• Jay F Yu, Andrew D Nicholson, Jeffrey Nelson, Matthew D Alexander, Stephanie H Tse, Steven W Hetts, J Claude Hemphill, Helen Kim, and Daniel L Cooke.
• 1 Department of Radiology and Biomedical Imaging, 8785 University of California, San Francisco , CA, USA.
• Interv Neuroradiol. 2018 Apr 1; 24 (2): 183-188.

AbstractBackground and purpose Despite evidence regarding risk factors for brain arteriovenous malformation (bAVM)-associated spontaneous intracranial hemorrhage (ICH), few data exist describing the spectrum of clinical outcomes that bAVM-associated ICH may manifest. This study aimed to identify the demographical, clinical, and bAVM anatomical variables associated with ICH volume and the presence of intraventricular hemorrhage (IVH) of ruptured bAVMs, two indicators of worse clinical outcome, to help better predict outcome for unruptured bAVMs. Methods Computed tomography images ( n = 169) of patients with ruptured bAVM in a prospectively maintained institutional database were retrospectively reviewed to calculate ICH volume and the presence or absence of IVH. Demographic, clinical, and bAVM characteristics information was summarized and analyzed with univariable and multivariable regression models to identify the associations of these features with ICH volume and the presence of IVH. Results Patient sex, exclusively deep venous drainage, and lobar location were associated with ICH volume in univariable analysis; exclusively deep venous drainage remained significant in multivariable analysis (PI = 0.33, 95% CI: 0.21-0.52, p < 0.001). Exclusively deep venous drainage, multiple feeding arteries, and venous stenosis were associated with IVH in univariable analysis; exclusively deep venous drainage (OR = 7.27, 95% CI: 1.94-27.29, p = 0.003) remained significant in multivariable analysis. Conclusions Variables associated with ICH volume and the presence of IVH in ruptured bAVMs were evaluated and identified. They impart information that may help predict the clinical outcome of unruptured bAVM, in turn aiding clinicians in treatment planning.

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