Male Youth Ice Hockey Concussion Incidence in a USA Hockey Membership-Adjusted Population: A Peak in 2011 and the Impact of Major Rule Changes.

OBJECTIVE: To investigate the incidence of youth ice hockey-related concussions preceding and following the implementation of new body-checking and head contact rules by USA hockey in 2011. We hypothesized a decrease in concussions after the rule change. DESIGN: Retrospective analysis. SETTING: United States emergency department (ED) data queried in the National Electronic InjurySurveillance System (NEISS). PATIENTS: National Electronic Injury Surveillance System reported male youth (≤18 years) ice hockey concussion cases from January 1, 2002, to December 31, 2016. In total, 848 players were diagnosed with concussion, representing a national estimate of 17 374 cases. INDEPENDENT VARIABLES: Time, specifically years. MAIN OUTCOME MEASURES: Incidences and incidence rates (measured per 10 000 person-years) of male youth ice hockey concussions. Annual trends were analyzed using descriptive and linear or polynomial regression analysis. RESULTS: The national estimate of youth ice hockey-related concussions seen in US emergency departments (EDs) increased significantly from 656 in 2007 to 2042 in 2011 (P < 0.01). During the same period, their respective incidence increased significantly from 21.8 to 66.8 per 10 000, before dropping through 2016 (P < 0.05). After 2011, concussions decreased from 1965 in 2012 to 1292 in 2016 (P = 0.055). The gap in concussion incidence between the 11 to 12 and 13 to 14 divisions widened after 2011 (before 2011: 41 vs 49 per 10 000 person-years [P = 0.80]; after 2011: 45 and 89, respectively [P < 0.01]). CONCLUSIONS: US EDs experienced a significant increase in youth ice hockey concussion visits from 2007 to 2011. After the 2011 rule changes, concussion visits decreased significantly from 2012 to 2016.

Exposure to Head Impacts and Cognitive and Behavioral Outcomes in Youth Tackle Football Players Across 4 Seasons.

Importance: Repetitive head impacts have been posited to contribute to neurocognitive and behavioral difficulties in contact sport athletes. Objective: To identify associations between cognitive and behavioral outcomes and head impacts measured in youth tackle football players over 4 seasons of play. Design, Setting, and Participants: This prospective cohort study was conducted from July 2016 through January 2020, spanning 4 football seasons. The setting was a youth tackle football program and outpatient medical clinic. Players were recruited from 4 football teams composed of fifth and sixth graders, and all interested players who volunteered to participate were enrolled. Data analysis was performed from March 2020 to June 2021. Exposures: Impacts were measured using helmet-based sensors during practices and games throughout 4 consecutive seasons of play. Impacts were summed to yield cumulative head impact gravitational force equivalents per season. Main Outcomes and Measures: Ten cognitive and behavioral measures were completed before and after each football season. Results: There were 70 male participants aged 9 to 12 years (mean [SD] age, 10.6 [0.64] years), with 18 completing all 4 years of the study. At the post-season 1 time point, higher cumulative impacts were associated with lower self-reported symptom burden (ß = -0.6; 95% CI, -1.0 to -0.2; P = .004). After correcting for multiple comparisons, no other associations were found between impacts and outcome measures. At multiple times throughout the study, premorbid attention-deficit/hyperactivity disorder, anxiety, and depression were associated with worse cognitive or behavioral scores, whereas a premorbid headache disorder or history of concussion was less often associated with outcomes. Conclusions and Relevance: In this cohort of youth tackle football players, premorbid conditions, including attention-deficit/hyperactivity disorder, anxiety, and depression, were associated with cognitive and behavioral outcomes more often than cumulative impact.

Subconcussive Head Impacts and Neurocognitive Function Over 3 Seasons of Youth Football.

OBJECTIVE: To determine the association between repetitive subconcussive head impacts and neurobehavioral outcomes in youth tackle football players. METHODS: Using helmet-based sensors, we measured head impacts for 3 consecutive seasons of play in 29 male players age 9-11. Cumulative impact g's were calculated. Players completed a battery of outcome measures before and after each season, including neuropsychological testing, vestibular-ocular sensitivity, and self- and parent-reported measures of symptoms and attention-deficit hyperactivity disorder (ADHD). RESULTS: Average cumulative impact over 3 seasons was 13 900g. High-intensity hits predicted worse change for self-reported social adjustment (P = .001). Cumulative impact did not predict change in any of the outcome measures. History of ADHD, anxiety, and depression predicted worse change for self-reported symptoms and social adjustment, independent of head impacts. When players were stratified into 3 groups based on cumulative impact across all 3 seasons, differences in outcome measures existed prior to the start of the first season. These differences did not further increase over the course of the 3 seasons. CONCLUSION: Over 3 consecutive seasons of youth tackle football, we found no association between cumulative head impacts and neurobehavioral outcomes. Larger sample sizes and longer follow-up times would further assist in characterizing this relationship.

Proposal of a Functional Impairment Symptom Scale for Concussion.

