Characterizing the Network Structure of Post-Concussion Symptoms

Abstract

Objective Assessment of post-concussion symptoms is implemented at secondary, post-secondary, and professional levels of athletics. Network theory suggests that disorders can be viewed as a set of interacting symptoms that amplify, reinforce, and maintain one another. Examining the network structure of post-concussion symptoms may provide new insights into symptom comorbidity and may inform targeted treatment. We used network analysis to examine the topology of post-concussion symptoms using the Post-Concussion Symptom Scale (PCSS) in high school athletes with recent suspected sport-related concussion. Method Using a cross-sectional design, the network was estimated from Post Concussion Symptom Scale scores from 3,292 high school athletes, where nodes represented symptoms and edges represented the association between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. Results The network consisted of edges within and across symptom domains. “Difficulty concentrating” and “dizziness” were the most central symptoms in the network. Although not highly central in the network, headaches were the highest rated symptom. Conclusions The interconnectedness among symptoms supports the notion that post-concussion symptoms are interrelated and mutually reinforcing. Given their central role in the network, “difficulty concentrating” and “dizziness” are expected to affect the activation and persistence of other post-concussion symptoms. Interventions targeting difficulties with concentration and dizziness may help alleviate other symptoms. Our findings could inform the development of targeted treatment with the aim of reducing overall symptom burden. Future research should examine the trajectory of post-concussion symptom networks to advance the clinical understanding of post-concussive recovery.

Network Analysis of Neuropsychiatric Symptoms in Alzheimer’s Disease

“…37 Network analysis has been used to characterize symptom presentation and progression in schizophrenia, 38 depression, anxiety, 39 post-traumatic stress disorder, 40 and sport-related concussion. [41][42][43] A network perspective may be equally illuminating for characterizing neuropsychiatric symptoms in AD. Network analysis could provide unique insights into symptom maintenance and progression and identify central symptoms that may be e cient targets for widespread symptom reduction.…”