ReviewIntegrative medicine research2018
Trends in deqi research: a text mining and network analysis.
Review in Integrative medicine research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 22 citations in OpenAlex.
- Psychophysical responses to needling depth using ultrasound imaging.BMC complementary medicine and therapies · 2025Article
- Research on strategies for enhancing drug knowledge dissemination on Chinese social media WeChat public accounts based on text mining technology.Frontiers in pharmacology · 2025Article
- Musculoskeletal ultrasound to evaluate the efficacy of acupuncture: a review.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2024Review
- Acupuncture for Women with Overactive Bladder: Perspective of Traditional Chinese Medicine and Related Mechanism.International journal of general medicine · 2023Review
- Article
- DES-ROD: Exploring Literature to Develop New Links between RNA Oxidation and Human Diseases.Oxidative medicine and cellular longevity · 2020Article
- Literature-Based Enrichment Insights into Redox Control of Vascular Biology.Oxidative medicine and cellular longevity · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDeqi is a term describing a special state of the human body, which is ready to cure itself through acupuncture stimulation and is believed to be a key factor in acupuncture treatment. However, knowledge about deqi remains subjective. Therefore, in this study, we aimed to determine the factors related to deqi generation based on present studies to promote the progression of deqi research.
methodsA term frequency-inverse document frequency (Tf-idf) was used to extract key elements from the abstracts of 148 articles searched from Pubmed, and the network structure between key elements was analyzed.
resultsA total of 37 items were extracted from the abstracts. Each item was categorized into one of three groups (acupuncture-related sensation, interventions or organ/mechanism). Acupuncture-related sensation was studied by comparing the items in the interventions group with the organ/mechanism group. Key elements related to deqi generation included muscles from the organ/mechanism group and intensity, depth and pressure from the interventions group. Items that belonged to the acupuncture-related sensation group were divided into two clusters: one cluster consisted of pain, tingling, aching, soreness, heaviness, fullness and numbness; the other included warm, cold and dull.
conclusionWe could find out that the trend of deqi was leaning towards the interventions group, which related to the generation of deqi; thus, authors concluded that the mechanism studies, which are aimed to investigate why deqi is generated or what kind of meanings it has, are needed for evolution of acupuncture theory and application of the brand new technologies and related devices.
Indexed as
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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.