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Although head injuries are common in cycling, exact conditions associated with cyclist head impacts are difficult to determine. Previous studies have attempted to reverse engineer cyclist head impacts by reconstructing bicycle helmet residual damage, but they have been limited by simplified damage assessment and testing. The present study seeks to enhance knowledge of cyclist head impact conditions by reconstructing helmet damage using advanced impact testing and damage quantification techniques. Damage to 18 helmets from cyclists treated in emergency departments was quantified using computed tomography and reconstructed using oblique impacts. Damage metrics were related to normal and tangential velocities from impact tests as well as peak linear accelerations (PLA) and peak rotational velocities (PRV) using case-specific regression models. Models then allowed original impact conditions and kinematics to be estimated for each case. Helmets were most frequently damaged at the front and sides, often near the rim. Concussion was the most common, non-superficial head injury. Normal velocity and PLA distributions were similar to previous studies, with median values of 3.4 m/s and 102.5 g. Associated tangential velocity and PRV medians were 3.8 m/s and 22.3 rad/s. Results can inform future oblique impact testing conditions, enabling improved helmet evaluation and design.

Background: Dual-task assessments can identify changes in postural control during recovery from a concussion. However, developing postural control in children presents a challenge when using adult balance assessments to examine children., Purpose: The purpose of this study was to investigate the reliability of a cognitive dual-task postural control testing protocol among a youth sample with no history of concussion or exposure to head impacts., Study Design: Reliability pilot study., Methods: Testing comprised nine 120 second trials of standing on a force plate collecting data at 250 Hz. Test conditions included no dual-task, counting backwards by 2, counting backwards by 3, listening, and the Stroop test. Subjects completed each test with open and closed eyes, except for the Stroop test. The force plate was used to measure the subjects' center of pressure (COP) trajectory., Results: Nine healthy, youth subjects (average age: 11.6 ± 0.5 years) with no history of concussion or exposure to head impacts participated. Reliability was good (>0.6) or excellent (>0.75) for COP speed, sway, and sample entropy measures for several test conditions. The eyes open, no task condition produced the lowest COP measures. No differences were observed between the other dual-task conditions., Conclusion: Given its high measures of reliability, this dual-task protocol might be able to detect postural control changes in concussed youth athletes., Evidence Level: 2., (© 2020 by the Sports Physical Therapy Section.)

Objective: To examine the association between estimated age at first exposure (eAFE) to American football and clinical measures throughout recovery following concussion., Methods: Participants were recruited across 30 colleges and universities as part of the National Collegiate Athletic Association (NCAA)-Department of Defense Concussion Assessment, Research and Education Consortium. There were 294 NCAA American football players (age 19 ± 1 years) evaluated 24-48 hours following concussion with valid baseline data and 327 (age 19 ± 1 years) evaluated at the time they were asymptomatic with valid baseline data. Participants sustained a medically diagnosed concussion between baseline testing and postconcussion assessments. Outcome measures included the number of days until asymptomatic, Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) composite scores, Balance Error Scoring System (BESS) total score, and Brief Symptom Inventory 18 (BSI-18) subscores. The eAFE was defined as participant's age at the time of assessment minus self-reported number of years playing football., Results: In unadjusted regression models, younger eAFE was associated with lower (worse) ImPACT Visual Motor Speed ( R 2 = 0.031, p = 0.012) at 24-48 hours following injury and lower (better) BSI-18 Somatization subscores ( R 2 = 0.014, p = 0.038) when the athletes were asymptomatic. The effect sizes were very small. The eAFE was not associated with the number of days until asymptomatic, other ImPACT composite scores, BESS total score, or other BSI-18 subscores., Conclusion: Earlier eAFE to American football was not associated with longer symptom recovery, worse balance, worse cognitive performance, or greater psychological distress following concussion. In these NCAA football players, longer duration of exposure to football during childhood and adolescence appears to be unrelated to clinical recovery following concussion., (© 2020 American Academy of Neurology.)

Identifying the associations between head impact biomechanics and clinical recovery may inform better head impact monitoring procedures and identify athletes who may benefit from early treatments aimed to enhance recovery. The purpose of this study was to test whether head injury biomechanics are associated with clinical recovery of symptom severity, balance, and mental status, as well as symptom resolution time (SRT) and return-to-participation (RTP) time. We studied 45 college American football players (n = 51 concussions) who sustained an incident concussion while participating in a multi-site study. Player race/ethnicity, prior concussion, medical history, position, body mass index, event type, and impact location were covariates in our multivariable analyses. Multivariable negative binomial regression models analyzed associations between our study outcomes and (1) injury-causing linear and rotational head impact severity, (2) season repetitive head impact exposure (RHIE), and (3) injury day RHIE. Median SRT was 6.1 days (IQR 5.8 days, n = 45) and median RTP time was 12.3 days (IQR 7.8 days, n = 36) across our study sample. RTP time was 86% (Ratio 1.86, 95% CI [1.05, 3.28]) longer in athletes with a concussion history. Offensive players had SRTs 49% shorter than defensive players (Ratio 0.51, 95% CI [0.29, 0.92]). Per-unit increases in season RHIE were associated with 22% longer SRT (Ratio 1.22, 95% CI [1.09, 1.36]) but 28% shorter RTP time (Ratio 0.72, 95% CI [0.56, 0.93]). No other head injury biomechanics predicted injury recovery.

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.

Measuring head impacts in sports can further our understanding of brain injury biomechanics and, hopefully, advance concussion diagnostics and prevention. Although there are many head impact sensors available, skepticism on their utility exists over concerns related to measurement error. Previous studies report mixed reliability in head impact sensor measurements, but there is no uniform approach to assessing accuracy, making comparisons between sensors and studies difficult. The objective of this paper is to introduce a two-phased approach to evaluating head impact sensor accuracy. The first phase consists of in-lab impact testing on a dummy headform at varying impact severities under loading conditions representative of each sensor's intended use. We quantify in-lab accuracy by calculating the concordance correlation coefficient (CCC) between a sensor's kinematic measurements and headform reference measurements. For sensors that performed reasonably well in the lab (CCC ≥ 0.80), we completed a second phase of evaluation on-field. Through video validation of impacts measured by sensors on athletes, we classified each sensor measurement as either true-positive and false-positive impact events and computed positive predictive value (PPV) to summarize real-world accuracy. Eight sensors were tested in phase one, but only four sensors were assessed in phase two. Sensor accuracy varied greatly. CCC from phase one ranged from 0.13 to 0.97, with an average value of 0.72. Overall, the four devices that were implemented on-field had PPV that ranged from 16.3 to 91.2%, with an average value of 60.8%. Performance in-lab was not always indicative of the device's performance on-field. The methods proposed in this paper aim to establish a comprehensive approach to the evaluation of sensors so that users can better interpret data collected from athletes.

