Evidence map›Paper›PMID 31885737›Full record

ArticleDisease markers2019

Circulating MicroRNAs as Novel Potential Biomarkers for Left Ventricular Remodeling in Postinfarction Heart Failure.

Guangyuan Gao, Weiwei Chen, Miao Liu, Xu Yan, Ping Yang

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
0.6field-weighted citation impact, top 38% 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, 3 syntheses or guidelines pooled it, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Guangyuan GaoDepartment of Cardiology, China-Japan Union Hospital of Jilin University, Changchun 130031, China.ORCID https://orcid.org/0000-0002-3948-4458
Weiwei ChenDepartment of Cardiology, China-Japan Union Hospital of Jilin University, Changchun 130031, China.
Miao LiuDepartment of Cardiology, China-Japan Union Hospital of Jilin University, Changchun 130031, China.
Xu YanDepartment of Cardiology, China-Japan Union Hospital of Jilin University, Changchun 130031, China.
Ping YangDepartment of Cardiology, China-Japan Union Hospital of Jilin University, Changchun 130031, China.ORCID https://orcid.org/0000-0001-7960-6248
Union Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating microRNAs (miRNAs) have been proposed as potential biomarkers for left ventricular remodeling in postinfarction heart failure (HF). However, the diagnostic reproducibility of the use of circulating miRNAs may be affected by the temporal expression of miRNAs following myocardial infarction (MI). In the current study, using a MI-induced HF rat cohort (4-, 8-, and 12-week post-MI groups), we investigated the temporal expression of plasma miRNAs during the development of left ventricular remodeling. The plasma miRNA expression profile was obtained using miRNA sequencing. The expression of candidate miRNAs in plasma and tissues was examined with real-time PCR. Target genes of candidate miRNAs were predicted using a parallel miRNA-messenger RNA expression profiling approach. The value of plasma miRNAs as biomarkers for left ventricular remodeling was evaluated in patients with postinfarction HF (

Indexed as

Ventricular RemodelingAgedAnimalsBiomarkersDisease Models, AnimalFemaleGene Expression ProfilingGene Expression RegulationHeart FailureHumansMaleMicroRNAsMiddle AgedMyocardial InfarctionRatsSequence Analysis, RNABiomarkersMicroRNAsMIRN20a microRNA, humanMIRN340 microRNA, humanmirnlet7 microRNA, human

Identifiers

PMID31885737
PMCPMC6914954
OpenAlexW2992115996

What OpenQuestion holds

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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.