Early Prediction of Delayed Cerebral Ischemia After Subarachnoid Hemorrhage

Abstract

BACKGROUND AND PURPOSE To develop and validate a risk chart for prediction of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage based on admission characteristics. METHODS For derivation of the risk chart, we studied data from 371 prospectively collected consecutive subarachnoid hemorrhage patients with a confirmed aneurysm admitted between 1999 and 2007. For its validation we similarly studied 255 patients admitted between 2007 and 2009. The predictive value of admission characteristics was tested in logistic regression models with delayed cerebral ischemia-related infarction as primary outcome. Procedure-related infarctions were not included. Performance of the models was tested by discrimination and calibration. On the basis of these models, a risk chart was developed for application in clinical practice. RESULTS The strongest predictors were clinical condition on admission, amount of blood on computed tomography (both cisternal and intraventricular) and age. A model that combined these 4 predictors had an area under the receiver operating characteristic curve of 0.63 (95% confidence interval, 0.57-0.69). This model improved little by including current smoking and hyperglycemia on admission (area under the receiver operating characteristic curve, 0.65; 95% confidence interval, 0.59-0.71). The risk chart predicted risks of delayed cerebral ischemia-related infarction varying from 12% to 61%. Both low risk (<20% risk) and high risk (>40% risk) were predicted in ≈20% of the patients. Validation confirmed that the discriminative ability was adequate (area under the receiver operating characteristic curve, 0.69; 95% confidence interval, 0.61-0.77). CONCLUSIONS Absolute risks of delayed cerebral ischemia-related infarction can be reliably estimated by a simple risk chart that includes clinical condition on admission, amount of blood on computed tomography (both cisternal and intraventricular), and age.