IDENTIFICATION OF RISK FACTORS FOR CEREBRAL ANEURYSM RUPTURE THROUGH STATISTICAL ANALYSIS

Abstract

This study examines the relationship between clinical, morphological, and hemodynamic factors and the risk of rupture in individuals with cerebral aneurysms. A logistic regression model was developed to identify variables influencing aneurysm rupture. The results indicate that age (p=0.0074) and comorbidities (p=0.0157) have a statistically significant effect on rupture probability. Variance Inflation Factor (VIF) analysis revealed multicollinearity between the length and width variables (VIF=3.96), while no such relationship was detected for other variables. Chi-square and Mann-Whitney U tests confirmed that age, aneurysm type, and comorbidities differ significantly between patients with and without rupture (p<0.05). Post-hoc analysis further supported statistically significant differences between groups concerning age (p=0.0001), aneurysm type (p=0.0004), and comorbidities (p=0.0039). Fisher’s exact test demonstrated a significant association between rupture risk and variables such as diabetes, ischemic cerebrovascular disease, a history of ischemic stroke, and coronary artery predisposition (p<0.05). This comprehensive analysis highlights the critical role of age, aneurysm type, and specific comorbidities in determining the risk of cerebral aneurysm rupture.