Innovative prognostication: a novel nomogram for post-interventional aneurysmal subarachnoid hemorrhage patients.

Background and purpose: Spontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a common acute cerebrovascular disease characterized by severe illness, high mortality, and potential cognitive and motor impairments. We carried out a retrospective study at Fujian Provincial Hospital to establish and validate a model for forecasting functional outcomes at 6 months in aSAH patients who underwent interventional embolization. Methods: 386 aSAH patients who underwent interventional embolization between May 2012 and April 2022 were included in the study. We established a logistic regression model based on independent risk factors associated with 6-month adverse outcomes (modified Rankin Scale Score ≥ 3, mRS). We evaluated the model's performance based on its discrimination, calibration, clinical applicability, and generalization ability. Finally, the study-derived prediction model was also compared with other aSAH prognostic scales and the model's itself constituent variables to assess their respective predictive efficacy. Results: The predictors considered in our study were age, the World Federation of Neurosurgical Societies (WFNS) grade of IV-V, mFisher score of 3-4, secondary cerebral infarction, and first leukocyte counts on admission. Our model demonstrated excellent discrimination in both the modeling and validation cohorts, with an area under the curve of 0.914 ( Conclusion: The new prediction nomogram has the capability to forecast the unfavorable outcomes at 6 months after intervention in patients with aSAH.