A Reanalysis of Predictors for the Risk of Hemorrhage in Brain Arteriovenous Malformation

作者:Huang, Zheng; Peng, Kang; Chen, Changqing; Zeng, Feiyue; Wang, Junyu; Chen, Fenghua*
来源:Journal of Stroke and Cerebrovascular Diseases, 2018, 27(8): 2082-2087.
DOI:10.1016/j.jstrokecerebrovasdis.2018.03.003

摘要

Background: Brain arteriovenous malformation (BAVM) is a congenital cerebral vascular disease that characterized with intracranial hemorrhage and epilepsy. It has some risk in current treatments including microsurgery, endovascular, and radiation therapy. Some patients with bAVMs may keep unruptured in their whole life. Whether it should be treated depends on the evaluation of the hemorrhage risk of bAVM. Although previous studies gave many significant predictors, we tried to find some new and more significant predictors in 173 patients with bAVMS by retrospective analysis. Methods: Except for previous predictors reported such as age, gender, epilepsy, location, aneurysm related with bAVM, volume of nidus, types of venous drainage, and the number of draining veins, we also collected time to peak (TTP) and sum of cross-sectional area of the feeding arteries and sum of cross-sectional area of the draining veins (Sigma SA/Sigma SV) data to proceed univariate and multivariate statistical analysis in 173 patients with bAVM. Results: The results of the statistical analysis show that gender, the location of bAVM nidus, and TTP are significant predictors of hemorrhage risk, but age, size, the number of draining veins, and types of venous drainage do not appear so significant. The value of predictors of bleeding risk including TTP was assessed by receiver operating characteristic curve and area under curve to be stronger. Conclusions: When TTP and Sigma SA/Sigma SV data were added, some previous important indicators such as age, size, the number of draining veins, and types of venous drainage appear less significant in predicting the hemorrhage risk of bAVM in statistics, but TTP, gender, and the location of bAVM nidus are significant; moreover, TTP is a predictor that needs to be emphasized.