Non-pharmacological interventions for the prevention of migraine in adults: a systematic review and meta-analysis
Abstract
Migraine is a common and debilitating neurological condition. The limitations of drug-based preventive measures, such as insufficient effectiveness and poor tolerability, highlight the necessity for alternative prevention methods. This systematic review and meta-analysis examined the safety and efficacy of non-drug interventions aimed at preventing migraines in adults. Following PRISMA guidelines, this review conducted a comprehensive search of various databases from their inception until 2025 to identify relevant randomized controlled trials (RCTs), quasi-RCTs, and observational studies. Key outcomes measured were migraine frequency, intensity, disability levels, quality of life indicators, and medication usage. A total of ten studies were included indicating a non-significant decrease in the number of migraine days (mean difference [MD] = -1.06 per month; 95% confidence interval [CI]: -2.41 to 0.29) and pain intensity (MD = -1.40; 95% CI: -3.51 to 0.71), both exhibiting considerable heterogeneity (I² = 99%). Conversely, there was a statistically significant reduction in acute medication usage (MD = 0.29; 95% CI: 0.10 to 0.49; P = 0.003) with negligible heterogeneity (I² = 0%). A non-significant trend suggested that non-pharmacological interventions might favorably impact achieving a ≥50% reduction in headache frequency (odds ratio [OR] = 1.77; 95% CI: 0.77 to 4.10). Importantly, these interventions were well-tolerated without a significant increase in adverse events…
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.