Evidence map›Paper›PMID 34194519›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

Summarizing the Effective Herbs for the Treatment of Hypertensive Nephropathy by Complex Network and Machine Learning.

Jia-Ming Huan, Wen-Ge Su, Wei Li, Chao Gao, Peng Zhou, Chun-Sheng Fu, Xiao-Feng Wang, Yi-Min Wang, Yi-Fei Wang

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Annals of translational medicine · 2021
    Article
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

9 authors at 2 institutions in 1 country.

Jia-Ming HuanSchool of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250014, China.ORCID https://orcid.org/0000-0001-7599-0297
Wen-Ge SuThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Wei LiThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Chao GaoThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Peng ZhouThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Chun-Sheng FuThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Xiao-Feng WangThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Yi-Min WangFirst School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250014, China.
Yi-Fei WangThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China.ORCID https://orcid.org/0000-0002-3311-1239
Affiliated Hospital of Shandong University of Traditional Chinese Medicine · CNShandong University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertensive nephropathy is a common complication of hypertension. Traditional Chinese medicine has been used in the clinical treatment of hypertensive nephropathy for a long time, but the commonly used prescriptions have not been summarized, and the basic therapeutic approaches have not been discussed. Based on data from 3 years of electronic medical records of traditional Chinese medicine used at the Affiliated Hospital of Shandong University of Traditional Chinese Medicine, a complex network and machine learning algorithm was used to explore the prescribed herbs of traditional Chinese medicine in the treatment of hypertensive nephropathy (HN). In this study, complex network algorithms were used to describe traditional Chinese medicine prescriptions for HN treatment. The Apriori algorithm was used to analyze the compatibility of these treatments with modern medicine. Data on the targets and regulatory genes related to hypertensive nephropathy and the herbs that affect their expression were obtained from public databases, and then, the signaling pathways enriched with these genes were identified on the basis of their participation in biological processes. A clustering algorithm was used to analyze the therapeutic pathways at multiple levels. A total of 1499 prescriptions of traditional Chinese medicines used for the treatment of hypertensive renal damage were identified. Fourteen herbs used to treat hypertensive nephropathy act through different biological pathways: huangqi, danshen, dangshen, fuling, baizhu, danggui, chenpi, banxia, gancao, qumai, cheqianzi, ezhu, qianshi, and niuxi. We found the formulae of these herbs and observed that they could downregulate the expression of inflammatory cytokines such as TNF, IL1B, and IL6 and the NF-

Identifiers

PMID34194519
PMCPMC8214481
OpenAlexW3167622835

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.