community-driven helmet safety initiatives, which often give away or subsidize wholesale helmet models that are manufactured at a low price point. However, the impact performance of such helmets during real-world accident conditions has yet to be explored. The present study seeks to investigate trends between wholesale bicycle helmet price and protective capabilities. METHODS: Nine common wholesale helmet models (price range $3.65-$12.95) were evaluated according to the bicycle Summation of Tests for the Analysis of Risk (STAR) methodology, which analyzes helmet performance in 24 oblique impact tests reflecting common cyclist head impact conditions. Resulting head peak linear acceleration (PLA) and peak rotational velocity (PRV) were collected and used to predict risk of concussion. Concussion risks were then combined using the STAR algorithm in order to summarize each model's risks into a single, weighted metric. RESULTS: Large ranges in kinematic results led to large variations in concussion risks between helmets, and in turn, large variations in STAR values (13.5-26.2). Wholesale helmet price was not significantly associated with STAR, although incorporating 30 previous bicycle helmet STAR results produced a weak negative correlation between price and STAR overall. Nonetheless, the best-performing wholesale helmet produced one of the lowest overall STAR values for a price of $6.45. Helmet style was instead a superior predictor of STAR, with multi-sport style helmets producing significantly higher linear accelerations and resulting STAR values than bike style helmets. CONCLUSIONS: These results show that the impact performance of wholesale helmets ranges considerably despite their low price-points. Results can also guide helmet safety promotion organizers toward distributing wholesale bicycle helmet models associated with lower overall concussion risks.

Assessment of Blood Biomarker Profile After Acute Concussion During Combative Training Among US Military Cadets: A Prospective Study From the NCAA and US Department of Defense CARE Consortium.

Importance: Validation of protein biomarkers for concussion diagnosis and management in military combative training is important, as these injuries occur outside of traditional health care settings and are generally difficult to diagnose. Objective: To investigate acute blood protein levels in military cadets after combative training-associated concussions. Design, Setting, and Participants: This multicenter prospective case-control study was part of a larger cohort study conducted by the National Collegiate Athletic Association and the US Department of Defense Concussion Assessment Research and Education (CARE) Consortium from February 20, 2015, to May 31, 2018. The study was performed among cadets from 2 CARE Consortium Advanced Research Core sites: the US Military Academy at West Point and the US Air Force Academy. Cadets who incurred concussions during combative training (concussion group) were compared with cadets who participated in the same combative training exercises but did not incur concussions (contact-control group). Clinical measures and blood sample collection occurred at baseline, the acute postinjury point (<6 hours), the 24- to 48-hour postinjury point, the asymptomatic postinjury point (defined as the point at which the cadet reported being asymptomatic and began the return-to-activity protocol), and 7 days after return to activity. Biomarker levels and estimated mean differences in biomarker levels were natural log (ln) transformed to decrease the skewness of their distributions. Data were collected from August 1, 2016, to May 31, 2018, and analyses were conducted from March 1, 2019, to January 14, 2020. Exposure: Concussion incurred during combative training. Main Outcomes and Measures: Proteins examined included glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, neurofilament light chain, and tau. Quantification was conducted using a multiplex assay (Simoa; Quanterix Corp). Clinical measures included the Sport Concussion Assessment Tool-Third Edition symptom severity evaluation, the Standardized Assessment of Concussion, the Balance Error Scoring System, and the 18-item Brief Symptom Inventory. Results: Among 103 military service academy cadets, 67 cadets incurred concussions during combative training, and 36 matched cadets who engaged in the same training exercises did not incur concussions. The mean (SD) age of cadets in the concussion group was 18.6 (1.3) years, and 40 cadets (59.7%) were male. The mean (SD) age of matched cadets in the contact-control group was 19.5 (1.3) years, and 25 cadets (69.4%) were male. Compared with cadets in the contact-control group, those in the concussion group had significant increases in glial fibrillary acidic protein (mean difference in ln values, 0.34; 95% CI, 0.18-0.50; P < .001) and ubiquitin C-terminal hydrolase-L1 (mean difference in ln values, 0.97; 95% CI, 0.44-1.50; P < .001) levels at the acute postinjury point. The glial fibrillary acidic protein level remained high in the concussion group compared with the contact-control group at the 24- to 48-hour postinjury point (mean difference in ln values, 0.22; 95% CI, 0.06-0.38; P = .007) and the asymptomatic postinjury point (mean difference in ln values, 0.21; 95% CI, 0.05-0.36; P = .01). The area under the curve for all biomarkers combined, which was used to differentiate cadets in the concussion and contact-control groups, was 0.80 (95% CI, 0.68-0.93; P < .001) at the acute postinjury point. Conclusions and Relevance: This study's findings indicate that blood biomarkers have potential for use as research tools to better understand the pathobiological changes associated with concussion and to assist with injury identification and recovery from combative training-associated concussions among military service academy cadets. These results extend the previous findings of studies of collegiate athletes with sport-associated concussions.

