A - 49 Predictors of Post-Concussion Anxiety In Patients without Pre-Existing Anxiety History

Abstract

Identify factors contributing to anxiety in individuals without a pre-existing anxiety history post-concussion. Patients (n = 264, aged 9–68) presented to a specialty concussion clinic post-concussion. They completed a clinical interview, Immediate Post-Concussion Assessment and Cognitive Test (ImPACT), Post-Concussion Symptom Scale (PCSS), Concussion Clinical Profile Screening (CP-Screen), and Vestibular/Ocular-Motor Screening (VOMS). Anxiety group was determined by a positive anxiety/mood clinical profile on CP-Screen. Independent samples t-tests and chi-square tests examined differences in demographics, medical history, and injury characteristics between groups. Univariate logistic regressions (LR) informed a follow-up forward stepwise LR to identify best predictors of post-concussion anxiety group. Receiver operating characteristic (ROC) analysis of the area under the curve (AUC) was used to identify which predictors retained from the LR model best-discriminated anxiety status. Statistical significance was set a priori at p < 0.05. Results of forward stepwise LR identifying factors contributing to post-concussion anxiety were significant (p < 0.001) and accounted for 19% of the variance. The model accurately classified 82.2% of patients, with non-Sport Related Concussion (SRC) (OR = 2.94, 95%CI, 1.45–1.5.98, p = 0.003), history of ADHD/LD (OR = 2.85, 95%CI, 1.21–6.71, p = 0.02), positive vestibular profile (OR = 2.14, 95%CI, 1.06–4.33, p = 0.03), and days to first clinic visit (OR = 1.01, 95%CI, 1.01–1.015, p = 0.003) as significant predictors. ROC analysis of the AUC of this 4-factor model discriminated post-concussion anxiety from no anxiety (AUC, 0.77, 95%CI, 0.71–0.85, p < 0.001). Findings suggest that non-SRC, ADHD/LD history, positive vestibular profile, and delayed clinic visit, may contribute to post-concussion anxiety among patients without prior anxiety history. These predictors may guide clinicians in tailoring interventions to optimize recovery outcomes.