ArticleJournal of pain research2025
Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Trigeminal Neuralgia: A Protocol for Data Mining.
Article in Journal of pain research, 2025. 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.
- Data Mining of Acupuncture Prescriptions for Lateral Epicondylitis: A Literature-Based Analysis of Acupoint Patterns and Parameters.Journal of pain research · 2026Article
- Effect of Electroacupuncture for Trigeminal Neuralgia: Study Protocol for a Multicenter Randomized Controlled Trial.Journal of pain research · 2026Article
- Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Trigeminal Neuralgia: A Protocol for Data Mining [Response to Letter].Journal of pain research · 2025Article
- Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Trigeminal Neuralgia: A Protocol for Data Mining [Letter].Journal of pain research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Trigeminal neuralgia is a prevalent neurological disorder within neuropathic pain. It severely impairs patients' quality of life, disrupting daily activities with intense facial pain. While acupuncture has proven effective in treating it, there's no consensus on acupoint selection. Different acupuncturists use various acupoints based on personal theories and experiences, and the optimal acupoints remain unclear due to varied analgesic mechanisms. This lack of clarity obstructs the standardization of acupuncture treatment, emphasizing the need for further research. Objective: Our purpose is to conduct the first thorough data mining analysis to identify the most effective acupoint selection and combinations for treating trigeminal neuralgia from published clinical trials. Methods: We will search 8 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 inception to May 2025. Clinical trials assessing the effectiveness of acupuncture therapy on the management of trigeminal neuralgia will be selected. We will strictly screen literature according to inclusion and exclusion criteria, and then extract relevant data for analysis. Descriptive statistics will be performed in Excel 2021. Association rule analysis will be performed in SPSS Modeler 14.1. Exploratory factor analysis, cluster analysis, and decision tree analysis will be performed in SPSS Statistics 26.0. Since the study was based on published studies, no ethical approval was required. Results: This study will investigate the most effective acupoint selection and combinations for patients with trigeminal neuralgia. Conclusion: Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with trigeminal neuralgia, helping clinicians and patients make a more informed decision together.
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What OpenQuestion 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 OpenQuestion graph.