Prognostic Value of Serum Bilirubin in Aneurysmal Subarachnoid Hemorrhage Patients.

Background: Bilirubin plays a crucial role in the pathophysiological processes of strokes. However, the relationship between serum bilirubin levels and the prognosis of aneurysmal subarachnoid hemorrhage (aSAH) remains unexplored. This study aims to investigate the association between serum bilirubin levels and the mortality rate of aSAH patients.

Methods: 695 aSAH patients were included to analyze the relationship between direct bilirubin (DBil), indirect bilirubin (IDBil), total bilirubin (TBil), and mortality. The univariate and multivariate logistic regression were conducted to discover risk factors for the mortality of aSAH. The restricted cubic spline (RCS) was used to show the correlation between DBil, IDBil, TBil, and mortality. A logistic regression predictive model was developed by incorporating significant factors in the multivariate logistic regression. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of serum bilirubin and the developed predictive model.

Results: 139 aSAH patients suffered death, with a mortality of 20.0%. Non-survivors had older age (p =0.007), lower GCS (p <0.001), higher Hunt Hess (p <0.001), and mFisher (p <0.001). Both DBil (p <0.001) and TBil (p =0.011) were significantly higher among non-survivors. While the IDBil did not show a difference between survivors and non-survivors. The multivariate analysis found age (p =0.111), Glasgow Coma Scale (p =0.005), white blood cell (p <0.001), glucose (p =0.004), DBil (p =0.001), delayed cerebral ischemia (p <0.001) were significantly related with the mortality of aSAH. A logistic regression predictive model for mortality was developed incorporating these five factors, which had an area under the ROC curve (AUC) of 0.876. The AUC of DBil, IDBil, and TBil for predicting mortality was 0.607, 0.570, and 0.529, respectively.

Conclusion: Serum DBil level is positively associated with the mortality risk of aSAH. The predictive model incorporating DBil is beneficial for clinicians to evaluate the mortality risk of aSAH and adopt personalized therapeutics.