Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study

BackgroundIntracranial aneurysms (IAs) can lead to subarachnoid hemorrhage, a life-threatening event associated with high morbidity and mortality. Identifying individuals at elevated risk is crucial for guiding timely interventions and improving patient outcomes.MethodsIn this retrospective cohort s...

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Main Authors: Bin Zhang, Zisheng Liu, Jiaming Xu, Jianyong Cai, Huajun Ba, Qun Lin, Jun Sun, Liangzhi Ye
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Neurology
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Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1559484/full
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author Bin Zhang
Zisheng Liu
Jiaming Xu
Jianyong Cai
Huajun Ba
Qun Lin
Jun Sun
Liangzhi Ye
author_facet Bin Zhang
Zisheng Liu
Jiaming Xu
Jianyong Cai
Huajun Ba
Qun Lin
Jun Sun
Liangzhi Ye
author_sort Bin Zhang
collection DOAJ
description BackgroundIntracranial aneurysms (IAs) can lead to subarachnoid hemorrhage, a life-threatening event associated with high morbidity and mortality. Identifying individuals at elevated risk is crucial for guiding timely interventions and improving patient outcomes.MethodsIn this retrospective cohort study, 850 patients who received interventional or surgical treatment for IAs between January 2018 and January 2024 were included. Demographic data (e.g., age, sex), lifestyle factors, and comorbidities were recorded. Hematologic, biochemical, and coagulation parameters were measured to evaluate their potential association with IA rupture. A univariate logistic regression was first conducted, followed by a multivariate logistic regression with a backward stepwise approach to derive the final predictive model. The model’s performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.ResultsYounger age, female sex, higher neutrophil count, lower hematocrit, and elevated markers of inflammation and coagulation (including fibrinogen and D-dimer) emerged as key risk factors. Electrolyte imbalances, such as low potassium, and elevated lactate dehydrogenase were also significantly associated with rupture. The optimized model achieved an AUC of 0.815, with good calibration and clinical utility indicated by decision curve analysis.ConclusionThese findings highlight the interplay of demographic, inflammatory, metabolic, and coagulation parameters in determining rupture risk in patients with IAs. Incorporating these risk factors into clinical practice may enhance early detection, guide targeted prevention strategies, and ultimately improve outcomes for high-risk individuals.
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spelling doaj-art-ad77f07e23ad479092fcdfcda25459002025-08-20T02:50:22ZengFrontiers Media S.A.Frontiers in Neurology1664-22952025-03-011610.3389/fneur.2025.15594841559484Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort studyBin ZhangZisheng LiuJiaming XuJianyong CaiHuajun BaQun LinJun SunLiangzhi YeBackgroundIntracranial aneurysms (IAs) can lead to subarachnoid hemorrhage, a life-threatening event associated with high morbidity and mortality. Identifying individuals at elevated risk is crucial for guiding timely interventions and improving patient outcomes.MethodsIn this retrospective cohort study, 850 patients who received interventional or surgical treatment for IAs between January 2018 and January 2024 were included. Demographic data (e.g., age, sex), lifestyle factors, and comorbidities were recorded. Hematologic, biochemical, and coagulation parameters were measured to evaluate their potential association with IA rupture. A univariate logistic regression was first conducted, followed by a multivariate logistic regression with a backward stepwise approach to derive the final predictive model. The model’s performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.ResultsYounger age, female sex, higher neutrophil count, lower hematocrit, and elevated markers of inflammation and coagulation (including fibrinogen and D-dimer) emerged as key risk factors. Electrolyte imbalances, such as low potassium, and elevated lactate dehydrogenase were also significantly associated with rupture. The optimized model achieved an AUC of 0.815, with good calibration and clinical utility indicated by decision curve analysis.ConclusionThese findings highlight the interplay of demographic, inflammatory, metabolic, and coagulation parameters in determining rupture risk in patients with IAs. Incorporating these risk factors into clinical practice may enhance early detection, guide targeted prevention strategies, and ultimately improve outcomes for high-risk individuals.https://www.frontiersin.org/articles/10.3389/fneur.2025.1559484/fullintracranial aneurysmsinflammatory markersmetabolic biomarkerscoagulation factorspredictive modeling
spellingShingle Bin Zhang
Zisheng Liu
Jiaming Xu
Jianyong Cai
Huajun Ba
Qun Lin
Jun Sun
Liangzhi Ye
Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study
Frontiers in Neurology
intracranial aneurysms
inflammatory markers
metabolic biomarkers
coagulation factors
predictive modeling
title Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study
title_full Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study
title_fullStr Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study
title_full_unstemmed Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study
title_short Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study
title_sort comprehensive analysis of risk factors for intracranial aneurysm rupture a retrospective cohort study
topic intracranial aneurysms
inflammatory markers
metabolic biomarkers
coagulation factors
predictive modeling
url https://www.frontiersin.org/articles/10.3389/fneur.2025.1559484/full
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