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Background: Understanding movement variability is important to guide biomechanical assessment. Variability may change with age, and more repetitions of a movement need to be assessed when variability is high., Research Question: This study quantified the trial-to-trial (within subject) variability of three tasks commonly assessed during sports biomechanical testing: vertical drop jump, heel touch (single leg squat from step), and single leg hop. We hypothesized that pre-teen athletes would exhibit greater variability than more mature teenage athletes when performing all of these movements., Methods: Fifty-five uninjured pediatric athletes ages 7-15 years performed 3 repetitions of vertical drop jump, heel touch, and single leg hop for distance tasks during 3D motion analysis testing. Trial-to-trial variability was assessed using the standard deviation (SD) and range (maximum-minimum) of clinically relevant kinematic and kinetic metrics among the multiple repetitions of each task performed by each participant. Variability was compared between age groups using 2-sided t-tests. Standard error of measurement (SEM) and minimum detectable difference (MDD) were also calculated for each variable of interest., Results: For drop jump and heel touch, kinetic variability was similar between groups, but the younger group had greater kinematic variability. However, the older group was much more variable than the younger group during single leg hop landing, particularly in terms of kinetics and sagittal plane kinematics. Overall, kinematic variability had a median within-subject SD of 1-9°, median range of 2-17°, and 95th percentile for range of >15-20° for many of the variables examined. MDD was >10° for many kinematic variables, >0.2 Nm/kg for all frontal plane moments, >0.4 Nm/kg for most sagittal plane moments, and >0.5 W/kg for most energy absorption variables., Significance: The high within-subject trial-to-trial variability in performing sports tasks suggests that multiple trials should be analyzed for a more complete and representative evaluation., Competing Interests: Declaration of Competing Interest This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: The need for medical care for student athletes is mounting, as participation in high school athletics is continuing to rise. This study assessed medical care available to high school student athletes in a large, urban school district in California that has not been studied since 2002. By surveying athletic directors and coaches, we expected to find inadequate availability of medical care in the studied district and predicted that care would be more widely available for student athletes at larger high schools., Methods: We developed and validated a questionnaire assessing practice and game coverage, emergency preparedness, treatment, and injury prevention measures. The survey was administered to athletic directors and coaches at a school district athletic directors' meeting., Results: Forty-three (57%) of 75 distributed surveys were completed. We found that 70% of schools did not staff a healthcare provider for practices, 28% did not staff home games, and 30% did not staff away games, for any sports. We found no significant differences between school sizes with respect to physician referrals after a student was injured, provision of health education, or implementation of emergency action plans., Conclusions: Although these data do not support our hypothesis of larger schools providing better medical care, it suggests that there are multiple areas of inadequate healthcare regardless of school size. We identified numerous gaps; thus, future work will examine the impact of these gaps., (Copyright © 2015. Published by Elsevier Inc.)

Background: A validated clinical risk tool has been developed to identify pediatric and adolescent patients at risk of developing persisting symptoms after concussion, but has not been prospectively investigated within a sample of athletes seen after concussion by primary care sports medicine physicians and/or athletic trainers. Purpose: To determine whether a validated clinical risk prediction tool for persistent postconcussive symptoms (PPCSs) predicted which patients would develop PPCSs when obtained within 14 days of concussion among a multicenter sample of adolescent athletes. Study Design: Cohort study; Level of evidence, 2. Methods: Pediatric and adolescent patients (8-18 years of age) from 7 pediatric medical centers and 6 secondary school athletic training facilities who were diagnosed with a concussion and presented ≤14 days after concussion were enrolled as part of the Sport Concussion Outcomes in Pediatrics (SCOPE) study during their initial visit and were followed until symptom resolution. Clinical risk scores (Predicting and Preventing Post-concussive Problems in Pediatrics [5P]) and total symptom severity were obtained using the Post-Concussion Symptom Inventory at the initial visit (mean, 4.9 ± 2.9 days after concussion). Participants were then compared based on symptom resolution time: PPCS group (≥28 days to symptom resolution) and no-PPCS group (<28 days). The authors assessed the odds of developing PPCSs based on the 5P risk score using a binary logistic regression model and the utility of the clinical risk prediction tool to identify total time to symptom resolution using a Cox proportional hazards model. Results: A total of 184 participants enrolled, underwent initial evaluation, and were followed until symptom resolution (mean age, 15.2 ± 2.1 years; 35% female). The mean time to symptom resolution across the entire sample was 17.6 ± 3.7 days; 16% (n = 30) of participants developed PPCS. Those in the PPCS group had significantly greater mean initial total 5P risk scores than those in the no-PPCS group (7.9 ± 1.7 vs 5.9 ± 2.3, respectively; P <.001). After adjustment for initial symptom severity, time to assessment, and assessment setting, a higher initial total 5P risk score was associated with a significantly greater odds of developing PPCSs (adjusted odds ratio, 1.49; 95% CI, 1.07-2.08; P =.019). Furthermore, a higher 5P risk score was significantly associated with longer total symptom resolution time (hazard ratio, 0.80; 95% CI, 0.74-0.88; P <.001). Conclusion: In a multicenter sample of youth athletes seen in different outpatient health care settings, the 5P risk score accurately predicted which athletes may be at risk for developing PPCSs. [ABSTRACT FROM AUTHOR]