The objective of this study was to compare head impact data acquired with an impact monitoring mouthguard (IMM) to the video-observed behavior of athletes' post-collision relative to their pre-collision behaviors. A total of n = 83 college and high school American football players wore the IMM and were video-recorded over 260 athlete-exposures. Ex-athletes and clinicians reviewed the video in a two-step process and categorized abnormal post-collision behaviors according to previously published Obvious Performance Decrement (OPD) definitions. Engineers qualitatively reviewed datasets to check head impact and non-head impact signal frequency and magnitude. The ex-athlete reviewers identified 2305 head impacts and 16 potential OPD impacts, 13 of which were separately categorized as Likely-OPD impacts by the clinical reviewers. All 13 Likely-OPD impacts were in the top 1% of impacts measured by the IMM (ranges 40-100 g, 3.3-7.0 m/s and 35-118 J) and 12 of the 13 impacts (92%) were to the side or rear of the head. These findings require confirmation in a larger data set before proposing any type of OPD impact magnitude or direction threshold exists. However, OPD cases in this study compare favorably with previously published impact monitoring studies in high school and college American football players that looked for OPD signs, impact magnitude and direction. Our OPD findings also compare well with NFL reconstruction studies for ranges of concussion and sub-concussive impact magnitudes in side/rear collisions, as well as prior theory, analytical models and empirical research that suggest a directional sensitivity to brain injury exists for single high-energy impacts.

Importance: Identifying plasma biomarkers associated with the amount of time an athlete may need before they return to sport (RTS) following a sport-related concussion (SRC) is important because it may help to improve the health and safety of athletes., Objective: To examine whether plasma biomarkers can differentiate collegiate athletes who RTS in less than 14 days or 14 days or more following SRC., Design, Setting, and Participants: This multicenter prospective diagnostic study, conducted by the National Collegiate Athletics Association-Department of Defense Concussion Assessment, Research, and Education Consortium, included 127 male and female athletes who had sustained an SRC while enrolled at 6 Concussion Assessment, Research, and Education Consortium Advanced Research Core sites as well as 2 partial-Advanced Research Core military service academies. Data were collected between February 2015 and May 2018. Athletes with SRC completed clinical testing and blood collection at preseason (baseline), postinjury (0-21 hours), 24 to 48 hours postinjury, time of symptom resolution, and 7 days after unrestricted RTS., Main Outcomes and Measures: A total of 3 plasma biomarkers (ie, total tau protein, glial fibrillary acidic protein [GFAP], and neurofilament light chain protein [Nf-L]) were measured using an ultrasensitive single molecule array technology and were included in the final analysis. RTS was examined between athletes who took less than 14 days vs those who took 14 days or more to RTS following SRC. Linear mixed models were used to identify significant interactions between period by RTS group. Area under the receiver operating characteristic curve analyses were conducted to examine whether these plasma biomarkers could discriminate between RTS groups., Results: The 127 participants had a mean (SD) age of 18.9 (1.3) years, and 97 (76.4%) were men; 65 (51.2%) took less than 14 days to RTS, and 62 (48.8%) took 14 days or more to RTS. Linear mixed models identified significant associations for both mean (SE) plasma total tau (24-48 hours postinjury, <14 days RTS vs ≥14 days RTS: -0.65 [0.12] pg/mL vs -0.14 [0.14] pg/mL; P = .008) and GFAP (postinjury, 14 days RTS vs ≥14 days RTS: 4.72 [0.12] pg/mL vs 4.39 [0.11] pg/mL; P = .04). Total tau at the time of symptom resolution had acceptable discrimination power (area under the receiver operating characteristic curve, 0.75; 95% CI, 0.63-0.86; P < .001). We also examined a combined plasma biomarker panel that incorporated Nf-L, GFAP, and total tau at each period to discriminate RTS groups. Although the analyses did reach significance at each time period when combined, results indicated that they were poor at distinguishing the groups (area under the receiver operating characteristic curve, <0.7)., Conclusions and Relevance: The findings of this study suggest that measures of total tau and GFAP may identify athletes who will require more time to RTS. However, further research is needed to improve our ability to determine recovery following an SRC.

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.

Conventional brain injury metrics are scalars that treat the whole head/brain as a single unit but do not characterize the distribution of brain responses. Here, we establish a network-based "response feature matrix" to characterize the magnitude and distribution of impact-induced brain strains. The network nodes and edges encode injury risks to the gray matter regions and their white matter interconnections, respectively. The utility of the metric is illustrated in injury prediction using three independent, real-world datasets: two reconstructed impact datasets from the National Football League (NFL) and Virginia Tech, respectively, and measured concussive and non-injury impacts from Stanford University. Injury predictions with leave-one-out cross-validation are conducted using the two reconstructed datasets separately, and then by combining all datasets into one. Using support vector machine, the network-based injury predictor consistently outperforms four baseline scalar metrics including peak maximum principal strain of the whole brain (MPS), peak linear/rotational acceleration, and peak rotational velocity across all five selected performance measures (e.g., maximized accuracy of 0.887 vs. 0.774 and 0.849 for MPS and rotational acceleration with corresponding positive predictive values of 0.938, 0.772, and 0.800, respectively, using the reconstructed NFL dataset). With sufficient training data, real-world injury prediction is similar to leave-one-out in-sample evaluation, suggesting the potential advantage of the network-based injury metric over conventional scalar metrics. The network-based response feature matrix significantly extends scalar metrics by sampling the brain strains more completely, which may serve as a useful framework potentially allowing for other applications such as characterizing injury patterns or facilitating targeted multi-scale modeling in the future.

Youth football helmet testing standards have served to largely eliminate catastrophic head injury from the sport. These standards, though, do not presently consider concussion and do not offer consumers the capacity to differentiate the impact performance of youth football helmets. This study adapted the previously developed Summation of Tests for the Analysis of Risk (STAR) equation for youth football helmet assessment. This adaptation made use of a youth-specific testing surrogate, on-field data collected from youth football players, and a concussion risk function developed for youth athletes. Each helmet is subjected to 48 laboratory impacts across 12 impact conditions. Peak linear head acceleration and peak rotational head acceleration values from each laboratory impact are aggregated into a single STAR value that combines player exposure and risk of concussion. This single value can provide consumers with valuable information regarding the relative performance of youth football helmets.

