Evidence map›Paper›PMID 24744808›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2014

Text mining of the classical medical literature for medicines that show potential in diabetic nephropathy.

Lei Zhang, Yin Li, Xinfeng Guo, Brian H May, Charlie C L Xue, Lihong Yang, Xusheng Liu

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
5.3field-weighted citation impact, top 6% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  3. Text mining for case report articles on "peritoneal dialysis" from PubMed database.Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy · 2025
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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

7 authors at 2 institutions in 2 countries.

Lei ZhangNephropathy Department, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Guangzhou 510120, China.
Yin LiGuangzhou University of Chinese Medicine, Guangzhou 510405, China.
Xinfeng GuoEvidence-Based Medicine and Clinical Research Service Group, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Guangzhou 510120, China.
Brian H MayTraditional and Complementary Medicine Research Program, Health Innovations Research Institute, WHO Collaborating Centre for Traditional Medicine, School of Health Sciences, RMIT University, Bundoora, VIC 3083, Australia.
Charlie C L XueTraditional and Complementary Medicine Research Program, Health Innovations Research Institute, WHO Collaborating Centre for Traditional Medicine, School of Health Sciences, RMIT University, Bundoora, VIC 3083, Australia.
Lihong YangEvidence-Based Medicine and Clinical Research Service Group, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Guangzhou 510120, China.
Xusheng LiuNephropathy Department, Guangdong Provincial Hospital of Chinese Medicine, 111 Dade Road, Guangzhou 510120, China.
Guangzhou University of Chinese Medicine · CNRMIT University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives. To apply modern text-mining methods to identify candidate herbs and formulae for the treatment of diabetic nephropathy. Methods. The method we developed includes three steps: (1) identification of candidate ancient terms; (2) systemic search and assessment of medical records written in classical Chinese; (3) preliminary evaluation of the effect and safety of candidates. Results. Ancient terms Xia Xiao, Shen Xiao, and Xiao Shen were determined as the most likely to correspond with diabetic nephropathy and used in text mining. A total of 80 Chinese formulae for treating conditions congruent with diabetic nephropathy recorded in medical books from Tang Dynasty to Qing Dynasty were collected. Sao si tang (also called Reeling Silk Decoction) was chosen to show the process of preliminary evaluation of the candidates. It had promising potential for development as new agent for the treatment of diabetic nephropathy. However, further investigations about the safety to patients with renal insufficiency are still needed. Conclusions. The methods developed in this study offer a targeted approach to identifying traditional herbs and/or formulae as candidates for further investigation in the search for new drugs for modern disease. However, more effort is still required to improve our techniques, especially with regard to compound formulae.

Identifiers

PMID24744808
PMCPMC3976881
OpenAlexW1988469208

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.