Opportunities for Prevention of Concussion and Repetitive Head Impact Exposure in College Football Players: A Concussion Assessment, Research, and Education (CARE) Consortium Study.

Importance: Concussion ranks among the most common injuries in football. Beyond the risks of concussion are growing concerns that repetitive head impact exposure (HIE) may increase risk for long-term neurologic health problems in football players. Objective: To investigate the pattern of concussion incidence and HIE across the football season in collegiate football players. Design, Setting, and Participants: In this observational cohort study conducted from 2015 to 2019 across 6 Division I National Collegiate Athletic Association (NCAA) football programs participating in the Concussion Assessment, Research, and Education (CARE) Consortium, a total of 658 collegiate football players were instrumented with the Head Impact Telemetry (HIT) System (46.5% of 1416 eligible football players enrolled in the CARE Advanced Research Core). Players were prioritized for instrumentation with the HIT System based on their level of participation (ie, starters prioritized over reserves). Exposure: Participation in collegiate football games and practices from 2015 to 2019. Main Outcomes and Measures: Incidence of diagnosed concussion and HIE from the HIT System. Results: Across 5 seasons, 528 684 head impacts recorded from 658 players (all male, mean age [SD], 19.02 [1.25] years) instrumented with the HIT System during football practices or games met quality standards for analysis. Players sustained a median of 415 (interquartile range [IQR], 190-727) recorded head impacts (ie, impacts) per season. Sixty-eight players sustained a diagnosed concussion. In total, 48.5% of concussions (n = 33) occurred during preseason training, despite preseason representing only 20.8% of the football season (0.059 preseason vs 0.016 regular-season concussions per team per day; mean difference, 0.042; 95% CI, 0.020-0.060; P = .001). Total HIE in the preseason occurred at twice the proportion of the regular season (324.9 vs 162.4 impacts per team per day; mean difference, 162.6; 95% CI, 110.9-214.3; P < .001). Every season, HIE per athlete was highest in August (preseason) (median, 146.0 impacts; IQR, 63.0-247.8) and lowest in November (median, 80.0 impacts; IQR, 35.0-148.0). Over 5 seasons, 72% of concussions (n = 49) (game proportion, 0.28; 95% CI, 0.18-0.40; P < .001) and 66.9% of HIE (262.4 practices vs 137.2 games impacts per player; mean difference, 125.3; 95% CI, 110.0-140.6; P < .001) occurred in practice. Even within the regular season, total HIE in practices (median, 175.0 impacts per player per season; IQR, 76.0-340.5) was 84.2% higher than in games (median, 95.0 impacts per player per season; IQR, 32.0-206.0). Conclusions and Relevance: Concussion incidence and HIE among college football players are disproportionately higher in the preseason than regular season, and most concussions and HIE occur during football practices, not games. These data point to a powerful opportunity for policy, education, and other prevention strategies to make the greatest overall reduction in concussion incidence and HIE in college football, particularly during preseason training and football practices throughout the season, without major modification to game play. Strategies to prevent concussion and HIE have important implications to protecting the safety and health of football players at all competitive levels.

Psychometric properties of the standardized assessment of concussion in youth football: Validity, reliability, and demographic factors.

The objective of this study was to determine the psychometrics (reliability, validity) of the original Standardized Assessment of Concussion (SAC) in a youth sample (ages 11 to 13). Demographic factors of race, level of vocabulary knowledge, mother's level of education were also considered. Over 150 youth football athletes completed the SAC and a brief battery of NIH Toolbox cognitive tests as part of a larger study on biomechanical factors in youth sport concussion. This was a within-subjects design (pre-season, post-season assessments), and correlational analysis of convergent and discriminant validity. Between groups analysis based on demographic differences was also employed. The pre-season SAC scores were not different by age; however, SAC scores were statistically different by race: t(155) = 3.162, p = .002, d = .519. Maternal level of education and participant vocabulary scores were related to racial group membership. Convergent and discriminant validity were established compared to NIH Toolbox tests of memory and speed. Pre-post-season tests for 108 participants established marginally acceptable test-retest reliability (ICC = .692). These data support the use of the original SAC in youth football although clinicians must be aware of racial differences in scores.