ArticleJournal of pain research2024
Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Migraine: A Protocol for Data Mining.
Article in Journal of pain research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Exploration of Acupoint Compatibility Patterns in Acupuncture Treatment for Infertility Based on Data Mining.International journal of women's health · 2026Review
- Artificial intelligence guided acupuncture decision making and treatment: a review of research.Frontiers in medicine · 2026Review
- Exploration of the Application Rules and Clinical Significance of Acupoints in Acupuncture Treatment of Migraine Based on Data Mining.Journal of pain research · 2025Article
- A Data Mining Study for Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Carpal Tunnel Syndrome [Response to Letter].Journal of pain research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Migraine is a prevalent neurological condition that causes significant disability and has a profound impact on sufferers' ability to work and their overall quality of life. The efficacy of acupuncture in the treatment of migraines has been confirmed via extensive clinical research. However, because each acupoint generates various analgesic processes, and different acupuncture physicians select different acupoints, there is still uncertainty regarding the optimal acupoint selection. Objective: Our purpose is to conduct the initial thorough data mining analysis to determine the optimal acupoint selection and combinations for the treatment of migraines. Methods: We will conduct a search of eight electronic bibliographic databases (PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chongqing VIP Database) from the inception of the databases to July 2024. Clinical trials that evaluate the efficacy of acupuncture therapy in migraine management will be chosen. Literature will be rigorously reviewed in accordance with inclusion and exclusion criteria, and pertinent data will be extracted for analysis. Excel 2021 will be utilized to conduct descriptive statistics. SPSS Modeler 14.1 will be employed to conduct the association rule analysis. SPSS Statistics 26.0 will be employed to conduct exploratory factor analysis, cluster analysis, and decision tree analysis. Results: This study aims to investigate the optimal acupoint selection and combinations for people suffering from migraines. Conclusion: Our research will offer empirical support for the efficacy and possible therapeutic recommendations of acupoint application in treating migraine patients, facilitating collaborative decision-making between physicians and patients.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.