Background: Organizations recommend that athletes should be asymptomatic or symptom-limited before initiating a graduated return-to-play (GRTP) protocol after sports-related concussion, although asymptomatic or symptom-limited is not well-defined., Hypotheses: (1) There will be a range (ie, beyond zero as indicator of "symptom-free") in symptom severity endorsement when athletes are deemed ready to initiate a GRTP protocol. (2) Baseline symptom severity scores and demographic/preinjury medical history factors influence symptom severity scores at the commencement of the GRTP protocol. (3) Greater symptom severity scores at GRTP protocol initiation will result in longer protocol duration. (4) Symptom severity scores will not differ between those who did and did not sustain a repeat injury within 90 days of their initial injury., Study Design: Cohort study; Level of evidence, 2., Methods: Across 30 universities, athletes (N = 1531) completed assessments at baseline and before beginning the GRTP protocol, as determined by local medical staff. Symptom severity scores were recorded with the symptom checklist of the Sport Concussion Assessment Tool-3rd Edition. Nonparametric comparisons were used to examine the effect of medical, demographic, and injury factors on symptom endorsement at GRTP protocol initiation, as well as differences in symptom severity scores between those who did and did not sustain a repeat injury within 90 days. A Cox regression was used to examine the association between symptom severity scores at GRTP protocol initiation and protocol duration., Results: Symptom severity scores at the time when the GRTP protocol was initiated were as follows: 0 to 5 (n = 1378; 90.0%), 6 to 10 (n = 76; 5.0%), 11 to 20 (n = 42; 3.0%), and ≥21 (n = 35; 2.0%). Demographic (sex and age), medical (psychiatric disorders, attention-deficit/hyperactivity disorder, learning disorder), and other factors (baseline symptom endorsement and sleep) were significantly associated with higher symptom severity scores at the GRTP initiation ( P < .05). The 4 GRTP initiation time point symptom severity score groups did not significantly differ in total time to unrestricted RTP, χ 2 (3) = 1.4; P = .73. When days until the initiation of the GRTP protocol was included as a covariate, symptom severity scores between 11 and 20 ( P = .02; hazard ratio = 1.44; 95% CI, 1.06-1.96) and ≥21 ( P < .001; hazard ratio = 1.88; 95% CI, 1.34-2.63) were significantly associated with a longer GRTP protocol duration as compared with symptom severity scores between 0 and 5. Symptom severity scores at GRTP initiation did not significantly differ between those who sustained a repeat injury within 90 days and those who did not ( U = 29,893.5; P = .75)., Conclusion: A range of symptom severity endorsement was observed at GRTP protocol initiation, with higher endorsement among those with higher baseline symptom endorsement and select demographic and medical history factors. Findings suggest that initiation of a GRTP protocol before an absolute absence of all symptoms is not associated with longer progression of the GRTP protocol, although symptom severity scores >10 were associated with longer duration of a GRTP protocol. Results can be utilized to guide clinicians toward optimal GRTP initiation (ie, balancing active recovery with avoidance of premature return to activity).

Importance: There is potential scientific and clinical value in validation of objective biomarkers for sport-related concussion (SRC)., Objective: To investigate the association of acute-phase blood biomarker levels with SRC in collegiate athletes., Design, Setting, and Participants: This multicenter, prospective, case-control study was conducted by the National Collegiate Athletic Association (NCAA) and the US Department of Defense Concussion Assessment, Research, and Education (CARE) Consortium from February 20, 2015, to May 31, 2018, at 6 CARE Advanced Research Core sites. A total of 504 collegiate athletes with concussion, contact sport control athletes, and non-contact sport control athletes completed clinical testing and blood collection at preseason baseline, the acute postinjury period, 24 to 48 hours after injury, the point of reporting being asymptomatic, and 7 days after return to play. Data analysis was conducted from March 1 to November 30, 2019., Main Outcomes and Measures: Glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament light chain, and tau were quantified using the Quanterix Simoa multiplex assay. Clinical outcome measures included the Sport Concussion Assessment Tool-Third Edition (SCAT-3) symptom evaluation, Standardized Assessment of Concussion, Balance Error Scoring System, and Brief Symptom Inventory 18., Results: A total of 264 athletes with concussion (mean [SD] age, 19.08 [1.24] years; 211 [79.9%] male), 138 contact sport controls (mean [SD] age, 19.03 [1.27] years; 107 [77.5%] male), and 102 non-contact sport controls (mean [SD] age, 19.39 [1.25] years; 82 [80.4%] male) were included in the study. Athletes with concussion had significant elevation in GFAP (mean difference, 0.430 pg/mL; 95% CI, 0.339-0.521 pg/mL; P < .001), UCH-L1 (mean difference, 0.449 pg/mL; 95% CI, 0.167-0.732 pg/mL; P < .001), and tau levels (mean difference, 0.221 pg/mL; 95% CI, 0.046-0.396 pg/mL; P = .004) at the acute postinjury time point compared with preseason baseline. Longitudinally, a significant interaction (group × visit) was found for GFAP (F7,1507.36 = 16.18, P < .001), UCH-L1 (F7,1153.09 = 5.71, P < .001), and tau (F7,1480.55 = 6.81, P < .001); the interaction for neurofilament light chain was not significant (F7,1506.90 = 1.33, P = .23). The area under the curve for the combination of GFAP and UCH-L1 in differentiating athletes with concussion from contact sport controls at the acute postinjury period was 0.71 (95% CI, 0.64-0.78; P < .001); the acute postinjury area under the curve for all 4 biomarkers combined was 0.72 (95% CI, 0.65-0.79; P < .001). Beyond SCAT-3 symptom score, GFAP at the acute postinjury time point was associated with the classification of athletes with concussion from contact controls (β = 12.298; 95% CI, 2.776-54.481; P = .001) and non-contact sport controls (β = 5.438; 95% CI, 1.676-17.645; P = .005). Athletes with concussion with loss of consciousness or posttraumatic amnesia had significantly higher levels of GFAP than athletes with concussion with neither loss of consciousness nor posttraumatic amnesia at the acute postinjury time point (mean difference, 0.583 pg/mL; 95% CI, 0.369-0.797 pg/mL; P < .001)., Conclusions and Relevance: The results suggest that blood biomarkers can be used as research tools to inform the underlying pathophysiological mechanism of concussion and provide additional support for future studies to optimize and validate biomarkers for potential clinical use in SRC.

Cycling is a leading cause of mild traumatic brain injury in the US. While bicycle helmets help protect cyclists who crash, limited biomechanical data exist differentiating helmet protective capabilities. This paper describes the development of a bicycle helmet evaluation scheme based in real-world cyclist accidents and brain injury mechanisms. Thirty helmet models were subjected to oblique impacts at six helmet locations and two impact velocities. The summation of tests for the analysis of risk (STAR) equation, which condenses helmet performance from a range of tests into a single value, was used to summarize measured linear and rotational head kinematics in the context of concussion risk. STAR values varied between helmets (10.9-25.3), with lower values representing superior protection. Road helmets produced lower STAR values than urban helmets. Helmets with slip planes produced lower STAR values than helmets without. This bicycle helmet evaluation protocol can educate consumers on the relative impact performance of various helmets and stimulate safer helmet design.

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82-0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s 2 compared to 4412 ± 2326 rad/s 2 . These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

Background: Concern for head injuries is widespread and has been reported by the media to be the number one cause of decreased participation in football among the American youth population. Identifying player mechanisms associated with intentional, or purposeful, head impacts should provide critical data for rule modifications, educational programs, and equipment design., Purpose: To investigate the frequency of intentional and unintentional head impacts and to examine the player mechanisms associated with intentional high-magnitude head impacts by comparing the impact mechanism distributions among session type, player position, and ball possession., Study Design: Cross-sectional study; Level of evidence, 3., Methods: Head impact sensors and video footage of 68 players were used to analyze and classify 1319 high-magnitude impacts recorded over 1 season of youth football., Results: In total, 80% of the high-magnitude head impacts were classified as being caused by intentional use of the head. Head-to-head impact was the primary impact mechanism (n = 868; 82.7%) within the 1050 intentional high-magnitude impacts, with classifiable mechanisms, followed by head-to-body (n = 139; 13.2%), head-to-ground (n = 34; 3.2%), and head-to-equipment (n = 9; 0.9%). Head-to-head impacts also accounted for a greater proportion of impacts during practices (n = 625; 88.9%) than games, for linemen (n = 585; 90.3%) than perimeters and backs, and for ball carriers (n = 72; 79.1%) than tacklers., Conclusion: Overall, the majority of high-magnitude head impacts were intentional and resulted from head-to-head contact. The proportion of head-to-head contact was significantly higher for practices than games, linemen than backs and perimeter players, and ball carriers than tacklers.

