Demographic and social determinants of mortality in cerebral arteriovenous malformations: identifying high-risk...

Health disparities in cerebral arteriovenous malformations (AVMs) arise from multifaceted factors, influencing clinical outcomes. This study models these disparities and explores their association with AVM-related mortality. Using the National Inpatient Sample (2016-2020), we identified cerebral AVM cases via ICD-10 codes. Multivariable, and ridge logistic regressions assessed mortality risk and length of stay. Risk clusters were identified by performing a factor analysis for mixed data (FAMD), followed by K-means clustering. Clusters memberships were associated with mortality and length of stay using logistic regression, adjusted for AVM rupture, treatment, and hospital characteristics. Among 11,755 patients, 2.9% (344) died during hospitalization. Logistic regression showed that residing in non-micropolitan counties (OR 1.71, 95% CI 1.03-2.84) and older age (OR 1.01, 95% CI 1.01-1.02 per year) increased mortality risk. Ridge regression identified higher income (76th-100th percentile: OR 0.79, 95% CI 0.74-0.84) and fringe metropolitan residency (OR 0.94, 95% CI 0.87-0.99) as protective, while self-pay status elevated mortality (OR 1.32, 95% CI 1.26-1.37). Clustering revealed three groups (high, medium and low risk of death); being the high-risk group defined as older, predominantly female White Medicare users (median age 70), had the highest mortality risk (OR 2.12, 95% CI 1.63-2.76) compared to the medium risk group. This study highlights the role of social determinants in shaping disparities in AVM outcomes. By modeling disparities in a non-linear way, we identified high-risk patient clusters, particularly older White females on Medicare residing in central metropolitan areas, who face the greatest mortality risk.