title: [Statistical study on correlation between cerebral arteriovenous malformation and hemodynamic aneurysms].
abstract: OBJECTIVE
  to explore the characteristic factors of arteriovenous malformation (AVM) which have statistically significant correlation with hemodynamic aneurysms.
  
  
  METHODS
  from August 1999 to July 2009, the clinical and imaging indices of 363 consecutive patients with AVM were retrospectively reviewed and entirely statistically analyzed. There were 229 male patients and 137 female patients, the mean age at the time of presentation was 28 ± 13 years. By using SPSS 16.0 medical statistic software, the correlation were analyzed between hemodynamic aneurysms and 13 characteristic factors associated with AVM through the methods of unit-factor and multi-factor analysis. Finally, the risk of the correlative factors filtered were evaluated.
  
  
  RESULTS
  the crosstabs analysis of unit-factor strongly suggested that the following factors, including age, location (supertentorium, subtentorium), size, number of main feeding arteries, number of drainage veins, ectasis of drainage veins, contralateral supply, and supply by both anterior and posterior circulation, were correlated with hemodynamic aneurysms. And the results of regression analysis of multi-factors indicated the following factors, including age, number of main feeding arteries, and contralateral supply, were positively correlated with hemodynamic aneurysms and the number of drainage veins were negatively correlated with hemodynamic aneurysms.
  
  
  CONCLUSIONS
  the factors including age, number of main feeding arteries, number of drainage veins and contralateral supply, are highly correlated with hemodynamic aneurysms.
authors.affiliation: Department of Neurosurgery, the First People's Hospital of Lianyungang City, Xuzhou Medical College, Lianyungang 222002, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Sun
authors.forename: Ai-Min
authors.initials: AM
authors.lastname: Li
authors.forename: You-Xiang
authors.initials: YX
authors.lastname: Li
authors.forename: Jun
authors.initials: J
authors.lastname: Chen
authors.forename: Hui
authors.initials: H
authors.lastname: Shi
authors.forename: Yu-Hua
authors.initials: YH
authors.lastname: Jiang
authors.forename: Peng
authors.initials: P
authors.lastname: Jiang
authors.forename: Xian-Li
authors.initials: XL
authors.lastname: Lü
authors.forename: Lian
authors.initials: L
authors.lastname: Liu
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002648:Child; D005260:Female; D006801:Humans; D002532:Intracranial Aneurysm / Q000209:etiology*; D002538:Intracranial Arteriovenous Malformations / Q000150:complications*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D012189:Retrospective Studies; D055815:Young Adult