A scoring model to predict the prognosis of patients with poor-grade aneurysmal subarachnoid hemorrhage

Abstract Background Patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH), defined as World Federation of Neurosurgical Societies (WFNS) grade IV-V has high rates of disability and mortality. The objective of this research is to prognosticate outcomes of poor-grade aSAH accurately. Methods A total of 147 poor-grade aSAH patients in our center were enrolled. Risk variables identified by multivariate logistic regression were used to devise the scoring model (total score of 0–9 points). The score values were estimated according to β coefficients. A cohort of 68 patients from another institute was used to validate the model. Results Multivariate analysis revealed that modified Fisher grade above II (odds ratio [OR], 2.972; p = 0.034), age ≥ 65 years (OR, 3.534; p = 0.006), conservative treatment (OR, 5.078; p = 0.019), WFNS Grade V (OR, 2.638; p = 0.029), delayed cerebral ischemia (OR, 3.170; p = 0.016), shunt-dependent hydrocephalus (OR, 3.202; p = 0.032) and cerebral herniation (OR, 7.337; p < 0.001) were significant predictors of poor prognosis (modified Rankin Scale [mRS] ≥ 3). By integration of above factors, a scoring system was constructed and divided poor-grade aSAH patients into three categories: low risk (0–1 point), intermediate risk (2–3 points) and high risk (4–9 points), with risk of poor prognosis being 11%, 52% and 87% respectively (P < 0.001). The area under the curve in derivation cohort was 0.844 (p < 0.001; 95% CI, 0.778–0.909). AUC in validation cohort was 0.831 (p < 0.001; 95% CI, 0.732–0.929). Conclusions The new scoring model could improve prognostication of prognosis and help decision-making for subsequent complement treatment.