Abstract

The management and outcome of cerebral venous thrombosis (CVT) may be different from that of arterial ischemic stroke (AIS). Clinically differentiating the 2 diseases on clinical grounds may be difficult. The main objective of this study was to identify predictors differentiating CVT from AIS in a large cohort of young Asian women, based on risk factors and investigations. Twelve centers in 8 Asian countries participated. Women aged 15-45 years were included if they had a diagnosis of first-ever symptomatic AIS or CVT confirmed by brain computed tomography scan or magnetic resonance imaging/magnetic resonance venography. Patients with head trauma, cerebral contusions, intracranial hemorrhage, and subarachnoid or subdural hemorrhage were excluded. Data, including demographic data, risk factor assessment, neuroimaging studies, blood tests, and cardiac studies, were collected by retrospective and then prospective chart review between January 2001 and July 2008. Outcome was based on the modified Rankin Scale (mRS) score at admission, discharge, and latest follow-up. A total of 958 patients (204 with CVT and 754 with AIS) were included in the study. Age under 36 years, anemia, pregnancy or postpartum state, and presence of hemorrhagic infarcts on computed tomography scan or magnetic resonance imaging were significant predictors of CVT on univariate analysis. Age over 36 years, diabetes, hypertension, dyslipidemia, recent myocardial infarction, electrocardiogram abnormalities, and blood glucose level >150 mg/dL were strong predictors of AIS. On multivariate analysis, postpartum state and hemorrhagic infarct were the strongest predictors of CVT (P < .001). Mortality was comparable in the 2 patient groups. Prognosis was significantly better for patients with CVT than for those with AIS (mRS score 0-2, 74% v 46%; P < .001). There was no difference in outcome between patients with obstetric and nonobstetric CVT. Our data indicate that in young Asian women, predictors of CVT differ from those for AIS. These findings could be useful in the early identification and diagnosis of patients with CVT.

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