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Background Concussion is a growing public health concern and generating concussion prevention programs depends on identifying high-risk sports and characteristics. Identifying the roles of sport, sex, and participation level (e.g., high school versus collegiate athletics) in concussion risk would facilitate more informed decision-making regarding sports participation and generate better targeted prevention strategies. Objectives The current study’s objectives were to: (1) determine the magnitude and hierarchy of sports-related concussion (SRC) risk across an array of events and (2) evaluate the modifying roles of sex, participation level, and session type on SRC rates. Methods A literature search was conducted on PubMed, searching concussion studies published between 2001 and December 2019. Inclusion criteria for studies required: (1) concussion occurred during sport, (2) that the SRC was clinically diagnosed, and (3) athlete exposures and concussions could be extracted or estimated. A study was excluded if it: (1) was not an original research article, (2) was not written in English language, (3) was an animal study, (4) did not have enough data to calculate SRC rates, (5) included professional or youth sample, and/or (6) contained data collected prior to 2001. The meta-analysis and meta-regression analyses were fit using a random effects model. Results Search results returned 2695 unique research articles, with 83 studies included in analyses. Sport, sex, participation level, and session type all significantly influenced SRC rates. Overall, rugby had the highest concussion rate and was classified as the highest risk sport (28.25 concussions per 10,000 athlete exposures). Overall, females had a higher concussion rate than males. Only lacrosse demonstrated a higher concussion rate for males compared to females. Collegiate athletes had higher concussion rates than high school athletes. Games were associated with 2.01 more concussions per 10,000 AEs than practices. Conclusions This meta-analysis demonstrated rugby has the highest concussion risk, followed by American Football, ice hockey, and wrestling. Concussion risk was influenced by sport, sex, participation, and session. Identifying the factors and environments that influence concussion risk can facilitate risk reduction and prevention strategies.

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. To assess available head-impact devices and their clinical utility. 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. Included studies were performed in vivo, used commercially available devices, and focused on sport-related concussion. 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. 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. 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.

This paper presents the Sport Concussion Assessment Tool 5th Edition (SCAT5), which is the most recent revision of a sport concussion evaluation tool for use by healthcare professionals in the acute evaluation of suspected concussion. The revision of the SCAT3 (first published in 2013) culminated in the SCAT5. The revision was based on a systematic review and synthesis of current research, public input and expert panel review as part of the 5th International Consensus Conference on Concussion in Sport held in Berlin in 2016. The SCAT5 is intended for use in those who are 13 years of age or older. The Child SCAT5 is a tool for those aged 5–12 years, which is discussed elsewhere.

ObjectivesTo evaluate prevention strategies, their unintended consequences and modifiable risk factors for sport-related concussion (SRC) and/or head impact risk.DesignThis systematic review and meta-analysis was registered on PROSPERO (CRD42019152982) and conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.Data sourcesEight databases (MEDLINE, CINAHL, APA PsycINFO, Cochrane (Systematic Review and Controlled Trails Registry), SPORTDiscus, EMBASE, ERIC0 were searched in October 2019 and updated in March 2022, and references searched from any identified systematic review.Eligibility criteriaStudy inclusion criteria were as follows: (1) original data human research studies, (2) investigated SRC or head impacts, (3) evaluated an SRC prevention intervention, unintended consequence or modifiable risk factor, (4) participants competing in any sport, (5) analytic study design, (6) systematic reviews and meta-analyses were included to identify original data manuscripts in reference search and (7) peer-reviewed. Exclusion criteria were as follows: (1) review articles, pre-experimental, ecological, case series or case studies and (2) not written in English.ResultsIn total, 220 studies were eligible for inclusion and 192 studies were included in the results based on methodological criteria as assessed through the Scottish Intercollegiate Guidelines Network high (‘++’) or acceptable (‘+’) quality. Evidence was available examining protective gear (eg, helmets, headgear, mouthguards) (n=39), policy and rule changes (n=38), training strategies (n=34), SRC management strategies (n=12), unintended consequences (n=5) and modifiable risk factors (n=64). Meta-analyses demonstrated a protective effect of mouthguards in collision sports (incidence rate ratio, IRR 0.74; 95% CI 0.64 to 0.89). Policy disallowing bodychecking in child and adolescent ice hockey was associated with a 58% lower concussion rate compared with bodychecking leagues (IRR 0.42; 95% CI 0.33 to 0.53), and evidence supports no unintended injury consequences of policy disallowing bodychecking. In American football, strategies limiting contact in practices were associated with a 64% lower practice-related concussion rate (IRR 0.36; 95% CI 0.16 to 0.80). Some evidence also supports up to 60% lower concussion rates with implementation of a neuromuscular training warm-up programme in rugby. More research examining potentially modifiable risk factors (eg, neck strength, optimal tackle technique) are needed to inform concussion prevention strategies.ConclusionsPolicy and rule modifications, personal protective equipment, and neuromuscular training strategies may help to prevent SRC.PROSPERO registration numberCRD42019152982.

To provide athletic trainers, physicians, and other health care professionals with best-practice guidelines for the management of sport-related concussions. An estimated 3.8 million concussions occur each year in the United States as a result of sport and physical activity. Athletic trainers are commonly the first medical providers available onsite to identify and evaluate these injuries. The recommendations for concussion management provided here are based on the most current research and divided into sections on education and prevention, documentation and legal aspects, evaluation and return to play, and other considerations.

