Evidence map›Paper›PMID 25797918›Full record

ArticleScientific reports2015

Integrating clinical indexes into four-diagnostic information contributes to the Traditional Chinese Medicine (TCM) syndrome diagnosis of chronic hepatitis B.

Hong Kang, Yu Zhao, Chao Li, Yujia Chen, Kailin Tang, Linlin Yang, Chao Ma, Jinghua Peng, Ruixin Zhu, Qi Liu and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 5% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Health-related quality-of-life among patients with premature ovarian insufficiency: a systematic review and meta-analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020
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  18. A Microcosmic Syndrome Differentiation Model for Metabolic Syndrome with Multilabel Learning.Evidence-based complementary and alternative medicine : eCAM · 2020
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  19. Article
  20. Factor and Cluster Analysis for TCM Syndromes of Real-World Metabolic Syndrome at Different Age Stage.Evidence-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

12 authors at 3 institutions in 1 country.

Hong Kang1] School of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China [2] School of Biomedical Informatics, University of Texas Health Science Center, Houston. TX 77030, USA.
Yu ZhaoInstitute of Liver Diseases, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, P.R.China.
Chao LiSchool of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China.
Yujia ChenSchool of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China.
Kailin TangSchool of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China.
Linlin YangSchool of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China.
Chao MaKey Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, P.R.China.
Jinghua PengInstitute of Liver Diseases, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, P.R.China.
Ruixin ZhuSchool of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China.
Qi LiuSchool of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China.
Yiyang Hu1] Institute of Liver Diseases, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, P.R.China [2] E-Institute of TCM Internal Medicine, Shanghai Municipal Education Commission, Shanghai 200003, P.R.China.
Zhiwei Cao1] School of Life Sciences and Technology, Tongji University, Shanghai 200092, P.R.China [2] Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, P.R.China.
Tongji University · CNShanghai University of Traditional Chinese Medicine · CNShanghai Institutes for Biological Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese Medicine (TCM) treatment has been commonly used to treat Chronic Hepatitis B (CHB) in Asian countries based on TCM syndrome diagnosis, also called "ZHENG". The syndrome is identified through the four-diagnostic methods, with certain degree of subjectivity and ambiguity from individual doctors. Normally those CHB patients also receive series of parameters from modern clinical examination, while they are routinely believed to be unrelated with the TCM syndrome diagnosis. In this study, we investigated whether these biomedical indexes in modern medicine could be beneficial to TCM syndrome diagnostics in an integrative way. Based on 634 patient samples from health controls and three subtypes of CHB syndromes, a two-view based hierarchical classification model was tested for TCM syndromes prediction based on totally 222 parameters integrated from both TCM practice and modern clinical tests. The results indicated that the performance of syndrome classification based on a proper integration of TCM and modern clinical indexes was significantly higher than those based on one view of parameters only. Furthermore, those indexes correlated with CHB syndrome diagnosis were successfully identified for CM indexes and biochemical indexes respectively, where potential associations between them were hinted to the MAPK signaling pathway.

Indexed as

Models, StatisticalAlgorithmsBiomarkersGene Expression RegulationHepatitis B, ChronicHepatitis B virusHost-Pathogen InteractionsHumansMAP Kinase Signaling SystemMedicine, Chinese TraditionalMitogen-Activated Protein KinasesSTAT Transcription FactorsSymptom AssessmentSyndromeBiomarkersMitogen-Activated Protein KinasesSTAT Transcription Factors

Identifiers

PMID25797918
PMCPMC4369723
OpenAlexW1970225950

What OpenQuestion holds

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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.