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Development and validation of a predictive model for severe white matter hyperintensity with obesity
Fu Chen1,2, Lin-Hao Cao1, Fei-Yue Ma1
1Department of Neurology, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Frontiers in Aging Neuroscience
|June 18, 2024
Summary
This study identified key predictors for severe white matter hyperintensity (WMH) in obese individuals, developing a non-MRI prediction model. The model effectively screens for severe WMH with obesity (SWO), enabling early detection and intervention.
Area of Science:
- Neurology
- Radiology
- Biochemistry
Background:
- White matter hyperintensities (WMH) are common in obesity and associated with neurological risks.
- Early identification of severe WMH in obese individuals (SWO) is crucial for timely intervention.
- Current screening methods often rely on Magnetic Resonance Imaging (MRI), which can be inaccessible or costly.
Purpose of the Study:
- To identify predictors of severe white matter hyperintensity (WMH) in obese patients (SWO).
- To develop and validate a prediction model for screening SWO without MRI.
- To assess the clinical utility of the developed prediction model.
Main Methods:
- Logistic regression analysis was used to identify independent risk factors for SWO from a cohort of 650 patients.
- A prediction model and nomogram were constructed using identified predictors and validated through bootstrapping and Area Under the Curve (AUC) analysis.
- Decision Curve Analysis (DCA) was employed to evaluate the clinical usefulness of the nomogram.
Main Results:
- Hypertension, uric acid (UA), complement 3 (C3), and Interleukin 8 (IL-8) were identified as independent risk factors for SWO.
- The prediction model, incorporating hypertension, UA, C3, IL-8, folic acid (FA), fasting C-peptide (FCP), and eosinophil, demonstrated good diagnostic performance (AUC=0.823).
- The nomogram showed strong performance in both development (AUC=0.829) and validation (AUC=0.835) groups, with satisfactory calibration and significant clinical utility.
Conclusions:
- Hypertension, UA, C3, IL-8, FA, FCP, and eosinophil can predict SWO incidence.
- A total score exceeding 9 points indicates a significantly increased risk of SWO.
- The developed nomogram provides a convenient, non-MRI tool for early SWO screening, facilitating early detection and management of WMH hazards.
