Efficacy and exploratory treatment-response modeling of acupuncture for acute migraine based on DIA proteomics: a study protocol for a randomized controlled trial
Abstract
According to estimates from the 2019 Global Burden of Disease (GBD) study, approximately 1.1 billion people worldwide suffer from migraine, with a prevalence rate of about 14% to 15%. Despite the development of various medications for different types of migraine, such as acetaminophen and caffeine combination preparations, most patients still experience suboptimal symptom control. Therefore, identifying effective and safer alternative treatments holds significant clinical importance. Acupuncture was formally recommended by the World Health Organization as a migraine therapy as early as 1979. In recent years, substantial domestic and international research evidence has demonstrated the distinct advantages of acupuncture in treating migraine. Proteomics technology can assess the final products of adaptive changes in the body following acupuncture, thereby establishing a close association with disease progression.
This study aims to evaluate the efficacy of a single acupuncture session for acute migraine, identify subgroups with different short-term treatment responses, and explore baseline plasma protein biomarkers potentially associated with acupuncture response. An exploratory proof-of-concept model will be developed to assess whether a small set of prespecified clinical and proteomic features may contain preliminary predictive information regarding short-term treatment response.
This study is divided into three parts. First, this randomized controlled trial will recruit 86…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design. Reported size: 86 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.