Differentiating Reversible Cerebral Vasoconstriction Syndrome With Subarachnoid Hemorrhage From Other Causes Of Subarachnoid Hemorrhage
Tarih
2013Yazar
Muehlschlegel, Susanne
Kursun, Oğuzhan
Topçuoğlu, Mehmet A.
Fok, Joshua
Singhal, Aneesh B.
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IMPORTANCE Reversible cerebral vasoconstriction syndrome (RCVS) is a clinical-angiographic syndrome characterized by recurrent thunderclap headaches and reversible segmental multifocal cerebral artery narrowing. More than 30% of patients with RCVS develop subarachnoid hemorrhage (SAH). Patients with RCVS with SAH (RCVS-SAH) are often misdiagnosed as having potentially ominous conditions such as aneurysmal SAH (aSAH) or cryptogenic "angiogram-negative" SAH (cSAH) owing to overlapping clinical and imaging features. OBJECTIVE To identify predictors that can distinguish RCVS-SAH from aSAH and cSAH at the time of clinical presentation. DESIGN Retrospective analysis of 3 patient cohorts: patients with RCVS (1998-2009), patients with aSAH (1995-2003), and patients with cSAH (1995-2003). SETTING Academic hospital and tertiary referral center. PARTICIPANTS Consecutive patients with RCVS-SAH (n = 38), aSAH (n = 515), or cSAH (n = 93) whose conditions were diagnosed using standard criteria. MAIN OUTCOMES AND MEASURES Multivariate logistic regression analysis was used to identify predictors that differentiate RCVS-SAH from aSAH and cSAH. RESULTS Predictors differentiating RCVS-SAH from aSAH were younger age, chronic headache disorder, prior depression, prior chronic obstructive pulmonary disease, lower Hunt-Hess grade, lower Fisher SAH group, higher number of affected arteries, and the presence of bilateral arterial narrowing. Predictors differentiating RCVS-SAH from cSAH were younger age, female sex, prior hypertension, chronic headache disorder, lower Hunt-Hess grade, lower Fisher SAH group, and the presence of bilateral arterial narrowing. CONCLUSION AND RELEVANCE We identified important clinical and imaging differences between RCVS-SAH, aSAH, and cSAH that may be useful for improving diagnostic accuracy, clinical management, and resource utilization.