BACKGROUND: Prompt hospital arrival is critical for acute ischemic stroke (AIS) treatment. This study aimed to examine the association between social network structure and prehospital delay among patients with AIS in China. METHODS: A cross-sectional survey using a validated instrument was conducted among patients with AIS admitted to 2 general hospitals in Qingdao, China, between October 2020 and May 2021. Key inclusion criteria were confirmed AIS diagnosis, age ≥18 years, and ability to complete the survey. Exclusion criteria included severe cognitive impairment or aphasia. We assessed 5 social network characteristics using egocentric network methodology: effective network size (number of nonredundant contacts), kin proportion (percentage of relatives), betweenness centrality (role as a bridge in the network), network constraint (limitations in forming new connections), and network efficiency (ability to access resources through contacts). Prehospital delay was defined as a binary outcome (arrival to hospital >3 hours after symptom onset). Binary logistic regression was used to analyze associations between network features and delay, adjusting for clinical and demographic variables. RESULTS: Among 422 participants (mean age 65.0±11.7 years, 71.0% male), 270 (64.0%) experienced prehospital delay (>3 hours). Adjusted logistic regression revealed that while a larger effective network size (odds ratio OR, 0.39 95% CI, 0.24–0.64) and a higher kin proportion (OR, 0.21 95% CI, 0.05–0.78) were associated with reduced odds of delay, higher betweenness centrality (OR, 1.16 95% CI, 1.03–1.31), greater network constraint (OR, 1.02 95% CI, 1.00–1.03), and higher network efficiency (OR, 1.04 95% CI, 1.02–1.06) were associated with increased odds. CONCLUSIONS: Social network structure significantly influences prehospital delay in patients with AIS. Interventions focused on social network expansion and strengthening kin involvement may reduce delays and improve stroke outcomes.
Gao et al. (Fri,) studied this question.