Placental growth factor (PlGF), total soluble fms-like tyrosine-kinase 1 (sFlt-1) and its placental-specific variant, sFlt-1 e15a, show promise as biomarkers for the prediction and diagnosis of preeclampsia. This study describes the degradation of PlGF, sFlt-1 and sFlt-1 e15a within maternal serum and plasma to assist clinical implementation. Whole blood was refrigerated at 4 °C for up to 48 h prior to centrifugation for isolation of plasma and serum. PlGF and sFlt-1 were quantified using the B.R.A.H.M.S Kryptor Compact PLUS; sFlt-1 e15a via a custom ELISA. All three analytes are stable for at least 48 h at 4 °C. Serum and plasma performed comparably., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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.

Studies of football athletes have implicated repetitive head impact exposure in the onset of cognitive and brain structural changes, even in the absence of diagnosed concussion. Those studies imply accumulating damage from successive head impacts reduces tolerance and increases risk for concussion. Support for this premise is that biomechanics of head impacts resulting in concussion are often not remarkable when compared to impacts sustained by athletes without diagnosed concussion. Accordingly, this analysis quantified repetitive head impact exposure in a cohort of 50 concussed NCAA Division I FBS college football athletes compared to controls that were matched for team and position group. The analysis quantified the number of head impacts and risk weighted exposure both on the day of injury and for the season to the date of injury. 43% of concussed athletes had the most severe head impact exposure on the day of injury compared to their matched control group and 46% of concussed athletes had the most severe head impact exposure for the season to the date of injury compared to their matched control group. When accounting for date of injury or season to date of injury, 72% of all concussed athletes had the most or second most severe head impact exposure compared to their matched control group. These trends associating cumulative head impact exposure with concussion onset were stronger for athletes that participated in a greater number of contact activities. For example, 77% of athletes that participated in ten or more days of contact activities had greater head impact exposure than their matched control group. This unique analysis provided further evidence for the role of repetitive head impact exposure as a predisposing factor for the onset of concussion. The clinical implication of these findings supports contemporary trends of limiting head impact exposure for college football athletes during practice activities in an effort to also reduce risk of concussive injury.

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 < 0.0001; η 2  = 0.46), team (p = 0.0016; η 2  = 0.03), and the number of game impacts (p < 0.0001; η 2  = 0.03), which served as a correlate for player ability. Even after controlling for practice participation, player position, team, and ability, differences between individuals accounted for 48% of the variance in head impact exposure in practice. This work demonstrates the importance of considering head impact exposure on a subject-specific basis rather than estimating head impact exposure from aggregate data.

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.

Objective: Youth football attracts approximately 3.5 million participants every year, but concern has recently arisen about the long-term effects of experiencing repetitive head accelerations from a young age due to participation in football. The objective of this study was to quantify total involvement in high-magnitude impacts among individual players in youth football practices. The authors explored the relationship between the total number of high-magnitude accelerations in which players were involved (experienced either by themselves or by other players) during practices and the number of high-magnitude accelerations players experienced., Methods: A local cohort of 94 youth football players (mean age 11.9 ± 1.5, mean body mass 50.3 ± 16.4 kg) from 4 different teams were recruited and outfitted with helmet-mounted accelerometer arrays. The teams were followed for one season each for a total of 128 sessions (practices, games, and scrimmages). All players involved in high-magnitude (greater than 40g) head accelerations were subsequently identified through analysis of practice film., Results: Players who experienced more high-magnitude accelerations were more likely to be involved in impacts associated with high-magnitude accelerations in other players. A small subset of 6 players (6%) were collectively involved in 230 (53%) high-magnitude impacts during practice, were involved in but did not experience a high-magnitude acceleration 78 times (21% of the 370 one-sided high-magnitude impacts), and experienced 152 (30%) of the 502 high-magnitude accelerations measured. Quarterbacks/running backs/linebackers were involved in the greatest number of high-magnitude impacts in practice and experienced the greatest number of high-magnitude accelerations. Which team a player was on was an important factor, as one team showed much greater head impact exposure than all others., Conclusions: This study showed that targeting the most impact-prone players for individualized interventions could reduce high-magnitude acceleration exposure for entire teams. These data will help to further quantify elevated head acceleration exposure and enable data-driven interventions that modify exposure for individual players and entire teams.

Previous studies have shown that mild traumatic brain injury (mTBI) can cause abnormalities in clinically relevant magnetic resonance imaging (MRI) sequences. No large-scale study, however, has prospectively assessed this in athletes with sport-related concussion (SRC). The aim of the current study was to characterize and compare the prevalence of acute, trauma-related MRI findings and clinically significant, non-specific MRI findings in athletes with and without SRC. College and high-school athletes were prospectively enrolled and participated in scanning sessions between January 2015 through August 2017. Concussed contact sport athletes ( n  = 138; 14 female [F]; 19.5 ± 1.6 years) completed up to four scanning sessions after SRC. Non-concussed contact ( n  = 135; 15 F; 19.7 ± 1.6) and non-contact athletes ( n  = 96; 15 F; 20.0 ± 1.7) completed similar scanning sessions and served as controls. Board-certified neuroradiologists, blinded to SRC status, reviewed T 1 -weighted and T 2 -weighted fluid-attenuated inversion recovery and T 2 *-weighted and T 2 -weighted images for acute (i.e., injury-related) or non-acute findings that prompted recommendation for clinical follow-up. Concussed athletes were more likely to have MRI findings relative to contact (30.4% vs. 15.6%; odds ratio [OR] = 2.32; p  = 0.01) and non-contact control athletes (19.8%; OR = 2.11; p  = 0.04). Female athletes were more likely to have MRI findings than males (43.2% vs. 19.4%; OR = 2.62; p  = 0.01). One athlete with SRC had an acute, injury-related finding; group differences were largely driven by increased rate of non-specific white matter hyperintensities in concussed athletes. This prospective, large-scale study demonstrates that <1% of SRCs are associated with acute injury findings on qualitative structural MRI, providing empirical support for clinical guidelines that do not recommend use of MRI after SRC.

During normal participation in football, players are exposed to repetitive subconcussive head impacts, or impacts that do not result in signs and symptoms of concussion. To better understand the effects of repetitive subconcussive impacts, the biomechanics of on-field head impacts and resulting brain deformation need to be well characterized. The current study evaluates local brain response to typical youth football head impacts using the atlas-based brain model (ABM), an anatomically accurate brain finite element (FE) model. Head impact kinematic data were collected from three local youth football teams using the Head Impact Telemetry (HIT) System. The azimuth and elevation angles were used to identify impacts near six locations of interest, and low, moderate, and high acceleration magnitudes (5th, 50th, and 95th percentiles, respectively) were calculated from the grouped impacts for FE simulation. Strain response in the brain was evaluated by examining the range and peak maximum principal strain (MPS) values in each element. A total of 40,538 impacts from 119 individual athletes were analyzed. Impacts to the facemask resulted in 0.18 MPS for the high magnitude impact category. This was 1.5 times greater than the oblique impact location, which resulted in the lowest strain value of 0.12 for high magnitude impacts. Overall, higher strains resulted from a 95th percentile lateral impact (41.0 g , 2556 rad/sec 2 ) with two predominant axes of rotation than from a 95th percentile frontal impact (67.6 g , 2641 rad/sec 2 ) with a single predominant axis of rotation. These findings highlight the importance of accounting for directional dependence and relative contribution of axes of rotation when evaluating head impact response.