Clinicians currently administer patient-reported symptom scales to quantify and track concussion symptoms. These scales are based on subjective ratings without reference to the degree of functional impairment caused by the symptoms. Our objective was to develop a concussion symptom scale based on functional impairment and compare it to a widely used concussion symptom checklist. We conducted a retrospective chart review evaluating 133 patients age 9-22 with an acute concussion who completed 2 symptom checklists at their initial visit-the Sport Concussion Assessment Tool (SCAT-3) symptom evaluation (22 symptoms, 0-6 scale) and the proposed Functional Impairment Scale (22 symptoms, 0-3 scale related to degree of functional impairment). Mean total symptom score was 27.2±22.9 for Sport Concussion Assessment Tool-3 and 14.7±11.9 for the Functional Impairment Scale. Pearson correlation between the scales was 0.98 (P < .001). Mean time from concussion to first visit was 6.9±6.2 days, and median clearance time after injury was 19 (95% CI 16-21) days. After adjusting for patient and injury characteristics, an increased score on each scale was associated with longer time to clearance (5-point increase in Sport Concussion Assessment Tool-3 hazard ratio 0.885, 95% CI 0.835-0.938, P < .001; 2.5-point increase in Functional Impairment Scale hazard ratio 0.851, 95% CI 0.802-0.902, P < .001). We propose a concussion symptom scale based on functional impairment that correlates strongly with the Sport Concussion Assessment Tool-3 scale, demonstrates a similar association with time to clearance, and may provide a more intuitive approach to monitoring how symptoms are affecting patients recovering from concussion. Future research should aim to validate this scale through a prospective longitudinal study.

Head Impact Burden Differs Between Seasons in Youth and High School US Football Players.

Retrospective estimates of head impact burden in contact sports are often used in studies assessing for correlation of head impact exposure with neurocognitive outcomes later in life. These estimations assume a consistent impact burden from year to year. We monitored head impacts in youth tackle football players in the 6th-8th grades and high school varsity players using helmet-based sensors during two consecutive seasons. Helmet-based pressure sensors were used to measure head impacts, and estimates of peak linear acceleration (g's) were then grouped and summed for cumulative impact. After each season, players estimated whether they experienced an average, below average, or above average head impact burden in relation to their teammates. Of the 98 players who participated, 54 played in both seasons and sustained a median of 102.5 impacts (2206 cumulative g's) in season 1 and 161 impacts (3682 cumulative g's) in season 2. Using pairwise comparisons, number of impacts and cumulative g's increased in the youth players from season 1 to season 2 (p = 0.0021 and p = 0.0018, respectively), but there was a trend towards a decrease in number of impacts and g's at the high school level. In an exploratory analysis, perceived cumulative head impact and measured cumulative g's weakly correlated (Pearson's correlation coefficient = 0.26 for season 1 and 0.02 for season 2). In conclusion, cumulative head impacts differ significantly from one season to the next, and players have difficulty estimating their cumulative head impacts in relation to their team mates, especially at the youth level. Retrospective estimations of head impact burden should account for this variability.

Neurocognitive Function and Head Impact Burden over Two Seasons of Youth Tackle Football.

This prospective cohort study sought to determine the association of repetitive sub-concussive head impacts with neurocognitive outcomes in youth tackle football players. The study sample included 166 youth tackle football players over two seasons: 70 primary school players ages 9-12 and 96 high school players ages 15-18. Helmet-based sensors recorded head impacts during practices and games, and impacts were summed to provide a cumulative measure of impact for each season. Participants also were stratified by "high intensity" and "low intensity" groups based on whether they sustained high or low g-force impacts. Participants completed assessments on a variety of neurologic, cognitive, and behavioral outcomes before and after each football season. In the subgroup of 55 players who participated in both seasons, the average combined cumulative impact for primary school and high school players was 7127 (standard deviation [SD] 4670) and 6558 (SD 4438) g-forces, respectively. Neither cumulative impact nor impact intensity predicted change scores from pre-season 1 to post-season 2 on any outcome measures. Instead, younger age group and history of attention deficit hyperactivity disorder (ADHD) predicted worse change scores on several cognitive measures and an ADHD symptom reporting scale. In the full 166-player cohort, a computerized test of processing speed declined over time, while the remaining 22 outcome measures either did not change or improved over time. Minimal changes were observed in neurocognitive outcomes associated with participation in youth tackle football over the course of two seasons, and there was no correlation with the number and severity of head impacts sustained over that time. However, longer prospective follow-up times will be beneficial.

Comparing the Acute Presentation of Sport-Related Concussion in the Pediatric and Adult Populations.

Despite growing research on concussion, there is minimal evidence comparing the acute presentation of concussion between pediatric and adult patients. This cross-sectional study compares injury characteristics, symptoms, and neurologic examination in sport-related concussion based on age. Patients presenting to an outpatient sports neurology clinic for initial assessment of concussion within 7 days of injury were divided into 2 groups, 18 and older (n = 28) and 17 and younger (n = 107). There were no significant differences between pediatric and adult patients in any score of the Sport Concussion Assessment Tool-3rd Edition symptom scale, neurologic examination category, pertinent elements of past medical history, or characteristics of the concussion. The pediatric group had higher average hours of sleep (8.1 ± 0.3 vs 7.1 ± 0.58; P = .03) and were less likely to wake refreshed (36.3% vs 65%; P = .02). The initial presentation of concussion within 7 days of injury will likely not differ by age, specifically 18 and older versus 17 and younger.

Clinical features and biomarkers of concussion and mild traumatic brain injury in pediatric patients.

There has been increasing awareness of the incidence and potential long-term consequences of mild traumatic brain injury (mTBI) in children and young adults. While parents, school systems, and athletic programs are clamoring for evidence-based guidelines, the field remains primitive in understanding the factors resulting in a spectrum of individual outcomes, most of which are complete, but some of which are not. In this article, we discuss the definition, epidemiology, clinical presentation, course, and outcomes of mTBI, with a focus on the pediatric population as the context for reviewing the mechanisms and pathophysiology mediating, and biomarkers reflective of, more significant concussion-induced brain injury. Our goal is to present a general overview of the features of mTBI in the pediatric population in order to provide a conceptual model for pediatricians and pediatric subspecialists. This model emphasizes the importance of establishing actionable, noninvasive biomarkers that are reflective of brain injury and that may identify those pediatric patients who can benefit from earlier and more aggressive interventions. We will focus on the specific features of mTBI in pediatric patients; although given the relative lack of research in the pediatric population, we will also extrapolate from research on adults.