ArticleSurgical neurology international2017
A proposed classification for assessing rupture risk in patients with intracranial arteriovenous malformations.
Article in Surgical neurology international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Risk of intracranial hemorrhage in brain arteriovenous malformations: a systematic review and meta-analysis.Journal of neurology · 2024Pooled it
- Grades of brain arteriovenous malformations and risk of hemorrhage and death.Annals of clinical and translational neurology · 2019Pooled it
- The angio-architectural features of brain arteriovenous malformations: is it possible to predict the probability of rupture?The neuroradiology journal · 2023Article
- Factors affecting the performance of brain arteriovenous malformation rupture prediction models.BMC medical informatics and decision making · 2021Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundWhether cerebral arteriovenous malformations (AVMs) should be treated remains an ongoing debate. Nevertheless, there is a need for predictive factors that assist in labelling lesions as low or high risk for future rupture. Our aim was to design a new classification that would consider hemodynamic and anatomic factors in the rapid assessment of rupture risk in patients with AVMs.
methodsThis was a retrospective study that included 639 patients with ruptured and unruptured AVMs. We proposed a new classification score (1-4 points) for AVM rupture risk using three factors: feeding artery mean velocity (Vm), nidus size, and type of venous drainage. We employed descriptive statistics and logistic regression analysis.
resultsA total of 639 patients with cerebral AVMs, 388 (60%) had unruptured AVMs and 251 (40%) had ruptured AVMs. Logistic regression analysis revealed a significant effect of Vm, nidus size, and venous drainage type in accounting for the variability of rupture odds (
conclusionThis classification is useful and easy to use, and it may allow for the individualisation of each cerebral AVM and the assessment of rupture risk based on a model of categorisation.
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