Youth football players comprise almost 70% of the football playing population, and the ongoing development of these athletes makes the understanding of concussions and repetitive head impact exposure in this population of particular concern. The objective of this study was to determine how player position and coaching influence head impact exposure in youth football players while controlling for player age. This analysis focused on a cohort of 45 youth football players between the ages of 9 and 14 that had helmets instrumented with accelerometer arrays for at least two seasons. A repeated measures, mixed model was used to assess the effect of coach and position on impacts per session, 95 th percentile linear acceleration, and 95 th percentile rotational head acceleration. Head impact exposure was also modeled in aggregate and for practices and games independently. Player position and coach were observed to be significant factors related to head impact exposure. These data highlight the important role that coaches have in managing head impact exposure for teams they lead., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest.

Infield softball masks are intended to reduce facial fracture risk, but are rarely worn. The objective of this study was to evaluate the effectiveness of infield masks' ability to attenuate facial fracture risk over a range of designs and materials. To simulate batted ball impacts, a customized pitching machine was used to propel softballs at 24.6 ± 0.51 m/s. The balls impacted locations centered over the maxilla and zygoma bones of a FOCUS headform. The FOCUS headform was attached to a 50th percentile Hybrid III neck and secured to a slider table. Facial fracture risk of each facial bone was compared between masks and impact locations using peak resultant forces. Analysis of these data showed that the mask material and the distance between the mask and the impacted facial bone were key factors in determining a mask's performance. The effectiveness of masks varied. It was found that a metal mask with a separation distance ≥ 35 mm away from the maxilla and ≥ 25 mm away from the zygoma best reduced facial fracture risk for these test configurations. Plastic masks performed worse because they excessively deformed allowing ball contact with the face. This study assesses various mask designs for their ability to reduce facial fracture and suggests design recommendations based on the impact configurations tested.

This study aimed to compare head impact exposures between practices and games in football players ages 9 to 14 years, who account for approximately 70% of all football players in the United States. Over a period of 2 seasons, 136 players were enrolled from 3 youth programs, and 49,847 head impacts were recorded from 345 practices and 137 games. During the study, individual players sustained a median of 211 impacts per season, with a maximum of 1226 impacts. Players sustained 50th (95th) percentile peak linear acceleration of 18.3 (46.9) g, peak rotational acceleration of 1305.4 (3316.6) rad·s -2 , and Head Impact Technology Severity Profile of 13.7 (24.3), respectively. Overall, players with a higher frequency of head impacts at practices recorded a higher frequency of head impacts at games (P < .001, r 2  = .52), and players who sustained a greater average magnitude of head impacts during practice also recorded a greater average magnitude of head impacts during games (P < .001). The youth football head impact data quantified in this study provide valuable insight into the player exposure profile, which should serve as a key baseline in efforts to reduce injury.

Cycling is a leading cause of sport-related head injuries in the U.S. Although bicycle helmets must comply with standards limiting head acceleration in severe impacts, helmets are not evaluated under more common, concussive-level impacts, and limited data are available indicating which helmets offer superior protection. Further, standards evaluate normal impacts, while real-world cyclist head impacts are oblique-involving normal and tangential velocities. The objective of this study was to investigate differences in protective capabilities of ten helmet models under common real-world accident conditions. Oblique impacts were evaluated through drop tests onto an angled anvil at common cyclist head impact velocities and locations. Linear and rotational accelerations were evaluated and related to concussion risk, which was then correlated with design parameters. Significant differences were observed in linear and rotational accelerations between models, producing concussion risks spanning >50% within single impact configurations. Risk differences were more attributable to linear acceleration, as rotational varied less between models. At the temporal location, shell thickness, vent configuration, and radius of curvature were found to influence helmet effective stiffness. This should be optimized to reduce impact kinematics. At the frontal, helmet rim location, liner thickness tapered off for some helmets, likely due to lack of standards testing at this location. This is a frequently impacted location for cyclists, suggesting that the standards testable area should be expanded to include the rim. These results can inform manufacturers, standards bodies, and consumers alike, aiding the development of improved bicycle helmet safety.

Football helmet testing standards for youth players make use of the same testing protocol for adult helmets despite research showing differences in head impact exposure between these populations. The objective of this study was to pair estimated impact velocities with linear acceleration data collected from on-field head impacts in youth football to inform youth-specific helmet testing methods. A total of 49 youth football players received helmets instrumented with accelerometer arrays to measure head acceleration throughout the season. Using video recordings of games from a single camera, impact velocities were estimated for impacts with known acceleration magnitudes. On-field accelerations ranged from 40 to 85 g, while impact velocities ranged from 0.5 to 5.5 m/s. The average error associated with these velocity estimates was below 10%, and a zoomed-in camera view provided results more consistent with true velocity. Velocities estimated from direct helmet-to-helmet impacts matched more closely with linear acceleration than other kinds of impacts. These findings may be used to inform testing methods/conditions that are more representative of impacts experienced by youth football players.

Advances in low-cost wearable head impact sensor technology provide potential benefits regarding sports safety for both consumers and researchers. However, previous laboratory evaluations are not directly comparable and do not incorporate test conditions representative of unhelmeted impacts. This study addresses those limitations. The xPatch by X2 Biosystems and the SIM-G by Triax Technologies were placed on a National Operating Committee on Standards for Athletic Equipment (NOCSAE) headform with a Hybrid III neck which underwent impact tests using a pendulum. Impact conditions included helmeted, padded impactor to bare head, and rigid impactor to bare head to represent long- and short-duration impacts seen in helmeted and unhelmeted sports. The wearable sensors were evaluated on their kinematic accuracy by comparing results to reference sensors located at the headform center of gravity. Statistical tests for equivalence were performed on the slope of the linear regression between wearable sensors and reference. The xPatch gave equivalent measurements to the reference in select longer-duration impacts, whereas the SIM-G had large variance leading to no equivalence. For the short-duration impacts, both wearable sensors underpredicted the reference. This error can be improved with increases in sampling rate from 1 to 1.5 kHz. Follow-up evaluations should be performed on the field to identify error in vivo.

Kinematic measurements of head impacts are sensitive to sports concussion, but not highly specific. One potential reason is these measures reflect input conditions only and may have varying degrees of correlation to regional brain tissue deformation. In this study, previously reported head impact data recorded in the field from high school and collegiate football players were analyzed using two finite element head models (FEHM). Forty-five impacts associated with immediately diagnosed concussion were simulated along with 532 control impacts without identified concussion obtained from the same players. For each simulation, intracranial response measures (max principal strain, strain rate, von Mises stress, and pressure) were obtained for the whole brain and within four regions of interest (ROI; cerebrum, cerebellum, brain stem, corpus callosum). All response measures were sensitive to diagnosed concussion; however, large inter-athlete variability was observed and sensitivity strength depended on measure, ROI, and FEHM. Interestingly, peak linear acceleration was more sensitive to diagnosed concussion than all intracranial response measures except pressure. These findings suggest FEHM may provide unique and potentially important information on brain injury mechanisms, but estimations of concussion risk based on individual intracranial response measures evaluated in this study did not improve upon those derived from input kinematics alone.

