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<p>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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年11月20日

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  • Niels Pacheco-Barrios,
  • Aryan Wadhwa,
  • Shashvat Purohit,
  • Alejandro Enriquez-Marulanda,
  • S. Farzad Maroufi,
  • Omar Alwakaa,
  • Felipe Ramírez-Velandia,
  • Emmanuel Mensah,
  • Justin H. Granstein,
  • Christopher S. Ogilvy

摘要

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.