Evidence map›Paper›PMID 33176699›Full record

ArticleBMC cardiovascular disorders2020

Risk factors for Keshan disease: a prospective cohort study protocol of gut flora.

Zhenzhen Li, Jin Wei, Yanping Zhang, Gaopeng Li, Huange Zhu, Na Lei, Qian He, Yan Geng, Jianhong Zhu

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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 3 institutions in 1 country.

Zhenzhen LiDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Jin WeiDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Yanping ZhangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Gaopeng LiKey Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, Shaanxi Key Laboratory of Physico-Inorganic Chemistry, College of Chemistry and Materials Science, Northwest University, Xi'an, 710127, People's Republic of China.
Huange ZhuDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Na LeiDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Qian HeDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Yan GengDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China.
Jianhong ZhuDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 Xiwu Road, Xi'an, 710004, People's Republic of China. zjh13389212293@163.com.ORCID 0000-0002-2383-5479
Shaanxi Provincial People's Hospital · CNSecond Affiliated Hospital of Xi'an Jiaotong University · CNMinistry of Education of the People's Republic of China · CN

Funding

the National Natural Science Foundation of China 81870298
6 · The paper itself

Abstract

backgroundKeshan disease is an endemic cardiomyopathy of undefined causes. Being involved in the unclear pathogenesis of Keshan disease, a clear diagnosis, and effective treatment cannot be initiated. However, the rapid development of gut flora in cardiovascular disease combined with omics and big data platforms may promote the discovery of new diagnostic markers and provide new therapeutic options. This study aims to identify biomarkers for the early diagnosis and further explore new therapeutic targets for Keshan disease.

methodsThis cohort study consists of two parts. Though the first part includes 300 participants, however, recruiting will be continued for the eligible participants. After rigorous screening, the blood samples, stools, electrocardiograms, and ultrasonic cardiogram data would be collected from participants to elucidate the relationship between gut flora and host. The second part includes a prospective follow-up study for every 6 months within 2 years. Finally, deep mining of big data and rapid machine learning will be employed to analyze the baseline data, experimental data, and clinical data to seek out the new biomarkers to predict the pathogenesis of Keshan disease. DISCUSSION: Our study will clarify the distribution of gut flora in patients with Keshan disease and the abundance and population changes of gut flora in different stages of the disease. Through the big data platform analyze the relationship between environmental factors, clinical factors, and gut flora, the main factors affecting the occurrence of Keshan disease were identified, and the changed molecular pathways of gut flora were predicted. Finally, the specific gut flora and molecular pathways affecting Keshan disease were identified by metagenomics combined with metabonomic analysis.

trial registrationChiCTR1900026639. Registered on 16 October 2019.

Indexed as

Gastrointestinal MicrobiomeMetabolomicsMetagenomicsAdolescentAdultAgedBacteriaBig DataBiomarkersCardiomyopathiesCase-Control StudiesEnterovirus InfectionsFemaleHumansIntestinesMaleBiomarkersCohort studyGut floraKeshan diseaseMetabonomic analysisThe big data platform

Identifiers

PMID33176699
PMCPMC7661207
OpenAlexW3101331926

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.