Evidence map›Paper›PMID 23843864›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2013

Prescription pattern of chinese herbal products for diabetes mellitus in taiwan: a population-based study.

Chung-Yu Huang, Yueh-Ting Tsai, Jung-Nien Lai, Feng-Lin Hsu

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In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
21.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 48 citations in OpenAlex.

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  14. Effective Dose ofFrontiers in pharmacology · 2020
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  16. Study on the Antibreast Cancer Mechanism and Bioactive Components ofEvidence-based complementary and alternative medicine : eCAM · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Chung-Yu HuangInstitute of Traditional Medicine, School of Medicine, National Yang-Ming University, No. 155, Section 2, Linong Road, Taipei 112, Taiwan ; Department of Traditional Medicine, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan.
Yueh-Ting Tsai
Jung-Nien Lai
Feng-Lin Hsu
National Yang Ming Chiao Tung University · TWTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background. Traditional Chinese medicine (TCM), when given as a therapy for symptom relief, has gained widespread popularity among diabetic patients. The aim of this study is to analyze the utilization of TCM among type 2 diabetic patients in Taiwan. Methods. The use of TCM for type 2 diabetic patients were evaluated using a randomly sampled cohort of 1,000,000 beneficiaries recruited from the National Health Insurance Research Database. Results. Overall, 77.9% (n = 31,289) of type 2 diabetic patients utilized TCM and 13.9% (n = 4,351) of them used TCM for the treatment of type 2 diabetes. Among the top ten most frequently prescribed herbal formulae, four remedies, Zhi-Bo-Di-Huang-Wan, Qi-Ju-Di-Huang-Wan, Ji-Sheng-Shen-Qi-Wan and Ba-Wei-Di-Huang-Wan are derivative formulae of Liu-Wei-Di-Huang-Wan. In other words, Liu-Wei-Di-Huang-Wan and its derivatives were found to be the most common herbal formulae prescribed by TCM doctors for the treatment of diabetes in Taiwan. Conclusion. Although some evidence does support the use TCM to treat diabetes, the results from the current study may have been confounded by placebo effect, which emphasize the need for well conducted, double-blind, randomized, placebo-controlled studies in order to further evaluate the efficacy of Liu-Wei-Di-Huang-Wan on patients with type 2 diabetes.

Identifiers

PMID23843864
PMCPMC3703417
OpenAlexW2089461532

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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.