Untreated brain arteriovenous malformation: Patient-level meta-analysis of hemorrhage predictors
OBJECTIVE:To identify risk factors for intracranial hemorrhage in the natural history course of brain arteriovenous malformations (AVMs) using individual patient data meta-analysis of 4 existing cohorts. METHODS:We harmonized data from Kaiser Permanente of Northern California (n = 856), University o...
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Veröffentlicht in: | Neurology 2014-08, Vol.83 (7), p.590-597 |
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Zusammenfassung: | OBJECTIVE:To identify risk factors for intracranial hemorrhage in the natural history course of brain arteriovenous malformations (AVMs) using individual patient data meta-analysis of 4 existing cohorts.
METHODS:We harmonized data from Kaiser Permanente of Northern California (n = 856), University of California San Francisco (n = 787), Columbia University (n = 672), and the Scottish Intracranial Vascular Malformation Study (n = 210). We censored patients at first treatment, death, last visit, or 10-year follow-up, and performed stratified Cox regression analysis of time-to-hemorrhage after evaluating hemorrhagic presentation, sex, age at diagnosis, deep venous drainage, and AVM size as predictors. Multiple imputation was performed to assess impact of missing data.
RESULTS:A total of 141 hemorrhage events occurred during 6,074 patient-years of follow-up (annual rate of 2.3%, 95% confidence interval [CI] 2.0%–2.7%), higher for ruptured (4.8%, 3.9%–5.9%) than unruptured (1.3%, 1.0%–1.7%) AVMs at presentation. Hemorrhagic presentation (hazard ratio 3.86, 95% CI 2.42–6.14) and increasing age (1.34 per decade, 1.17–1.53) independently predicted hemorrhage and remained significant predictors in the imputed dataset. Female sex (1.49, 95% CI 0.96–2.30) and exclusively deep venous drainage (1.60, 0.95–2.68, p = 0.02 in imputed dataset) may be additional predictors. AVM size was not associated with intracerebral hemorrhage in multivariable models (p > 0.5).
CONCLUSION:This large, individual patient data meta-analysis identified hemorrhagic presentation and increasing age as independent predictors of hemorrhage during follow-up. Additional AVM cohort data may further improve precision of estimates, identify new risk factors, and allow validation of prediction models. |
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ISSN: | 0028-3878 1526-632X |
DOI: | 10.1212/WNL.0000000000000688 |