There are no scoring methods for optimal treatment of patients with aneurysmal subarachnoid hemorrhage (aSAH). We developed a scoring model to predict clinical outcomes according to aSAH risk factors using data from the Japan Stroke Data Bank (JSDB). Of 5344 patients initially registered in the JSDB, 3547 met the inclusion criteria. Patients had been diagnosed with aSAH and treated with surgical clipping or endovascular coiling between 1998 and 2013. We performed multivariate logistic regression for poor outcomes at discharge, indicated by a modified Rankin Scale (mRS) score >2, and in-hospital mortality for both treatment methods. Based on each risk factor, we developed a scoring model assessing its validity using another dataset of our institution. In the surgical clipping group, scoring criteria for aSAH were age >72 years, history of more than once stroke, World Federation of Neurological Societies (WFNS) grades II-V, aneurysmal size >15 mm, and vertebrobasilar artery (VBA) aneurysm location. In the endovascular coiling group, scoring criteria were age >80 years, history of stroke, WFNS grades III-V, computed tomography (CT) Fisher group 4, and aneurysmal location in the middle cerebral artery (MCA) and anterior cerebral artery (ACA). The rates of poor outcome of mRS score >2 in an isolated dataset using these scoring criteria were significantly correlated with our model's scores, so this scoring model was validated. This scoring model can help in the more objective treatment selection in patients with aSAH.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905300PMC
http://dx.doi.org/10.2176/nmc.oa.2020-0262DOI Listing

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