The eSAH score: a simple practical predictive model for SAH mortality and outcomes - Rohan Sharma; Daniel Mandl; Fabian Föttinger; Saif D. Salman; Raja Godasi; Yujia Wei; Rabih G. Tawk; W. David Freeman (Scientific Reports)
Abstract We developed a simple quantifiable scoring system that predicts aneurysmal subarachnoid hemorrhage (aSAH) mortality, delayed cerebral ischemia (DCI), and modified Rankin scale (mRS) outcomes using readily available SAH admission data with SAH volume (SAHV) measured on computed tomography (CT). We retrospectively analyzed a cohort of 277 patients with aSAH admitted at our Comprehensive Stroke Center at Mayo Clinic in Jacksonville, Florida, between January 5, 2012, and February 24, 2022. We developed a mathematical radiographic model SAHV that measures basal cisternal SAH blood volume using a derivation of the ABC/2 ellipsoid formula (A = width/thickness, B = length, C = vertical extension) on noncontrast CT, which we previously demonstrated is comparable to pixel-based manual segmentation on noncontrast CT. Data were analyzed using t test, χ2 test, receiver operator characteristics curve, and area under the curve (AUC) analysis. Multivariate logistic regression analysis with stepwise elimination of variables not contributing to the model (0.05 significance level for entry into the model) was used to develop an enhanced SAH (eSAH) scoring system. Using multivariate logistic regression, we found that age, Glasgow Coma Scale score, and SAHV were significantly associated with mRS outcomes at discharge, in-hospital DCI, and in-hospital mortality. Using these factors, we developed a weighted eSAH score, ranging from 0 to 5, that was strongly predictive of mRS outcomes (AUC = 0.89), DCI (AUC = 0.75), and in-hospital mortality (AUC = 0.88). Our proposed eSAH score, a simple quantitative model based on SAHV, Glasgow Coma Scale score, and age, appears to predict mortality and outcomes in patients with aSAH. A larger cohort validation study is planned.