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The effectiveness of non-invasive vagus nerve stimulation in migraine management: a meta-analysis of randomized controlled trials

Qian C, Shi Y, Liu C, Ye Z, Jin Y, Wang H, Li D

Frontiers in neurology, 2026

917 participants

Abstract

Background: Non-invasive vagus nerve stimulation (nVNS) has emerged as a potential non-pharmacological intervention for migraine. This systematic review and meta-analysis of randomized controlled trials (RCTs) evaluated its efficacy for both acute and preventive migraine treatment.

Methods: This review was conducted according to PRISMA and registered in PROSPERO (CRD420261347799). PubMed, Cochrane Central, Embase, CNKI, VIP, and Wanfang were searched from inception to February 19, 2026, to identify RCTs of nVNS for migraine. The primary outcomes were monthly headache days, monthly acute medication use, and headache pain intensity. Continuous outcomes were synthesized as mean differences (MDs), and dichotomous outcomes as odds ratios (ORs), with 95% confidence intervals (CIs). Fixed- or random-effects models were applied according to outcome type and statistical heterogeneity, and random-effects sensitivity analyses were conducted for continuous primary outcomes to account for expected clinical heterogeneity. Risk of bias was assessed using the original Cochrane Risk of Bias tool, and certainty of evidence was evaluated using GRADE.

Results: Seven RCTs involving 917 patients with migraine were included. Meta-analysis showed that nVNS significantly reduced monthly headache days (MD = -1.52, 95% CI - 1.86 to -1.18, p p p < 0.001), with low heterogeneity across these outcomes. Exploratory overall estimates for acute treatment outcomes also favored nVNS for pain-free and…

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. Reported size: 917 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

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