Reliable Identification of Benign Clinical Course in Aneurysmal Subarachnoid Hemorrhage: A Simple and Qualitative Algorithm

BACKGROUND: A reliable method to specifically identify low vasospasm risk in aneurysmal subarachnoid hemorrhage (aSAH) patients has not been previously proposed. OBJECTIVE: To develop a clinical algorithm using admission aSAH clinical severity and subarachnoid blood distribution to identify patients at low risk of clinical vasospasm. METHODS: Clinical severities, admission noncontrasted head computerized tomography (CT) scan, and incidences of vasospasm among 291 aSAH patients treated at our institution were evaluated. Admission head CTs were assessed for distributions of cisternal and ventricular blood. Patients with the following 4 criteria experienced considerably lower risk of vasospasm: (1) Hunt Hess grade 1 to 2, (2) Lack of thick subarachnoid blood filling 2 adjacent cisterns, (3) Lack of thick interhemispheric blood, and (4) Lack of biventricular intraventricular hemorrhage. RESULTS: One hundred thirty-three patients (45.7%) developed cerebral vasospasm. Hunt Hess grade greater than 2 (odds ratio [OR] 4.52, 95% confidence interval [CI] 2.74-7.46), adjacent cistern blood (OR 4.1, 95% CI 2.51-6.7), interhemispheric thick blood (OR 5.72, 95% CI 3.41-9.59), and biventricular intraventricular hemorrhage (OR 1.92, 95% CI 1.19-3.02) were significant risk factors. Application of our algorithm yielded a sensitivity of 29%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 54.5%, which was superior compared to metrics from current institutional practice criteria. Inter-rater agreement was substantial at mean kappa = 0.75. CONCLUSION: Application of our novel clinical algorithm produced successful identification of aSAH patients who experience zero risk of clinical vasospasm. Our algorithm is simple to apply with high reliability and is superior to currently available clinical and radiographic metrics.