Development and Internal Validation of the ARISE Prediction Models for Rebleeding After Aneurysmal Subarachnoid Hemorrhage

BACKGROUND: Aneurysmal rerupture is one of the most important determents for outcome after aneurysmal subarachnoid hemorrhage and still occurs frequently because individual risk assessment is challenging given the heterogeneity in patient characteristics and aneurysm morphology. OBJECTIVE: To develop and internally validate a practical prediction model to estimate the risk of aneurysmal rerupture before aneurysm closure. METHODS: We designed a multinational cohort study of 2 prospective hospital registries and 3 retrospective observational studies to predict the risk of computed tomography confirmed rebleeding within 24 and 72 hours after ictus. We assessed predictors with Cox proportional hazard regression analysis. RESULTS: Rerupture occurred in 269 of 2075 patients. The cumulative incidence equaled 7% and 11% at 24 and 72 hours, respectively. Our base model included hypertension, World Federation of Neurosurgical Societies scale, Fisher grade, aneurysm size, and cerebrospinal fluid drainage before aneurysm closure and showed good discrimination with an optimism corrected c-statistic of 0.77. When we extend the base model with aneurysm irregularity, the optimism-corrected c-statistic increased to 0.79. CONCLUSION: Our prediction models reliably estimate the risk of aneurysm rerupture after aneurysmal subarachnoid hemorrhage using predictor variables available upon hospital admission. An online prognostic calculator is accessible at https://www.evidencio.com/models/show/2626.

Automated summary

This study developed a practical prediction model to estimate the risk of aneurysmal rerupture before aneurysm closure and internally validated the model. The results showed that both the base model and the extended model had good discrimination and could reliably estimate the risk of aneurysmal rerupture.