OBJECTIVE Currently, little is known about the biomechanics of head impact for concussion in youths (ages 5 to 18 years). Even less is known about the biomechanical characteristics and variables related to head impacts that may be useful in differentiating between transient and persistent postconcussion symptoms in a youth population. The purpose of this research was to examine the differences in biomechanics of youth head impact for transient postconcussion symptoms (TPCSs) and persistent postconcussion symptoms (PPCSs) by using data from a hospital population. METHODS In a laboratory setting and using physical, computational, and finite element models, the authors reconstructed falling events in a large cohort of patients who had sustained a brain injury that resulted in transient or persistent postconcussion symptoms. The falling events and resulting concussions for the TPCS and PPCS patient groups were analyzed in terms of force, energy, peak resultant linear and rotational accelerations, and maximum principal strain in the gray and white matter of the brain, as well as measurements of cumulative strain damage. RESULTS The results indicated that there were no significant differences between the groups for any of the variables analyzed. CONCLUSIONS With methods derived for use in an adult population, the magnitudes of peak linear acceleration for the youth data set were determined to be above the 50% risk of injury. The youth data set showed higher brain tissue strain responses for lower energy and impact velocities than measured in adults, suggesting that youths are at higher risk of concussive injury at lower event severities. A trend shown by some variables indicated that larger magnitudes of response were associated with PPCSs, but no single measurement variable consistently differentiated between the TPCS and PPCS groups. It is possible that using the biomechanics of head and brain responses to predict a subjective symptom load may not be appropriate. To enhance future biomechanical analyses, further investigations should include the use of quantifiable measures of brain injury linked to clinical outcomes and possible confounding factors such as history of brain injury and patient predisposition.
University College Dublin ->