Background: Timely removal from activity after concussion symptoms remains problematic despite heightened awareness. Previous studies indicated potential adverse effects of continuing to participate in physical activity immediately after sustaining a concussion. Hypothesis/Purpose: The purpose was to determine the effect of timing of removal from play after concussion on clinical outcomes. It was hypothesized that immediate removal from activity after sport-related concussion (SRC) would be associated with less time missed from sport, a shorter symptomatic period, and better outcomes on acute clinical measures., Study Design: Cohort study; Level of evidence, 3., Methods: Data were reported from the National Collegiate Athletic Association and Department of Defense Grand Alliance: Concussion Awareness, Research, and Education (CARE) Consortium. Participants with 506 diagnosed SRCs from 18 sports and 25 institutions and military service academies were analyzed and classified as either immediate removal from activity (I-RFA) or delayed removal from activity (D-RFA). Outcomes of interest included time missed from sport attributed to their SRC, symptom duration, and clinical assessment scores., Results: There were 322 participants (63.6%) characterized as D-RFA. I-RFA status was associated with significantly less time missed from sport ( R 2 change = .022-.024, P < .001 to P = .001) and shorter symptom duration ( R 2 change = .044-.046, P < .001 [all imputations]) while controlling for other SRC recovery modifiers. These athletes missed approximately 3 fewer days from sport participation. I-RFA athletes had significantly less severe acute SRC symptoms and were at lower risk of recovery taking ≥14 days (relative risk = .614, P < .001, small-medium effect size) and ≥21 days (relative risk = .534, P = .010, small effect size)., Conclusion: I-RFA is a protective factor associated with less severe acute symptoms and shorter recovery after SRC. Conveying this message to athletes, coaches, and others involved in the care of athletes may promote timely injury reporting.

Static postural control testing is often conducted by clinicians and athletic trainers for use with athletes who have sustained a concussion. Dynamic postural control involves the body's response to perturbation of the center of mass and may offer additional insight that static testing cannot capture. The objective of this study was to assess the reliability and feasibility of a balance protocol consisting of both static and dynamic postural control assessments with a healthy, adult population. Subjects stood in both unipedal and bipedal stances on a force plate to capture quantitative data regarding the center of pressure over time. Further, subjects completed the Balance Error Scoring System (BESS), a static measure, and a modified version of the Star Excursion Balance Test (SEBT), a dynamic measure. Reliability with the BESS was limited, while moderate to strong reliability was obtained for the modified SEBT. Unipedal stances were associated with a greater variance than bipedal stances for both the BESS and force plate protocol. These assessments will be applied within a pediatric populations to determine the validity of their use. Further postural control research is necessary to determine the most viable assessments for use within an active, pediatric population.

Concussions occur in youth football with lower frequency than observed at higher levels of play, though the effect of repetitive subconcussive head impacts resulting from participation in youth football is unknown at this point. One measure shown to be affected by concussions is athlete postural control. The objective of this study was to compare performance on the Balance Error Scoring System (BESS) and a force plate protocol at two time points within a cohort of healthy youth football players and healthy non-contact youth track or baseball athletes. In absence of a clinically-diagnosed concussion, the hypothesis was tested that a season of youth football would affect measures of static postural control and stability. Between time points, there were no significant differences observed between either BESS scores or force plate metrics. Between athlete groups, there were no significant differences observed for either the BESS or the force plate protocol. Particularly for pediatric males, postural control is still developing and current assessments may not be sensitive enough to detect changes. Continued research is necessary to determine what postural control testing may be most viable for use within an active, pediatric population.

Postural control testing is often used by clinicians and athletic trainers to assess the health of athletes during recovery from a concussion. Characterization of postural control as a clinical tool for use with youth athletes is limited though. The objective of this study was to compare performance on the Balance Error Scoring System (BESS) and a force plate protocol at the beginning and end of a season of football within a cohort of 34 healthy youth football players (average age of 9.9 ± 0.6 y). A secondary aim was to investigate if changes in measures of balance from the postseason to the preseason were correlated with head impact exposure. Players completed testing at the beginning and end of the youth football season. There were no significant differences between BESS scores before the season and after the season (P = .54). Performance on the BESS was not associated with any of the center of pressure metrics considered in this study. No correlation was observed between measures of balance and head impact exposure for the season. Further research is required to determine the viability of postural control testing with this population.

In order to address concerns about head injury in youth sports, a number of youth football organizations have developed rules and recommendations surrounding the tackling form which should be used in order to reduce unnecessary head impact exposure. Reduction in injury has been suggested with these programs, but association between tackling form and head acceleration magnitude has not been studied previously. To address this knowledge gap, grading criteria were developed from multiple youth organizations' recommendations for a collision. A total of 142 tackles from a youth football team were graded. Head acceleration data were collected from helmet-mounted accelerometer arrays. An association was found between poor form and resultant head acceleration being greater than 40 g for both the tackler and the ball carrier. This study demonstrates the potential usefulness of tackling technique coaching programs in youth football.

Objective: The purpose of this study was to investigate relative differences in impact attenuation capabilities of bicycle helmets under real-world impact conditions and safety standard-specified conditions using a standard rig., Methods: A Consumer Product Safety Commission (CPSC) test rig was used to impact 10 helmet models of varied design. Impact configurations included 2 locations and 2 velocities. A frontal rim location (inferior to the standard-defined test area) and a temporal location were selected to reflect common cyclist impacts. An impact velocity of 3.4 m/s, an average normal impact velocity in cyclist accidents, was selected, as well as the CPSC standard velocity of 6.2 m/s. Four samples per helmet model were subjected to each of the 4 impact configurations once (randomized test order per sample), resulting in 160 drop tests. Peak linear acceleration (PLA) and head injury criterion (HIC)-based Abbreviated Injury Scale (AIS) ≥ 4 brain injury risk were determined and compared across helmets and impact configurations using analysis of variance. Other impact characteristics such as duration, effective liner stiffness, and energy dissipated were also calculated from acceleration data., Results: Helmet performance varied significantly between models. PLA ranged from 78 to 169 g at 3.4 m/s (0-2% AIS ≥ 4 brain injury risk) and 165-432 g (10-100% risk) at 6.2 m/s. Temporal impacts resulted in higher PLAs than frontal impacts, likely due to increased effective liner stiffness. However, 2 helmets exceeded the CPSC pass-fail threshold (300 g) at the frontal rim location, producing >70% risk. Force-displacement curves suggest that bottoming-out occurred in these impacts. Aside from bottoming-out cases, helmets that performed worse in one impact configuration tended to perform worse in others, with non-road-style helmets among the worst., Conclusions: The 10 bicycle helmets tested produced considerable differences in their protective capabilities under both real-world and standard-specified conditions on the CPSC rig. Risk of severe brain injury varied widely between helmets at the standard impact velocity, whereas the common, lower severity impacts produced PLAs associated with concussion. Helmets of a nonroad style generally performed worse across configuration. The temporal location produced higher risks for most helmets, although some helmets were found to offer inadequate protection at the helmet rim. Because this is a commonly impacted location in cyclist accidents, there may be benefit to expanding the testable area in standards to include the rim. Results from this study demonstrate the value in testing nonstandard conditions and can be used to inform standards testing and helmet design.

