Poor-Grade Aneurysmal Subarachnoid Hemorrhage: Risk Factors Affecting Clinical Outcomes in Intracranial Aneurysm Patients in a Multi-Center Study.

Patients with poor-grade aneurysm subarachnoid hemorrhage (SAH) have commonly been considered to have a poor prognosis. The objective of this study was to investigate the independent risk factors affecting clinical outcomes in intracranial aneurysm patients with poor-grade aneurysm subarachnoid hemorrhage (aSAH) underwent different intervention therapies. A multicenter observational registry of 324 poor-grade aSAH patients treated at tertiary referral centers from October 2010 to March 2012 were enrolled in this study. The clinical data including patient characteristics on admission and during treatment course, treatment modality, aneurysm size and location, radiologic features, signs of cerebral herniation (dilated pupils), and functional neurologic outcome were collected. Clinical outcomes were assessed via a modified Rankin Scale at 12 months. Multivariate logistic regression models were used to develop prognostic models. The area under the receiver operator characteristic curves (AUC) and Hosmer-Lemeshow tests were used to assess discrimination and calibration. WAP score was developed to predict risk of poor outcome. Older age, female gender, ventilated breathing status, non-reactive pupil response, pupil dilation, lower GCS score, a WFNS grade of V, intraventricular hemorrhage, a higher Fisher grade, a higher modified Fisher grade, and conservative treatment were calculated to be associated with a relatively poor outcome. Multivariate analyses revealed that older age, lower Glasgow coma scale score (GCS), the absence of pupillary reactivity, higher modified Fisher grade, and conservative treatment were independent predictors of poor outcome, showed good discrimination and calibration. Patients with WFNS grade V, older age and non-reactive pupillary reactivity were predicted to have a poor outcome by WAP risk score. A simple WAP risk score had good discrimination and calibration in the prediction of outcome. The risk score can be easily measured and may complement treatment decision-making.