In many US high schools, the athletic trainer (AT) has the responsibility to identify and manage athletes with concussions. Although the availability of ATs varies a great deal among schools, how the level of AT availability in high schools affects the reported incidence and management of sport-related concussions (SRCs) is unknown. To determine how the presence of an AT affects the reporting and management of SRCs. Prospective cohort study. A total of 2459 (female = 37.5%, age = 16.1 ± 1.2 years) athletes from 31 Wisconsin high schools were categorized as having low availability (LoAT), mid availability (MidAT), or high availability (HiAT) of ATs. Athletic trainers recorded the incidence, days lost from sport, and postconcussion management through return to sport. The incidence of SRC reporting among categories was examined using a multivariate Cox proportional hazards model. Fisher exact tests were used to determine if postconcussion management differed based on AT availability. The incidence of reported SRCs was lower for the LoAT schools (2.4%) compared with the MidAT (5.6%, hazard ratio = 2.59, P = .043) and HiAT (7.0%, hazard ratio = 3.33, P = .002) schools. The median time before the first AT interaction was longer for LoAT schools (24.0 hours) than for MidAT (0.5 hours, post hoc P = .012) and HiAT (0.2 hours, post hoc P = .023) schools. The number of post-SRC interactions was different in all groups (LoAT = 2 interactions, MidAT = 3, and HiAT = 4; all post hoc P values < .05). Days lost were greater for MidAT and HiAT (both 14 days lost) schools compared with LoAT schools (11.5 days lost, post hoc P = .231 and P = .029, respectively). Athletes at LoAT schools were less likely to undergo a return-to-play protocol (9/18 SRCs, 50.0%) than athletes at MidAT (44/47 SRCs, 93.6%; post hoc P = .001) or HiAT (64/64 SRCs, 100%; post hoc P < .001) schools. The level of AT availability positively influenced the reported incidence of SRCs as well as postconcussion management activities in this sample of high schools.

Researchers are striving to understand the biomechanics of concussive injury that occur in the context of sport by using a number of methodologies. Animal models, video reconstruction, and helmet-based accelerometers have all been used, but have their limitations. The Head Impact Telemetry (HIT) System permits the real-time in vivo tracking of all impacts that occur on the football field and has been used in both the high school and collegiate setting. This review provides a theoretical discussion of concussion mechanics and examines the current literature on the effects of the number of impacts, impact magnitude, impact distribution, and concussion threshold in high school and collegiate football athletes recorded by the HIT System.

The Concussion Recognition Tool 5 (CRT5) is the most recent revision of the Pocket Sport Concussion Assessment Tool 2 that was initially introduced by the Concussion in Sport Group in 2005. The CRT5 is designed to assist non-medically trained individuals to recognise the signs and symptoms of possible sport-related concussion and provides guidance for removing an athlete from play/sport and to seek medical attention. This paper presents the development of the CRT5 and highlights the differences between the CRT5 and prior versions of the instrument.

Epidemiologic research on sports-related concussion (SRC) has focused on individual risk factors, with limited research on institutional risk factors and variability in concussion rates. This study used data from 53,822 athletes-seasons collected at 30 United States sites (26 civilian institutions and 4 military service academies), from 2014/15 to 2018/19 academic years, by the Concussion Assessment, Research, and Education Consortium. School-level risk factors included competitive division (DI, DII, DIII), school type (military/civilian) and a Sport Risk Index (SRI; Low, Medium, High). For comparability between civilian institutions and military academies, only NCAA athletes and concussions in sports games and practices were included. Random intercepts log-binomial regression was used to estimate Risk Ratios (RRs) and model variability in SRC risk. A total of 2,503 SRCs were observed during the study period, including 829 competition SRCs (33%) and 1,674 practice SRCs (67%). Most variability in SRC risk was at the level of athlete or team (within-school), rather than at the school-level. Specifically, across the three SRC outcomes (all [competition and practice combined], competition-only, and practice-only), within-school variability was 5 to 7 times greater than between-school variability. Three school-level risk factors (Division, School Type, and SRI) accounted for over one-third (36%) of between-school variability. SRI was the strongest school-level predictor of SRC risk (RR = 5.7; 95%CI: 4.2, 7.6 for High vs. Low). SRC risk was higher for Division I compared to Divisions II/III (RR = 1.6; 95%CI: 0.9, 2.9 for DI vs. DIII), and military academies had a moderately elevated risk of SRC (RR = 1.4; 95%CI: 0.7, 2.7). A large portion of the apparent variability between schools was attributable to structural factors (sport risk and competitive level), suggesting that there were minimal systemic differences in concussion identification between schools. While most variability is within-school, understanding school-level determinants of concussion risk may still be important in providing the implementation science context for individual-level interventions.

Little is known about the impact biomechanics sustained by players during interscholastic football. To characterize the location and magnitude of impacts sustained by players during an interscholastic football season. Observational design. On the field. High school varsity football team (n = 35; age = 16.85 +/- 0.75 years, height = 183.49 +/- 5.31 cm, mass = 89.42 +/- 12.88 kg). Biomechanical variables (linear acceleration, rotational acceleration, jerk, force, impulse, and impact duration) related to head impacts were categorized by session type, player position, and helmet impact location. Differences in grouping variables were found for each impact descriptor. Impacts occurred more frequently and with greater intensity during games. Linear acceleration was greatest in defensive linemen and offensive skill players and when the impact occurred at the top of the helmet. The largest rotational acceleration occurred in defensive linemen and with impacts to the front of the helmet. Impacts with the highest-magnitude jerk, force, and impulse and shortest duration occurred in the offensive skill, defensive line, offensive line, and defensive skill players, respectively. Top-of-the-helmet impacts yielded the greatest magnitude for the same variables. We are the first to provide a biomechanical characterization of head impacts in an interscholastic football team across a season of play. The intensity of game play manifested with more frequent and intense impacts. The highest-magnitude variables were distributed across all player groups, but impacts to the top of the helmet yielded the highest values. These high school football athletes appeared to sustain greater accelerations after impact than their older counterparts did. How this finding relates to concussion occurrence has yet to be elucidated.