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.

Understanding the biomechanics of head injuries is essential for the development of preventive strategies and protective equipment design. However, there are many challenges associated with determining the forces that cause injury. Acceleration of the skull is often measured because it is relatively easy to quantify and relates to severity of impact, but it is difficult to relate those measurements to the type and extent of injury that occurs. Experimental work in the laboratory has used either human cadavers or volunteers. Cadavers can be instrumented with high-grade sensors that are tightly coupled to the skull for accurate measurements, but they cannot exhibit a functional response to determine a threshold for brain injury. Volunteers can also be instrumented with high-grade sensors in controlled laboratory experiments, but any head accelerations they experience must be well below an injurious level. Athletes participating in contact sports present a unique opportunity to collect biomechanical data from populations that have increased exposure to head impacts and a higher risk of head injury than the general population. Recent advances in sensor technology have allowed for more accurate measurements from instrumented athletes during play, but it is challenging to tightly couple the instrumentation to the skull to provide meaningful measurements. Because of the challenges associated with on-field measurements, it is important to consider the type of sensor used and its accuracy in the field when evaluating head impact data from athletes., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Current youth football helmets, intended for players under the age of 14 years old, are similar in design and are tested under the same standard as varsity football helmets. This study evaluated the impact performance of matched youth and adult varsity football helmets. Eight helmet models were evaluated using an impact pendulum, with a modified National Operating Committee on Standards for Athletic Equipment (NOCSAE) medium sized headform mounted on a Hybrid III 50 th percentile neck. Four locations on the helmet shell at three impact velocities were tested for three trials, for a total of 576 impact tests. Linear acceleration, rotational acceleration, and a concussion correlate were recorded for each test and a comparison between the youth and varsity helmets were made. It was found that the age group the helmet is intended for did not have a significant effect on the impact performance of the helmet in either linear acceleration, rotational acceleration, or concussion correlate. These results are likely due to the similarities in helmet design resulting from being tested to the same standard. Although it is unknown how a youth helmet should differ from a varsity helmet, differences in impact exposure, anthropometry, physiology, and injury tolerance are factors to consider. These data serves as a reference point for future youth-specific helmet design and helmet standards.

Youth football helmets currently undergo the same impact testing and must satisfy the same criteria as varsity helmets, although youth football players differ from their adult counterparts in anthropometry, physiology, and impact exposure. This study aimed to relate football helmet standards testing to on-field head impact magnitudes for youth and varsity football helmets. Head impact data, filtered to include only impacts to locations in the current National Operating Committee on Standards for Athletic Equipment standard, were collected for 48 collegiate players (ages 18-23 years) and 25 youth players (ages 9-11 years) using helmet-mounted accelerometer arrays. These on-field data were compared to a series of National Operating Committee on Standards for Athletic Equipment standard drop tests with a youth and varsity Riddell Speed helmet. In the on-field data, the adult players had a higher frequency of impact than the youth players, and a significant difference in head acceleration magnitude only existed at the top location (p < 0.001). In the laboratory drop tests, the only significant difference between the youth and varsity helmets was at the 3.46 m/s (61 cm) impact to the front location (p = 0.0421). Drop tests generated head accelerations within the top 10% of measured on-field impacts, at all locations and drop heights, demonstrating that drop tests are representative of the most severe head impacts experienced by youth and adult football players on the field. Current standards have been very effective at eliminating skull fracture and severe brain injury in both populations. This analysis suggests that there is not currently a need for a youth-specific drop test standard. However, there may be such a need if helmet testing standards are updated to address concussion, paired with a better understanding of differences in concussion tolerance between youth and adult populations., Competing Interests: Declaration of conflicting interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

OBJECTIVE Even in the absence of a clinically diagnosed concussion, research suggests that neurocognitive changes may develop in football players as a result of frequent head impacts that occur during football games and practices. The objectives of this study were to determine the specific situations in which high-magnitude impacts (accelerations exceeding 40 g) occur in youth football games and practices and to assess how representative practice activities are of games with regard to high-magnitude head impact exposure. METHODS A total of 45 players (mean age 10.7 ± 1.1 years) on 2 youth teams (Juniors [mean age 9.9 ± 0.6 years; mean body mass 38.9 ± 9.9 kg] and Seniors [mean age 11.9 ± 0.6 years; mean body mass 51.4 ± 11.8 kg]) wore helmets instrumented with accelerometer arrays to record head impact accelerations for all practices and games. Video recordings from practices and games were used to verify all high-magnitude head impacts, identify specific impact characteristics, and determine the amount of time spent in each activity. RESULTS A total of 7590 impacts were recorded, of which 571 resulted in high-magnitude head impact accelerations exceeding 40 g (8%). Impacts were characterized based on the position played by the team member who received the impact, the part of the field where the impact occurred, whether the impact occurred during a game or practice play, and the cause of the impact. High-magnitude impacts occurred most frequently in the open field in both games (59.4%) and practices (67.5%). "Back" position players experienced a greater proportion of high-magnitude head impacts than players at other positions. The 2 teams in this study structured their practice sessions similarly with respect to time spent in each drill, but impact rates differed for each drill between the teams. CONCLUSIONS High-magnitude head impact exposure in games and practice drills was quantified and used as the basis for comparison of exposure in the 2 settings. In this cohort, game impact rates exceeded those for practice. Back players, who were often positioned in the open field, were shown to experience elevated levels of head impact exposure relative to players at other positions. The analysis also suggests that practice intensity, which may be influenced by coaching style, may also affect high-magnitude head impact exposure. Future studies should investigate this aspect as a factor affecting head impact exposure.

Regulations have allowed for increased unmanned aircraft systems (UAS) operations over the last decade, yet operations over people are still not permitted. The objective of this study was to estimate the range of injury risks to humans due to UAS impact. Three commercially-available UAS models that varied in mass (1.2-11 kg) were evaluated to estimate the range of risk associated with UAS-human interaction. Live flight and falling impact tests were conducted using an instrumented Hybrid III test dummy. On average, live flight tests were observed to be less severe than falling impact tests. The maximum risk of AIS 3+ injury associated with live flight tests was 11.6%, while several falling impact tests estimated risks exceeding 50%. Risk of injury was observed to increase with increasing UAS mass, and the larger models tested are not safe for operations over people in their current form. However, there is likely a subset of smaller UAS models that are safe to operate over people. Further, designs which redirect the UAS away from the head or deform upon impact transfer less energy and generate lower risk. These data represent a necessary impact testing foundation for future UAS regulations on operations over people.

Objective: The aim of this study was to quantify head impact exposure for a collegiate women's soccer team over the course of the 2014 season., Design: Observational and prospective study., Setting: Virginia Tech women's soccer games and practices., Participants: Twenty-six collegiate level women's soccer players with a mean player age of 19 ± 1., Interventions: Participating players were instrumented with head impact sensors for biomechanical analysis. Video recordings of each event were used to manually verify each impact sustained., Main Outcome Measures: Head impact counts by player position and impact situation., Results: The sensors collected data from a total of 17 865 accelerative events, 8999 of which were classified as head impacts. Of these, a total of 1703 impacts were positively identified (19% of total real impacts recorded by sensor), 90% of which were associated with heading the ball. The average number of impacts per player per practice or game was 1.86 ± 1.42. Exposure to head impact varied by player position., Conclusions: Head impact exposure was quantified through 2 different methods, which illustrated the challenges associated with autonomously collecting acceleration data with head impact sensors. Users of head impact data must exercise caution when interpreting on-field head impact sensor data.

