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Logistic regression model for predicting risk factors and contribution of cerebral microbleeds using renal function
Xuhui Liu1, Zheng Pan2, Yilan Li3
1Department of Neurology of the Second Hospital Affiliated to Lanzhou University, Lanzhou, China.
Frontiers in Neurology
|October 4, 2024
Summary
Hypertension and impaired kidney function, indicated by blood urea nitrogen and cystatin C, are key risk factors for cerebral microbleeds (CMBs). Managing these conditions can help reduce CMB incidence.
Area of Science:
- Neurology
- Nephrology
- Vascular Biology
Background:
- The brain and kidneys share similar microvascular structures, making them susceptible to blood pressure changes.
- Cerebral microbleeds (CMBs) are small hemorrhages in the brain vasculature.
- Understanding CMB risk factors is crucial for preventing neurological damage.
Purpose of the Study:
- To investigate the causative factors of cerebral microbleeds (CMBs).
- To quantify the contribution of each risk factor using a multivariate model.
- To identify key indicators for CMB risk assessment.
Main Methods:
- 164 hospitalized patients were enrolled between January 2022 and March 2023.
- Magnetic susceptibility-weighted imaging (SWI) was used to detect CMBs.
- Multivariate logistic regression and stepwise regression were employed to analyze risk factors.
Main Results:
- 36% of participants had CMBs.
- Hypertension (OR=13.95), blood urea nitrogen (BUN) (OR=1.57), cystatin C (CyC) (OR=4.90), and urinary β-2 microglobulin (OR=2.11) were significant risk factors.
- Hypertension was the most significant determinant (47.81% weight).
Conclusions:
- Hypertension, BUN, urinary β-2 microglobulin, and CyC are significant risk factors for CMBs.
- Controlling these indicators may reduce CMB incidence.
- This study provides a quantitative model for CMB risk assessment.
