Background: Following a concussion, approximately 15% of individuals experience persistent symptoms that can lead to functional deficits. However, underlying symptom-clusters that persist beyond 12 months have not been adequately characterized, and their relevance to functional deficits are unclear. The aim of this study was to characterize the underlying clusters of prolonged post-concussive symptoms lasting more than 12 months, and to investigate their association with functional impairments.
Methods: Although hierarchical clustering is ideally suited in evaluating subjective symptom severities, it has not been applied to the Rivermead Post-Concussion Questionnaire (RPQ). The RPQ and functional impairments questions were administered via a smartphone application to 445 individuals who self-reported prolonged post-concussive symptoms. Symptom-clusters were obtained using agglomerative hierarchical clustering, and their association with functional deficits were investigated with sensitivity analyses, and corrected for multiple comparisons.
Results: Five symptom-clusters were identified: headache-related, sensitivity to light and sound, cognitive, mood-related, and sleep-fatigue. Individuals with more severe RPQ symptoms were more likely to report functional deficits (p < 0.0001). Whereas the headache and sensitivity clusters were associated with at most one impairment, at-least-mild sleeping difficulties and fatigue were associated with four, and moderate-to-severe cognitive difficulties with five (all p < 0.01).
Conclusions: Symptom-clusters may be clinically useful for functional outcome stratification for targeted rehabilitation therapies. Further studies are required to replicate these findings in other cohorts and questionnaires, and to ascertain the effects of symptomatic intervention on functional outcomes.
Keywords: Post-concussion syndrome; Rivermead; factor analysis; machine learning; principal components analysis; traumatic brain injury.