Propranolol in the management of recurrent migraine: a meta-analytic review
Abstract
We used meta-analytic statistical techniques to synthesize findings from studies that evaluated propranolol HCI for the prevention of recurrent migraine (2,403 treated patients). The modal migraine sufferer treated in these studies was a female, about 37 years of age, who suffered from common (rather than classical) migraines and reported a 17-year history of problem migraines. The modal treatment was 160 mg. propranolol per day. Meta-analysis revealed that, on average, propranolol yielded a 44% reduction in migraine activity when daily headache recordings were used to assess treatment outcome, and a 65% reduction in migraine activity when less conservative measures (e.g., clinical ratings of improvement, global patient reports) were used. Meta-analysis thus revealed substantial support for short-term effectiveness of propranolol. However, little information was available concerning the long-term effectiveness of propranolol.
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: 2,403 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.