Prevalence and clinical characteristics of white matter hyperintensities in Migraine: A meta-analysis
Abstract
BACKGROUND: Current evidences show an increased risk of white matter hyperintensities (WMHs) in migraineurs compared to age-matched controls. However, WMHs prevalence and the associations between WMHs and clinical characteristics in migraineurs have not been systematically evaluated using a meta-analytical approach. This study explored the pooled prevalence of WMHs and the associations of WMHs with the clinical characteristics in patients with migraine.
METHODS: A systematic review and meta-analysis of observational studies reporting the occurrence and clinical characteristics of patients with WMHs attributed to migraine was performed. We searched the PubMed, Web of Science, and Embase databases. Random-effects models were used to calculate the pooled prevalence rate, odds ratio (OR), or mean difference (MD) with corresponding 95% confidence intervals (CIs).
RESULTS: Thirty eligible studies were identified including 3,502 migraineurs aged 37.2 (mean) years. The pooled WMHs prevalence was 44 %, 45 %, and 38 % in migraine, migraine with aura, and migraine without aura groups, respectively. In migraineurs with WMHs, the frontal lobe and subcortical white matter were the most susceptible area. Compared with non-migraine controls, patients with migraine had increased odds for WMHs (OR 4.32, 95 % CI = 2.56-7.28, I2 = 67 %). According to reported univariable results from included studies, pooled analysis showed that clinical characteristics including age, presence of aura, disease…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.