Injury Rates in Age-Only Versus Age-and-Weight Playing Standard Conditions in American Youth Football

BACKGROUND: American youth football leagues are typically structured using either age-only (AO) or age-and-weight (AW) playing standard conditions. These playing standard conditions group players by age in the former condition and by a combination of age and weight in the latter condition. However, no study has systematically compared injury risk between these 2 playing standards. PURPOSE: To compare injury rates between youth tackle football players in the AO and AW playing standard conditions. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Athletic trainers evaluated and recorded injuries at each practice and game during the 2012 and 2013 football seasons. Players (age, 5-14 years) were drawn from 13 recreational leagues across 6 states. The sample included 4092 athlete-seasons (AW, 2065; AO, 2027) from 210 teams (AW, 106; O, 104). Injury rate ratios (RRs) with 95% CIs were used to compare the playing standard conditions. Multivariate Poisson regression was used to estimate RRs adjusted for residual effects of age and clustering by team and league. There were 4 endpoints of interest: (1) any injury, (2) non-time loss (NTL) injuries only, (3) time loss (TL) injuries only, and (4) concussions only. RESULTS: Over 2 seasons, the cohort accumulated 1475 injuries and 142,536 athlete-exposures (AEs). The most common injuries were contusions (34.4%), ligament sprains (16.3%), concussions (9.6%), and muscle strains (7.8%). The overall injury rate for both playing standard conditions combined was 10.3 per 1000 AEs (95% CI, 9.8-10.9). The TL injury, NTL injury, and concussion rates in both playing standard conditions combined were 3.1, 7.2, and 1.0 per 1000 AEs, respectively. In multivariate Poisson regression models controlling for age, team, and league, no differences were found between playing standard conditions in the overall injury rate (RRoverall, 1.1; 95% CI, 0.4-2.6). Rates for the other 3 endpoints were also similar (RRNTL, 1.1 [95% CI, 0.4-3.0]; RRTL, 0.9 [95% CI, 0.4-1.9]; RRconcussion, 0.6 [95% CI, 0.3-1.4]). CONCLUSION: For the injury endpoints examined in this study, the injury rates were similar in the AO and AW playing standards. Future research should examine other policies, rules, and behavioral factors that may affect injury risk within youth football

The Interrelationship and Diagnostic Utility of Memory and Reaction Time in Concussed Students: 971 Board #232 May 30 3

More than 40 million American youth participate in interscholastic, community-based, and collegiate sports. A risk of participation is traumatic brain injury (TBI). In up to 40% of TBI cases, athletes experience persistent functional and cognitive deficits. It is important to understand the variables that lead to these deficits to improve diagnosis and prognostic management. PURPOSE: To evaluate memory and reaction time as markers of TBI severity among patients experiencing prolonged recovery. METHODS: We retrospectively analyzed student-athletes admitted to a Midwestern outpatient clinic for neuropsychological evaluation; 78 patients had relatively comprehensive profiles and were included in the analysis. We conducted a health history, a 22-item post-concussion symptom inventory, and the ImPACT computerized test, which evaluated memory and reaction time. Pearson’s and point-biserial correlation coefficients tested the direction and strength of association between memory, reaction time, and markers of injury severity. Logistic, negative binomial, and linear regressions tested memory and reaction time as predictors of whether symptoms were reported, the number of reported symptoms, and the severity of symptoms. RESULTS: Patients were 16.0 ± 2.6 years of age, 56.3% were male, and they had experienced 1.2 ± 1.5 previous concussions. Reaction time was 0.64 ± 0.13 seconds; visual motor speed score was 44.7 ± 34.6; visual memory score was 92.0 ± 69.3; verbal memory score was 98.0 ± 80.9; cognitive efficiency score was 0.34 ± 0.12. Reaction time was a significant predictor (p\u3c0.05) of balance problems, dizziness, mental fogginess, and sensitivity to light and noise; it was a trending predictor (p=0.061) of the summed severity of symptoms. Verbal memory was a significant predictor (p\u3c0.05) of balance problems, sleeping problems, and fatigue. Visual memory, visual motor speed, and cognitive efficiency index were poor predictors of injury severity. CONCLUSIONS: Reaction time and memory are common components of testing batteries for concussed athletes. In our sample, reaction time and verbal memory emerged as useful predictors of severity among patients suffering long-term symptoms of TBI. It may be of value for coaches and athletic trainers to establish baseline values at the onset of a competitive season