A-30 Symptom Count Versus Symptom Severity: Which is a Better Predictor of Time to Recovery?

Abstract

Abstract Objective Evaluation of self-reported symptoms is a key component of concussion management. This study examined whether symptom count, a more parsimonious method to gather symptom information, would predict recovery better than symptom severity. Method Participants were 1267 (39.3% female) adolescents ages 10–18 (M = 14.7, SD = 1.8) who were evaluated and diagnosed with a concussion by a physician within 10 days of injury. At their initial visit, participants completed the ImPACT computerized test and the included post-concussion symptom scale. The primary outcome was number of weeks (M = 3.2, SD = 1.8) until participants were cleared to return to play by the treating physician based on a standardized protocol. Results Symptom count and symptom severity were highly correlated (r = .89, p < .001). When examined in separate linear regression models, both symptom count (β = .28, p < .001) and symptom severity (β = .25, p < .001) predicted weeks until return to play after controlling for age, gender, prior history of concussion, and neurocognitive test performance. However, when symptom count and severity were both included in the same regression model, symptom count continued to predict weeks to recovery (β = .31, p < .001) and the effect of symptom severity was reduced to non-significance (β = −.03, p = .64). Conclusions Symptom count at initial clinic visit predicted recovery time, eliminating the predictive power of symptom severity when both were entered in the same regression model. Thus, symptom count may be a more robust and more parsimonious assessment than traditional severity ratings, which may save clinic time and allow for additional multimodal assessments.