Dataset Information

Sex Difference and Rupture Rate of Intracranial Aneurysms: An Individual Patient Data Meta-Analysis.

ABSTRACT:

Background and purpose

In previous studies, women had a higher risk of rupture of intracranial aneurysms than men, but female sex was not an independent risk factor. This may be explained by a higher prevalence of patient- or aneurysm-related risk factors for rupture in women than in men or by insufficient power of previous studies. We assessed sex differences in rupture rate taking into account other patient- and aneurysm-related risk factors for aneurysmal rupture.

Methods

We searched Embase and Pubmed for articles published until December 1, 2020. Cohorts with available individual patient data were included in our meta-analysis. We compared rupture rates of women versus men using a Cox proportional hazard regression model adjusted for the PHASES score (Population, Hypertension, Age, Size of Aneurysm, Earlier Subarachnoid Hemorrhage From Another Aneurysm, Site of Aneurysm), smoking, and a positive family history of aneurysmal subarachnoid hemorrhage.

Results

We pooled individual patient data from 9 cohorts totaling 9940 patients (6555 women, 66%) with 12 193 unruptured intracranial aneurysms, and 24 357 person-years follow-up. Rupture occurred in 163 women (rupture rate 1.04%/person-years [95% CI, 0.89-1.21]) and 63 men (rupture rate 0.74%/person-years [95% CI, 0.58-0.94]). Women were older (61.9 versus 59.5 years), were less often smokers (20% versus 44%), more often had internal carotid artery aneurysms (24% versus 17%), and larger sized aneurysms (≥7 mm, 24% versus 23%) than men. The unadjusted women-to-men hazard ratio was 1.43 (95% CI, 1.07-1.93) and the adjusted women/men ratio was 1.39 (95% CI, 1.02-1.90).

Conclusions

Women have a higher risk of aneurysmal rupture than men and this sex difference is not explained by differences in patient- and aneurysm-related risk factors for aneurysmal rupture. Future studies should focus on the factors explaining the higher risk of aneurysmal rupture in women.

SUBMITTER: Zuurbier CCM

PROVIDER: S-EPMC8785514 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND AND PURPOSE:Many ruptured intracranial aneurysms (IAs) are small. Clinical presentations suggest that small and large IAs could have different phenotypes. It is unknown if small and large IAs have different characteristics that discriminate rupture. METHODS:We analyzed morphological, hemodynamic, and clinical parameters of 413 retrospectively collected IAs (training cohort; 102 ruptured IAs). Hierarchal cluster analysis was performed to determine a size cutoff to dichotomize the IA population into small and large IAs. We applied multivariate logistic regression to build rupture discrimination models for small IAs, large IAs, and an aggregation of all IAs. We validated the ability of these 3 models to predict rupture status in a second, independently collected cohort of 129 IAs (testing cohort; 14 ruptured IAs). RESULTS:Hierarchal cluster analysis in the training cohort confirmed that small and large IAs are best separated at 5 mm based on morphological and hemodynamic features (area under the curve=0.81). For small IAs (<5 mm), the resulting rupture discrimination model included undulation index, oscillatory shear index, previous subarachnoid hemorrhage, and absence of multiple IAs (area under the curve=0.84; 95% confidence interval, 0.78-0.88), whereas for large IAs (?5 mm), the model included undulation index, low wall shear stress, previous subarachnoid hemorrhage, and IA location (area under the curve=0.87; 95% confidence interval, 0.82-0.93). The model for the aggregated training cohort retained all the parameters in the size-dichotomized models. Results in the testing cohort showed that the size-dichotomized rupture discrimination model had higher sensitivity (64% versus 29%) and accuracy (77% versus 74%), marginally higher area under the curve (0.75; 95% confidence interval, 0.61-0.88 versus 0.67; 95% confidence interval, 0.52-0.82), and similar specificity (78% versus 80%) compared with the aggregate-based model. CONCLUSIONS:Small (<5 mm) and large (?5 mm) IAs have different hemodynamic and clinical, but not morphological, rupture discriminants. Size-dichotomized rupture discrimination models performed better than the aggregate model.