Burden of headache among people with epilepsy: A systematic review and meta-analysis
Abstract
Background: Headache and epilepsy frequently coexist, likely reflecting shared mechanisms such as cortical hyperexcitability and genetic susceptibility. However, the burden of headache in people with epilepsy (PWE), particularly in children, remains uncertain.
Methods: We performed a systematic review and meta-analysis (PROSPERO: CRD420251000235) of observational studies reporting headache prevalence in PWE. MEDLINE, EMBASE, Scopus, and Web of Science were searched to January 2026. Random-effects meta-analyses of proportions were conducted, with subgroup analyses by geography, age, and headache subtypes. Publication bias was assessed using Doi plots and the LFK index.
Results: Seventy-three studies including 103,357 PWE (2067 children) were analyzed. The pooled prevalence of headache among PWE was estimated at 40.36% (36.51-44.32); in children, it was 27.5% (95% CI: 19.7-36.1). Prevalence varied significantly by geographic region (p < 0.0001), highest in Africa and lowest in North America. Among headaches temporally related to seizures, interictal headache was reported in 35.48% (95% CI: 26.17%-46.04%), and postictal headache in 27.06% (95% CI: 22.53%-32.12%), representing the most frequent subtypes. Patients receiving polytherapy had lower headache prevalence compared with those on monotherapy. Publication bias was evident for several outcomes.
Conclusions: Headache affects nearly two in five individuals with epilepsy and over one in four children, representing a…
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: 2,067 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.