A study protocol for risk stratification in children with concussion (RSiCC): Theoretical framework, design, and methods

Abstract

Research shows that one in five children will experience a concussion by age 16. Compared to adults, children experience longer and more severe postconcussive symptoms (PCS), with severity and duration varying considerably among children and complicating management of these patients. Persistent PCS can result in increased school absenteeism, social isolation, and psychological distress. Although early PCS diagnosis and access to evidence-based interventions are strongly linked to positive health and academic outcomes, symptom severity and duration are not fully explained by acute post-injury symptoms. Prior research has focused on the role of neuroinflammation in mediating PCS and associated fatigue; however relationship between inflammatory biomarkers and PCS severity, has not examined longitudinally. To identify which children are at high risk for persistent PCS and poor health, academic, and social outcomes, research tracking PCS trajectories and describing school-based impacts across the entire first year postinjury is critically needed. This study will 1) define novel PCS trajectory typologies in a racially/ethnically diverse population of 500 children with concussion (11–17 years, near equal distribution by sex), 2) identify associations between these typologies and patterns of inflammatory biomarkers and genetic variants, 3) develop a risk stratification model to identify children at risk for persistent PCS; and 4) gain unique insights and describe PCS impact, including fatigue, on longer-term academic and social outcomes. We will be the first to use NIH’s symptom science model and patient-reported outcomes to explore the patterns of fatigue and other physical, cognitive, psychological, emotional and academic responses to concussion in children over a full year. Our model will enable clinicians and educators to identify children most at risk for poor long-term health, social, and academic outcomes after concussion. This work is critical to meeting our long-term goal of developing personalized concussion symptom-management strategies to improve outcomes and reduce disparities in the health and quality of life of children.