Evidence map›Paper›PMID 29456889›Full record

ArticlePeerJ2018

A bibliometric analysis in gene research of myocardial infarction from 2001 to 2015.

Huaqiang Zhou, Wulin Tan, Zeting Qiu, Yiyan Song, Shaowei Gao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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

28 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  18. A Bibliometric Analysis of 14,822 Researches on Myocardial Reperfusion Injury by Machine Learning.International journal of environmental research and public health · 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.

Huaqiang Zhou *Department of Anesthesia, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Wulin Tan *Department of Anesthesia, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zeting Qiu *Department of Anesthesia, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yiyan SongZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Shaowei GaoDepartment of Anesthesia, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWe aimed to evaluate the global scientific output of gene research of myocardial infarction and explore their hotspots and frontiers from 2001 to 2015, using bibliometric methods.

methodsArticles about the gene research of myocardial infarction between 2001 and 2015 were retrieved from the Web of Science Core Collection (WoSCC). We used the bibliometric method and Citespace V to analyze publication years, journals, countries, institutions, research areas, authors, research hotspots, and trends. We plotted the reference co-citation network, and we used key words to analyze the research hotspots and trends.

resultsWe identified 1,853 publications on gene research of myocardial research from 2001 to 2015, and the annual publication number increased with time. Circulation published the highest number of articles. United States ranked highest in the countries with most publications, and the leading institute was Harvard University. Relevant publications were mainly in the field of Cardiovascular system cardiology. Keywords and references analysis indicated that gene expression, microRNA and young women were the research hotspots, whereas stem cell, chemokine, inflammation and cardiac repair were the frontiers.

conclusionsWe depicted gene research of myocardial infarction overall by bibliometric analysis. Mesenchymal stem cells Therapy, MSCs-derived microRNA and genetic modified MSCs are the latest research frontiers. Related studies may pioneer the future direction of this filed in next few years. Further studies are needed.

Indexed as

Bibliometric analysisGeneticsMyocardial infarction

Identifiers

PMID29456889
PMCPMC5813587

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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.