Epidemiology and Clinical Characteristics of Nummular Headache in Observational Studies: A Systematic Review and Meta-Analysis
Abstract
INTRODUCTION: Nummular headache (NH) is a rare primary headache disorder which was first described in 2002. This meta-analysis aimed to evaluate the prevalence and relative frequencies of clinical features of NH.
METHODS: PubMed, Embase, Medline, and ScienceDirect were thoroughly searched for observational studies reporting the relevant data regarding NH diagnosed in accordance with ICHD-2, ICHD-3β, ICHD-3, or Pareja's original study. Random-effects meta-analysis was performed in order to calculate the pooled prevalence estimates (PPEs) and the I2 statistics was used to measure the between-study heterogeneity. The PRISMA guidelines were strictly followed by the study's structure. The Joanna Briggs Institute Checklist for Studies Reporting Prevalence Data was used to evaluate the risk of bias of included studies.
RESULTS: Out of initial 2,441 records, 17 studies met all of the inclusion criteria. The pooled mean age of onset of NH was 46.91 (95% confidence interval [95% CI]: 43.85-49.96). The PPE of NH in adult patients evaluated for a headache in a clinic-based setting was 0.7% (95% CI: 0.2-2.4), with slight female predominance (females = 0.5%, 95% CI: 0.2-1.4 vs. males = 0.3%, 95% CI: 0.1-0.8). The majority of patients (69.4%, 95% CI: 58.1-78.8) experience chronic course of NH. The shape of the headache was round/circular in 78.4% (95% CI: 71.9-83.7) and oval/elliptical in 21.6% (95% CI: 16.3-28.1) of patients. In 7.5% (95% CI: 2.7-19.0) of individuals, pain had multifocal…
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.