Evidence map›Paper›PMID 42877258›Full record

ArticleJournal of pain research2026

Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Endometriosis: A Protocol for Data Mining.

Linglin Dai, Yin Zhang, Lili Wang

Abstract read
In one paragraph

Article in Journal of pain research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Linglin Dai *Department of Acupuncture, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People's Republic of China.
Yin Zhang *Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, People's Republic of China.ORCID 0000-0002-9742-5421
Lili WangDepartment of Acupuncture, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Endometriosis, characterized by dysmenorrhea and pelvic pain, is a common gynecological disease. Acupuncture, as a complementary and alternative therapy for endometriosis, has been supported by a large body of clinical evidence. However, due to the heterogeneity of acupoint prescriptions, the commonly used acupoints remain undetermined. Purpose: This study aims to identify the commonly used acupoint selection and combination patterns for the treatment of endometriosis through a comprehensive data mining analysis based on existing literature. Methods: We will systematically search 8 databases (Web of Science (WOS), PubMed, Embase, Cochrane Library, Wanfang, Chongqing VIP database, China National Knowledge Infrastructure (CNKI), and the Chinese Biomedical Literature Database (CBM)) from their inception to September 30, 2026. Only acupuncture clinical trials will be included. All other types will be excluded. Literature deduplication will be performed using NoteExpress 4.3. Data management and descriptive statistical analysis will be completed using WPS Spreadsheets (version 12.1.0.26375). Association rule analysis will be conducted in SPSS Modeler 14.1. Cluster analysis, exploratory factor analysis, and decision tree analysis will be implemented using SPSS Statistics 26.0. Results: Our study will conduct an in-depth exploration of the frequently uesd acupoint selection and combination patterns for treating patients with endometriosis. Conclusion: The findings of this study will identify commonly used acupoints and potentially relevant acupoint combinations for acupuncture treatment in patients with endometriosis, and provide a basis for subsequent clinical decision-making, and for the selection of acupoints in prospective randomized controlled trials, thereby helping both clinicians and patients make more informed choices.

Indexed as

acupoint selection and combinationacupuncturedata miningendometriosisstudy protocol

Identifiers

PMID42877258
PMCPMC13664685

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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.