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Updated: Jun 4, 2026
13:53
The Helsinki Rat Microsurgical Sidewall Aneurysm Model
Published on: October 12, 2014
Study Design Differences and Temporal Morphology Bias in Intracranial Aneurysm Rupture Research: Toward Prospectively
Luca Ruggeri1, Carmine Antonio Donofrio2
1Department of Neurosurgery, Sant'Elia Hospital, Caltanissetta, Italy.
Neurosurgery
|June 3, 2026
Summary
Study design significantly impacts intracranial aneurysm rupture risk assessment. Cross-sectional studies overestimate morphological associations compared to prospective cohorts, highlighting the need for standardized prospective data for accurate risk stratification.
Area of Science:
- Neurosurgery
- Epidemiology
- Medical Imaging
Background:
- Intracranial aneurysm rupture risk stratification relies on meta-analyses of heterogeneous data.
- Study design differences, especially cross-sectional vs. prospective, may bias morphology-rupture associations.
Purpose of the Study:
- To evaluate how study design influences reported associations between aneurysm morphology and rupture risk.
- To assess if current evidence supports clinically useful rupture risk estimates.
Main Methods:
- Umbrella review of systematic reviews and meta-analyses (1999-2025) from major databases.
- Assessed methodological quality using AMSTAR-2.
- Compared effect estimates for morphology (size, shape, location) between prospective and cross-sectional study syntheses.
Main Results:
- Seventeen meta-analyses (200,000+ aneurysms) were included; significant study overlap was minimal.
- Morphological variables showed larger effect estimates in cross-sectional studies versus prospective analyses.
- Limited prospective data with standardized morphometrics, low event rates, and potential bias constrained causal interpretation.
Conclusions:
- Reported aneurysm morphology-rupture associations vary significantly by study design.
- Cross-sectional and prospective studies address different questions and are not interchangeable.
- Improved risk stratification requires large prospective studies with standardized morphometrics for validated prediction models.
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