A proposed classification for assessing rupture risk in patients with intracranial arteriovenous malformations

Felipe, Padilla-Vázquez; Zenteno, Marco; Balderrama, Jorge; Garma, Víctor Hugo Escobar-de la; Juan, Daniel San; Trenado, Carlos

doi:10.4103/sni.sni_273_17

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…The results from the present analysis indicates that the evaluated unruptured and untreated AVMs failed to show an association between the original grades of Spetzler–Martin scale and the occurrence of subsequent hemorrhagic stroke. Although not from a randomized sample, similar failure was reported by Padilla‐Vazquez et al . and Tasic et al …”

Section: Discussionsupporting

confidence: 82%

Grades of brain arteriovenous malformations and risk of hemorrhage and death

Stefani

Ribeiro

Mohr

2019

Ann Clin Transl Neurol

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Objective To assess the relationship of the grade of unruptured and untreated Brain Arteriovenous Malformations (AVMs), with the risk of subsequent stroke and death during follow‐up. Methods This prospective study was drawn from a cohort of adult patients with unruptured AVMs, who participated in the conservative treatment arm (medical management only for headache or seizures) of the randomized clinical trial of unruptured brain AVMs (ARUBA study). The grade of AVMs (Spetzler–Martin scale) was dichotomized into categories: AVMs of grades I and II were considered low grade; AVMs of grades III and IV were considered high grade. There were no grade V AVM patients in ARUBA. The primary outcome was symptomatic stroke (hemorrhagic or ischemic – documented by imaging) or death. Results The conservative treatment group had 123 patients (“as treated” analysis). 71 (57.7%) had lesions characterized for this analysis as low‐grade lesions and 52 (42.2%) as high grade. From the total of 10 (8.13%) primary outcomes, three occurred (4.22%) in low‐grade AVMs and seven (13.46%) in high‐grade AVMs (P = 0.0942). Interpretation Statistical analysis of the cohort of patients with unruptured and untreated AVMs from ARUBA study showed that the graduation categories (Spetzler–Martin grades) were not associated with the outcome of subsequent stroke or death.

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Section: Discussionsupporting

confidence: 82%

Grades of brain arteriovenous malformations and risk of hemorrhage and death

Stefani

Ribeiro

Mohr

2019

Ann Clin Transl Neurol

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“…16 In fact, none of the Spetzler and Martin (SM), 17 the Spetzler-Ponce, 18 the Lawton’s supplementary system, 19 the Buffalo, 20 and Toronto classifications and scores allow to predict the probability of bleeding for bAVMs. 21…”

Section: Introductionmentioning

confidence: 99%

“…16 In fact, none of the Spetzler and Martin (SM), 17 the Spetzler-Ponce, 18 the Lawton's supplementary system, 19 the Buffalo, 20 and Toronto classifications and scores allow to predict the probability of bleeding for bAVMs. 21 In this study, we aimed to identify the angio-architectural characteristics of brain AVMs associated with bleeding.…”

Section: Introductionmentioning

confidence: 99%

The angio-architectural features of brain arteriovenous malformations: is it possible to predict the probability of rupture?

et al. 2022

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Background Hemorrhage is the most devastating complication of brain arteriovenous malformations (bAVMs), and to date, there is still concern about the needing for treatment in case of unruptured and asymptomatic bAVM. In fact, the morbidity and mortality of treatments may exceed that of the AVM’s natural history. None of the classifications and scores for bAVM allows to predict the risk of bleeding. In this study, we aimed to identify the angio-architectural characteristics of brain AVMs associated with bleeding. Methods We retrospectively evaluated all consecutive patients diagnosed with cerebral AVMs, between January 2010 and December 2019 from our prospective bAVM database. Univariate and multivariate logistic regression analysis were used to evaluate relationships between angio-architectural features of ruptured and unruptured bAVMs. Results Of the 143 retrieved bAVMs, 65 were unruptured and 78 were ruptured. The univariate logistic regression analysis demonstrated statistically significant differences into angio-architectural features of unruptured and ruptured bAVMs. The multivariate logistic regression analysis fitted well ( p =.113) with a good discrimination capacity (ROC = 0.83) of three independent angio-architectural features mainly related to bleeding in bAVMs: a smaller diameter of the nidus ( p < .001), the absence of venous drainage alterations ( p = .047), of the presence of prenidal aneurysms ( p = .005). Conclusions In our study, several features resulted related to an increased probability of rupture for bAVMs, among which the more relevant were a small diameter of the nidus, the absence of venous drainage alterations, and the presence of prenidal aneurysms.

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“…All these showed that predicting the hemorrhagic risk was important for unruptured bAVMs. Some studies proposed predictors for hemorrhagic risk, such as female sex, deep location, deep draining veins, single draining veins, and associated aneurysm [20][21][22][23]. Depending on these predictors, some authors tried to develop prediction models or scoring systems for the hemorrhagic risk of bAVM [6].…”

Section: Discussionmentioning

confidence: 99%

Factors affecting the performance of brain arteriovenous malformation rupture prediction models

Tao

Yan

Zeng

et al. 2021

BMC Med Inform Decis Mak

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Background In many cases, both the rupture rate of cerebral arteriovenous malformation (bAVM) in patients and the risk of endovascular or surgical treatment (when radiosurgery is not appropriate) are not low, it is important to assess the risk of rupture more cautiously before treatment. Based on the current high-risk predictors and clinical data, different sample sizes, sampling times and algorithms were used to build prediction models for the risk of hemorrhage in bAVM, and the accuracy and stability of the models were investigated. Our purpose was to remind researchers that there may be some pitfalls in developing similar prediction models. Methods The clinical data of 353 patients with bAVMs were collected. During the creation of prediction models for bAVM rupture, we changed the ratio of the training dataset to the test dataset, increased the number of sampling times, and built models for predicting bAVM rupture by the logistic regression (LR) algorithm and random forest (RF) algorithm. The area under the curve (AUC) was used to evaluate the predictive performances of those models. Results The performances of the prediction models built by both algorithms were not ideal (AUCs: 0.7 or less). The AUCs from the models built by the LR algorithm with different sample sizes were better than those built by the RF algorithm (0.70 vs 0.68, p < 0.001). The standard deviations (SDs) of the AUCs from both prediction models with different sample sizes displayed wide ranges (max range > 0.1). Conclusions Based on the current risk predictors, it may be difficult to build a stable and accurate prediction model for the hemorrhagic risk of bAVMs. Compared with sample size and algorithms, meaningful predictors are more important in establishing an accurate and stable prediction model.

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A proposed classification for assessing rupture risk in patients with intracranial arteriovenous malformations

Cited by 8 publications

References 37 publications

Grades of brain arteriovenous malformations and risk of hemorrhage and death

Grades of brain arteriovenous malformations and risk of hemorrhage and death

The angio-architectural features of brain arteriovenous malformations: is it possible to predict the probability of rupture?

Factors affecting the performance of brain arteriovenous malformation rupture prediction models

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