Evidence map›Paper›PMID 31551804›Full record

ArticleFrontiers in physiology2019

NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients.

Lin-Lin Zhao, Xin-Jian Qiu, Wen-Bo Wang, Ruo-Meng Li, Dong-Sheng Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

13 citing papers in PubMed, 31 citations in OpenAlex.

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  10. Metabolomic profiling of patients with high gradient aortic stenosis undergoing transcatheter aortic valve replacement.Clinical research in cardiology : official journal of the German Cardiac Society · 2021
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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

5 authors at 2 institutions in 1 country.

Lin-Lin ZhaoHealth Management Department, The Third Xiangya Hospital, Central South University, Changsha, China.
Xin-Jian QiuInstitute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, China.
Wen-Bo WangInstitute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, China.
Ruo-Meng LiTraditional Chinese Medicine Department, The Third Xiangya Hospital, Central South University, Changsha, China.
Dong-Sheng WangInstitute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary heart disease (CHD) remains highly prevalent and is one of the largest causes of death worldwide. Blood stasis syndrome (BSS) is the main syndrome associated with CHD. However, the underlying biological basis of BSS with CHD is not yet been fully understood. MATERIALS AND

methodsWe proposed a metabolomics method based on

resultsThe models constructed by RF could visually discriminate BSS from PS in CHD patients. Simultaneously, we obtained 12 characteristic metabolites, including lysine, glutamine, taurine, tyrosine, phenylalanine, histidine, lipid, citrate, choline, lactate, α-glucose, β-glucose related to the CHD patients, and Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD-BSS.

conclusionThe combining of

Indexed as

blood stasis syndromecoronary heart diseasemetabolomicsrandom forestsSystems BiologyZHENG types

Identifiers

PMID31551804
PMCPMC6738169
OpenAlexW2967550607

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.