Why the study?
Accurate prediction of initial aneurysmal subarachnoid hemorrhage severity is important for managing unruptured intracranial aneurysms, prompting investigation into pre-rupture patient and aneurysm predictors.
Age over 55 years and intracranial aneurysm size greater than 6 mm are independent pre-rupture predictors of severe aneurysmal subarachnoid hemorrhage, providing insights for risk stratification.
OBJECTIVE: Accurate prediction of the initial severity of aneurysmal subarachnoid hemorrhage (aSAH) is important for effective management of unruptured intracranial aneurysms (IA). This study aims to investigate patient and IA characteristics as pre-rupture predictors of severe aSAH. METHODS: This retrospective analysis included all patients aged 18 years or older diagnosed with acute aSAH at our center between January 2003 and June 2016. Severe aSAH was defined on the patient's initial condition as World Federation of Neurosurgical Societies Scale Grade 4-5 and the original Fisher Scale grade 3-4 on CT imaging. We recorded demographic, clinical, and radiological parameters assessable prior to rupture, and utilized univariate and multivariate regression analyses to identify predictors of severe aSAH. RESULTS: 932 patients were included in the final analysis, with a median age of 55 years. Severe aSAH occurred in 404 patients (43.35 %). Multivariate analysis identified that age > 55 years (adjusted odds ratio [aOR]= 1.33, 95 % CI: 1.01-1.76) and IA size > 6 mm (aOR= 1.90, 95 % CI: 1.45-2.50) as independent predictors of severe aSAH. In contrast, smoking (aOR= 0.49, 95 % CI: 0.36-0.67) and migraine (aOR= 0.26, 95 % CI: 0.10-0.70) were associated with reduced severity. Other examined factors, including blood pressure and medication use, were not significantly associated with aSAH severity. CONCLUSION: aSAH severity can be predicted prior to IA rupture. The identified patient and IA characteristics provide valuable insights for risk stratification and indicate directions for further investigation. Future studies should explore additional risk factors beyond those directly related to aneurysm rupture, incorporating them into treatment decision-making to enhance personalized management strategies and optimize patient outcomes.
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Song et al. (2025) studied this question.
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