The eSAH Score: A Simple Practical Predictive Model for SAH Mortality & Outcomes

Abstract

AbstractBackgroundWe developed a simple quantifiable scoring system that predicts aneurysmal subarachnoid hemorrhage (aSAH) mortality, delayed cerebral ischemia (DCI) and modified Rankin Scale outcomes using readily available SAH admission clinical data with a new radiographic quantitative volumetric SAH method.MethodsWe analyzed 277 patients with aneurysmal SAH (aSAH) admitted at our Comprehensive Stroke Center (CSC) at Mayo Clinic Florida between 2012 and 2022. We developed a mathematical model that measures aSAH basal cisternal subarachnoid hemorrhage volume (SAHV) using a derivation of the ABC/2 ellipsoid formula, where A = width/thickness, B = length, C = vertical extension) on non-contrast CT (NCCT), which we previously demonstrated comparable to pixel based manual segmentation on NCCT scans. Data was analyzed using t-test, chi-square, receiver operator characteristics (ROC) curve, and area under curve 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.ResultsUsing regression and logistic regression, we found that age, GCS score and SAHV were significantly associated with final discharge outcome, prediction on in-hospital DCI, and in-hospital mortality. A weighted eSAH score was developed using these factors that ranged between ‘0-5’ and was strongly predictive of outcome (AUC=0.88), DCI (AUC=0.75) and in-hospital mortality (AUC=0.87).ConclusionsA volumetrically-enhanced SAH (eSAH) score is a simple quantitative model based on SAH volumetrics, GCS and age and appears to predict mortality and outcomes in SAH patients. A larger cohort validation study is planned.