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Journals / Middle East Journal of Science / 2026 / Volume: 11 Issue: 2

IDENTIFICATION OF RISK FACTORS FOR CEREBRAL ANEURYSM RUPTURE THROUGH STATISTICAL ANALYSIS

Meltem Yavuz Çelikdemir(Bitlis Eren Üniversitesi)0000-0003-0552-2601
Ayhan Akbal(FIRAT ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ)0000-0001-5385-9781
Pages
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Publication Date
2025-12-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results indicate that age (p=0.0074) and comorbidities (p=0.0157) have a statistically significant effect on rupture probability.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study examines the relationship between clinical, morphological, and hemodynamic factors and the risk of rupture in individuals with cerebral aneurysms.
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Key Findings & Data:The results indicate that age (p=0.0074) and comorbidities (p=0.0157) have a statistically significant effect on rupture probability.
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Conclusion & Impact:This comprehensive analysis highlights the critical role of age, aneurysm type, and specific comorbidities in determining the risk of cerebral aneurysm rupture.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Statistical analysis · cerebral aneurysm · rupture risk

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.

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Cite This Article

Çelikdemir, M. Y., Akbal, A., *, M. Y. Ç. (2025). IDENTIFICATION OF RISK FACTORS FOR CEREBRAL ANEURYSM RUPTURE THROUGH STATISTICAL ANALYSIS. Middle East Journal of Science, Volume: 11 Issue: 2. https://doi.org/10.51477/mejs.1658742

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