Evidence map›Paper›PMID 31147455›Full record

Trial reportBioscience reports2019

Association between TGF-β1 -913G/C polymorphism and myocardial infarction risk in a Chinese Han population: a case-control study.

Lili Wu, Guofan Chen, Jia Song

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in Bioscience reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 3 institutions in 1 country.

Lili WuDepartment of Nursing, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 Qingchun East Road, Hangzhou, Zhejiang, China.
Guofan ChenDepartment of Cardiology, The Affiliated Hospital of Hangzhou Normal University, 126 Wenzhou Road, Hangzhou, Zhejiang, China.
Jia SongDepartment of Emergency, the Second Affiliated Hospital of Zhejiang Chinese Medical University, 318 Chaowang Road, Hangzhou, Zhejiang, China ccjia112@163.com.ORCID 0000-0003-2153-5197
Affiliated Hospital of Hangzhou Normal University · CNSir Run Run Shaw Hospital · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transforming growth factor (TGF)-β1 contributed to angiotensin II (Ang II)-mediated collagen accumulation after myocardial infarction (MI). The present study aimed to investigate the association of genetic variant of TGF-β1 gene with the risk of MI. The present study recruited a total of 530 MI patients and 651 healthy controls. The genomic DNA was extracted and subjected into polymerase chain reaction (PCR) and Sanger sequencing. The present study indicated that TGF-β1 -913G/C polymorphism was associated with increased risk for MI under the co-dominant, dominant and allelic models. The increased risk effect was also evident among the females, younger subjects (age < 60 years), smokers, non-drinkers and individuals with hypertension. Additionally, the present study observed significant differences among cases and controls in terms of total cholesterol (TC). In conclusion, TGF-β1 -913G/C polymorphism is associated with increased risk for MI. TGF-β1 -913G/C polymorphism may be a potential prognostic biomarker for MI.

Indexed as

Polymorphism, GeneticAgedAsian PeopleChinaFemaleHumansMaleMiddle AgedMyocardial InfarctionRisk FactorsTransforming Growth Factor beta1TGFB1 protein, humanTransforming Growth Factor beta1case-control studymyocardial infarctionpolymorphismTGF-β1

Identifiers

PMID31147455
PMCPMC6617046
OpenAlexW2947141274

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.