Context: With an estimated 3.8 million sport- and recreation-related concussions occurring annually, targeted prevention and diagnostic methods are needed. Biomechanical analysis of head impacts may provide quantitative information that can inform both prevention and diagnostic strategies., Objective: To assess available head-impact devices and their clinical utility., Data Sources: We performed a systematic search of the electronic database PubMed for peer-reviewed publications, using the following phrases: accelerometer and concussion, head impact telemetry, head impacts and concussion and sensor, head impacts and sensor, impact sensor and concussion, linear acceleration and concussion, rotational acceleration and concussion, and xpatch concussion. In addition to the literature review, a Google search for head impact monitor and concussion monitor yielded 15 more devices., Study Selection: Included studies were performed in vivo, used commercially available devices, and focused on sport-related concussion., Data Extraction: One author reviewed the title and abstract of each study for inclusion and exclusion criteria and then reviewed each full-text article to confirm inclusion criteria. Controversial articles were reviewed by all authors to reach consensus., Data Synthesis: In total, 61 peer-reviewed articles involving 4 head-impact devices were included. Participants in boxing, football, ice hockey, soccer, or snow sports ranged in age from 6 to 24 years; 18% (n = 11) of the studies included female athletes. The Head Impact Telemetry System was the most widely used device (n = 53). Fourteen additional commercially available devices were presented., Conclusions: Measurements collected by impact monitors provided real-time data to estimate player exposure but did not have the requisite sensitivity to concussion. Proper interpretation of previously reported head-impact kinematics across age, sport, and position may inform future research and enable staff clinicians working on the sidelines to monitor athletes. However, head-impact-monitoring systems have limited clinical utility due to error rates, designs, and low specificity in predicting concussive injury.

OBJECTIVE Although 70% of football players in the United States are youth players (6-14 years old), most research on head impacts in football has focused on high school, collegiate, or professional populations. The objective of this study was to identify the specific activities associated with high-magnitude (acceleration > 40g) head impacts in youth football practices. METHODS A total of 34 players (mean age 9.9 ± 0.6 years) on 2 youth teams were equipped with helmet-mounted accelerometer arrays that recorded head accelerations associated with impacts in practices and games. Videos of practices and games were used to verify all head impacts and identify specific drills associated with each head impact. RESULTS A total of 6813 impacts were recorded, of which 408 had accelerations exceeding 40g (6.0%). For each type of practice drill, impact rates were computed that accounted for the length of time that teams spent on each drill. The tackling drill King of the Circle had the highest impact rate (95% CI 25.6-68.3 impacts/hr). Impact rates for tackling drills (those conducted without a blocker [95% CI 14.7-21.9 impacts/hr] and those with a blocker [95% CI 10.5-23.1 impacts/hr]) did not differ from game impact rates (95% CI 14.2-21.6 impacts/hr). Tackling drills were observed to have a greater proportion (between 40% and 50%) of impacts exceeding 60g than games (25%). The teams in this study participated in tackling or blocking drills for only 22% of their overall practice times, but these drills were responsible for 86% of all practice impacts exceeding 40g. CONCLUSIONS In youth football, high-magnitude impacts occur more often in practices than games, and some practice drills are associated with higher impact rates and accelerations than others. To mitigate high-magnitude head impact exposure in youth football, practices should be modified to decrease the time spent in drills with high impact rates, potentially eliminating a drill such as King of the Circle altogether., Competing Interests: The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Computerized neuropsychological testing has become an important tool in the identification and management of sports-related concussions; however, the psychometric effect of repeat testing has not been studied extensively beyond test-retest statistics. The current study analyzed data from Division I collegiate athletes who completed Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) baseline assessments at four sequential time points that varied over the course of their athletic careers. Administrations were part of a larger National Institutes of Health (NIH) study. Growth curve modeling showed that the two memory composite scores increased significantly with successive administrations: Change in Verbal Memory was best represented with a quadratic model, while a linear model best fit Visual Memory. Visual Motor Speed and Reaction Time composites showed no significant linear or quadratic growth. The results demonstrate the effect of repeated test administrations for memory composite scores, while speed composites were not significantly impacted by repeat testing. Acceptable test-retest reliability was demonstrated for all four composites as well.

Concussions can occur in any sport. Often, clinical and biomechanical research efforts are disconnected. This review paper analyzes current concussion issues in sports from a biomechanical perspective and is geared toward Sports Med professionals. Overarching themes of this review include the biomechanics of the brain during head impact, role of protective equipment, potential population-based differences in concussion tolerance, potential intervention strategies to reduce the incidence of injury, and common biomechanical misconceptions.

Depression during pregnancy has been linked to in utero stress and is associated with long-lasting symptoms in offspring, including anxiety, helplessness, attentional deficits, and social withdrawal. Depression is diagnosed in 10-20% of expectant mothers, but the impact of antidepressant treatment on offspring development is not well documented, particularly for females. Here, we used a prenatal stress model of maternal depression to test the hypothesis that in utero antidepressant treatment could mitigate the effects of prenatal stress. We also investigated the effects of prenatal stress and antidepressant treatment on gene expression related to GABAergic and serotonergic neurotransmission in the amygdala, which may underlie behavioral effects of prenatal stress. Nulliparous female rats were implanted with osmotic minipumps delivering clinically-relevant concentrations of escitalopram and mated. Pregnant dams were exposed to 12 days of mixed-modality stressors, and offspring were behaviorally assessed in adolescence (postnatal day 28) and adulthood (beyond day 90) to determine the extent of behavioral change. We found that in utero stress exposure, regardless of escitalopram treatment, increased anxiety-like behavior in adolescent females and profoundly influenced amygdala expression of the chloride transporters KCC2 and NKCC1, which regulate GABAergic function. In contrast, prenatal escitalopram exposure alone elevated amygdala expression of 5-HT1A receptors. In adulthood, anxiety-like behavior returned to baseline and gene expression effects in the amygdala abated, whereas deficits emerged in novel object recognition for rats exposed to stress during gestation. These findings suggest prenatal stress causes age-dependent deficits in anxiety-like behavior and amygdala function in female offspring, regardless of antidepressant exposure., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Optimizing the protective capabilities of helmets is one of several methods of reducing brain injury risk in sports. This paper presents the experimental and analytical development of a hockey helmet evaluation methodology. The Summation of Tests for the Analysis of Risk (STAR) formula combines head impact exposure with brain injury probability over the broad range of 227 head impacts that a hockey player is likely to experience during one season. These impact exposure data are mapped to laboratory testing parameters using a series of 12 impact conditions comprised of three energy levels and four head impact locations, which include centric and non-centric directions of force. Injury risk is determined using a multivariate injury risk function that incorporates both linear and rotational head acceleration measurements. All testing parameters are presented along with exemplar helmet test data. The Hockey STAR methodology provides a scientific framework for manufacturers to optimize hockey helmet design for injury risk reduction, as well as providing consumers with a meaningful metric to assess the relative performance of hockey helmets.