Kudos to Karin Reuter-Rice, associate professor, and her entire team for the submission of her NIH R01 resubmission application entitled: “Risk Stratification of Postconcussive Symptoms in Children to Promote Health Outcomes and Academic Performance." This proposal requests funding for a five-year period with a start date of September 1, 2021.
Concussions are occurring at an alarming rate among American schoolchildren, with one in five children experiencing a concussion by age 16. Concussion in children represents a major public health burden. More than one million children visit emergency departments each year for concussions; a 50% increase over the past decade with an estimated cost to the US health care system of $1 billion annually. Compared to adults, children experience longer and more severe postconcussive symptoms (PCS) with rates as high as 25% at one year after a concussion. PCS also results in increased school absenteeism, social isolation and psychological distress. Fatigue is an underexplored postconcussive symptom despite 73% of children reporting continuous fatigue after sustaining a concussion. When combined with PCS, continuous fatigue can result in adverse health outcomes and school performance, significantly decreasing the quality of life for children and their families. Preliminary evidence also suggests fatigue is a biological byproduct of pediatric concussions. The severity and duration of PCS vary considerably between children, complicating clinical care and return-to-learn and -play. There are no existing models to help clinicians and school professionals identify those children with concussion who are at high risk for persistent PCS and fatigue. This is important because positive health, social, and academic outcomes are strongly linked to early PCS diagnosis and access to evidence-based return to health and school interventions. Based on the personal and societal impact of pediatric concussion, there is a strong and unmet need for research focused on tracking fatigue and PCS symptom trajectories using patient reported outcomes (PROs) during the crucial first year after a concussion. Information from PROs could be used to develop a model to identify high-risk children and provide them with personalized symptom-management strategies soon after concussion diagnosis. To address this gap, this study will be the first to use the NIH Symptom Science Model as a framework to examine PCS and fatigue trajectories using NIH PROs during the first year after a concussion. Our longitudinal multi-center study will enroll 400 concussed children (11-17 years) and collect data at six time points over 1-year. Project goals include: 1) develop symptom-based groups using a novel symptom trajectory analytic approach; 2) collect saliva for biologic markers at six time points over the 1-year assessment; 3) symptom-based groups will then be combined with biologic markers, clinical, social, and psychologic factors to develop a PCS risk stratification model; and 4) explore if symptom-based groups can identify academic performance. This project will provide new evidence in biologically-defined patient types to personalize symptom-management. Ultimately, a postconcussive symptom risk model could influence future healthcare delivery and aid in reducing the substantial health and socioeconomic burden on children, families, schools, and healthcare systems.