Endothelial Activation and Stress Index (EASIX) in migraine: association with disease subtypes and clinical characteristics
Abstract
Background: Migraine is a common neurovascular disorder associated with endothelial dysfunction and systemic microvascular stress. The Endothelial Activation and Stress Index (EASIX) is a novel composite biomarker that has been proposed to reflect endothelial stress and thrombo-inflammatory activity. This study aimed to investigate the association between EASIX levels and migraine subtypes and to explore its potential clinical relevance in patients with migraine with aura.
Methods: This retrospective cross-sectional study included 66 patients with migraine with aura, 99 patients with migraine without aura, and 81 age- and sex-matched healthy controls. EASIX was calculated using the formula: (lactate dehydrogenase × creatinine) / platelet count. EASIX values were compared among the study groups. Receiver operating characteristic (ROC) curve analysis was performed to assess the discriminative ability of EASIX in distinguishing patients with migraine with aura and overall migraine patients from healthy controls. Univariate logistic regression analysis was conducted to evaluate the association between EASIX levels and migraine with aura.
Results: Mean EASIX values were higher in patients with migraine with aura compared to healthy controls (p = 0.048). ROC analysis demonstrated that EASIX had a modest discriminative ability to differentiate patients with migraine with aura from healthy controls (AUC = 0.58). An optimal cut-off value of 0.37 yielded a sensitivity of 66.6% and…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 99 participants or records.
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.