Background: Persistent postconcussive symptoms (PPCS) can negatively impact quality of life, school, and return to sport. The Predicting and Preventing Postconcussive Problems in Pediatrics [5P] clinical risk score has been validated in the Emergency Department setting to predict pediatric patients at risk of PPCS using 9 variables. Hypothesis/Purpose: To determine if the 5P risk score, obtained within 14 days of concussion, predicts which athletes seen in an athletic training or pediatric sports medicine clinic setting develop PPCS in a multi-center sample. Methods: Data were prospectively collected from participants enrolled in the Sport Concussion Outcomes in Pediatrics (SCOPE) study between September 2018-May 2021 across seven sites. Participants aged 6-18 years diagnosed with a concussion who presented within 14 days of injury were included. Demographics, medical history, and the Postconcussion Symptom Inventory (PCSI) were reviewed to calculate the 5P risk score. 5P risk scores were stratified as low (0-3 points), medium (4-8 points), and high risk (9-12 points). Participants were grouped based on symptom resolution time: PPCS (≥28 days) and no PPCS (<28 days). We compared total symptom resolution time among the 5P risk categories using one-way ANOVA and assessed the odds of developing PPCS based on 5P risk score using a binary logistic regression model. Results: We included 117 participants: 23 with PPCS (19.7%). A higher proportion of the PPCS group were female, were seen in a sports medicine clinic setting, and had a longer time to initial presentation (Table 1). Both PCSI symptom severity and 5P risk score were significantly higher in the PPCS group compared to the no PPCS group (p<0.001). Participants with high risk 5P scores had a significantly longer mean symptom resolution time compared to those with low risk scores (Figure 1; 28.4±18.2 vs 7.1±6.8 days, p=0.009). After adjusting for potential confounding variables of initial symptom severity, time to presentation, and assessment setting, each point increase on the 5P risk score was associated with a 1.7x odds of developing PPCS (odds ratio=1.66; 95% CI=1.13, 2.41; p=0.009). Conclusion: In a multi-center sample of youth athletes, the 5P risk score accurately predicted which athletes were at risk for developing PPCS. The odds of developing PPCS increases with each point increase on the risk score. The 5P risk score can help clinicians identify which athletes are likely to develop PPCS, which may aid in educating families on expectations of recovery and/or provide opportunities for targeted intervention to facilitate sooner recovery. Table 1. 5 P Variables and other Patient Characteristics Comparing PPCS and no PPCS groups Figure 1. Symptom resolution time among the three 5P risk categories (Low : n=15; Medium : n=80; High : n=25; p=0.009) [ABSTRACT FROM AUTHOR]

This study compared three-dimensional (3-D) hip and knee kinematics and kinetics between lateral shuffle and side-step cutting movements to determine whether the simpler lateral shuffle movement can be used in place of cutting to assess knee injury risk. A total of 78 patients (52 female) and 34 controls (16 female) aged 8-19 years performed lateral shuffle and 45° side-step cutting movements. Hip and knee kinematics and kinetics between initial contact and peak knee flexion were calculated using the Plug-in-Gait model and compared between activities using Pearson's correlation and paired t-tests. Peak knee valgus angle correlated strongly (r=0.86, p<0.0001), while minimum (r=0.25, p=0.0001) and peak hip abduction (r=0.24, p=0.0003), and peak hip internal rotation (r=0.33, p<0.0001) correlated only weakly between the two activities. Peak external knee valgus moment (r=0.32, p<0.0001) and average external knee (r=0.42, p<0.0001) and hip (r=0.37, p<0.0001) flexion moments correlated weakly to moderately between activities. Subjects were more internally rotated (3.6°, p<0.0001) and less abducted (16.7° and 17.3° for minimum and maximum, p<0.0001) at the hip during cutting, with higher hip (0.12, p<0.0001) and lower knee (-0.02, p=0.0001) non-dimensional flexion moments. These results suggest that the lateral shuffle movement may be useful for evaluating knee valgus, particularly during initial visual assessment. However, the lateral shuffle may not be challenging enough to reveal poor neuromuscular control over hip ab/adduction and rotation, necessitating follow-up assessment of cutting, ideally using 3-D motion analysis. [ABSTRACT FROM AUTHOR]