Evidence map›Paper›PMID 39371961›Full record

ArticleClinical medicine insights. Endocrinology and diabetes2024

Bibliometric Analysis of ncRNA Studies in Diabetes Mellitus With Coronary Heart Disease: A Visualization Approach.

Yu'e Tang, Rifang Gu, Jidong Rong, Xuqiang Nie

Abstract read
In one paragraph

Article in Clinical medicine insights. Endocrinology and diabetes, 2024. 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
–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

0 citing papers in PubMed.

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

4 authors.

Yu'e TangSchool of Clinical Medicine, Zunyi Medical University, Zunyi, China.
Rifang GuUniversity Medical Office, Zunyi Medical University, Zunyi, China.
Jidong RongDepartment of Cardiology, The Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Xuqiang NieKey Laboratory of Basic Pharmacalogy of Ministry of Education and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi, China.ORCID https://orcid.org/0000-0002-6926-6515

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Non-coding RNA (ncRNA) plays a role in the development of diabetes and coronary heart disease. However, there is limited research on the association between ncRNA and these conditions. This study aims to conduct a bibliometric analysis and visualization of existing research to provide a comprehensive reference for future investigation in this field. Methods: We searched the China National Knowledge Infrastructure (CNKI) and Web of Science Core Collection (WoSCC) databases for articles published from 2012 to 2024. We analyzed publication volume, country of origin, authors, and keywords using Microsoft Office Excel, CiteSpace, and VOSviewer. Results: A total of 414 papers from 56 countries/regions, involving 298 authors, were analyzed. China had the highest number of publications (177), followed by the USA (90) and Italy (28). The number of publications generally shows an increasing trend. Collaborative research efforts were prevalent, with Katare Rajesh being the most cited author on average. Conclusion: Research on ncRNA in the context of diabetes and coronary heart disease has made notable strides, although it warrants further exploration. Through bibliometric and visual analysis, we elucidate the collaborative relationships among researchers, which can facilitate the identification of potential collaborators. Additionally, we delineate the key areas and emergent trends in this field, providing valuable insights that can guide researchers in selecting future research directions.

Indexed as

bibliometricscircular RNAsdiabetes mellitus with coronary heart diseaselong non-coding RNAsmicroRNAsNoncoding RNA

Identifiers

PMID39371961
PMCPMC11456197

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.