Osmophobia in Patients With Migraine: A Systematic Review and Meta‐Analysis
Abstract
ABSTRACT Objective To determine the prevalence of osmophobia and to better characterize experiences reported by patients with migraine. Data Sources CINAHL, Cochrane Library, PubMed, and SCOPUS. Methods The literature was searched for articles reporting prevalence of osmophobia in patients with migraine. Primary outcome measures included proportions (%) and odds ratio (OR) with 95% confidence intervals (CI). Results Fifty‐eight studies were included ( n = 22,299 patients). The prevalence of osmophobia among patients with migraine was 47.8% [95% CI: 42.0%–53.6%]. Migraine attacks triggered by odor occurred in 40.1% [95% CI: 32.7%–47.8%] of patients with perfume as the primary trigger. Patients that experienced osmophobia were at greater risk of experiencing other sensory disturbances, such as photophobia, aura, and nausea (OR = 1.45, 1.66, 1.73, respectively, all p < 0.0001). Conclusion Osmophobia is a significant and underrecognized component of migraine. In this study, n e arly half of patients with migraine reported osmophobia and over a third identified specific odorants, such as perfume or smoke, as a trigger of migraine attacks. Of note, true prevalence of osmophobia is hard to discern as studies were selected based on reporting of osmophobia. This study furthers the understanding that osmophobia can be a concomitant symptom in patients with migraine, and has association with other sensory disturbances, which may guide both diagnosis and management of migraine.
How strong is the evidence?
Evidence Hub reads this as a systematic review, 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: 22,299 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.