ArticleBrain and behavior2020
Association between red blood cell distribution width and white matter hyperintensities: A large-scale cross-sectional study.
Article in Brain and behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Metabolic signatures, vitamin D, and red cell distribution width in dementia risk: UK Biobank insights.GeroScience · 2026Article
- Red cell distribution width and cerebral white matter hyperintensity.Scientific reports · 2025Article
- Serum albumin and white matter hyperintensities.Translational psychiatry · 2024Article
- An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset.PLoS genetics · 2023Article
- Differential association of cerebral blood flow and anisocytosis in APOE ε4 carriers at midlife.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023Article
- What do users care about? Research on user behavior of mobile interactive video advertising.Heliyon · 2022Article
- Cross-Sectional Association Between Blood Cell Phenotypes, Cognitive Function, and Brain Imaging Measures in the Community-Based Framingham Heart Study.Journal of Alzheimer's disease : JAD · 2022Article
- Erythrocytes Are an Independent Protective Factor for Vascular Cognitive Impairment in Patients With Severe White Matter Hyperintensities.Frontiers in aging neuroscience · 2022Article
- Association between red blood cell distribution width and white matter hyperintensities: A large-scale cross-sectional study.Brain and behavior · 2020Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundRed blood cell distribution width (RDW) is a strong prognostic marker for various medical conditions, such as ischemic strokes. However, the relationships between higher RDW and the subtypes of white matter hyperintensities (WMHs) remain unclear. Hence, this study aimed to thoroughly evaluate the relationships between RDW and the subtypes of WMHs. PATIENTS AND
methodsThis cross-sectional study was a retrospective analysis of hospital database (Dongguan Medical System, from April 2015 to February 2017). The presence and subtypes of WMHs were evaluated using Fazekas score with the T2WI-FLAIR brain images from a 1.5-T MRI system. The overall sample was randomly split in half. One of the two split-half samples was used for determining the optimal cutoff value of higher RDW and another for further statistical analyses.
resultsA total of 555 subjects with WMHs and 642 controls were recruited. The optimal cutoff value of higher RDW was 13.25%. Logistic regression revealed that higher RDW (≥13.25%) was positively associated with periventricular WMHs (adjusted OR = 1.81, 95% CI: 1.16-2.82, p = .009). However, higher RDW was not associated with total WMHs (adjusted OR = 1.52, 95% CI: 0.99-2.33, p = .057) and deep WMHs (adjusted OR = 1.21, 95% CI: 0.76-1.94, p = .426).
conclusionOur findings suggested that higher RDW may be independently associated with periventricular WMHs, but not with total WMHs and deep WMHs.
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