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Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis

INTRODUCTION: To map publication trends and explore research hotspots of insulin resistance (IR) in polycystic ovary syndrome (PCOS) study. METHODS: With the theme of “Polycystic ovary syndrome” AND “Insulin Resistance”, the key data set of Science Core Literature Collection (WoSCC) web from 2017 to...

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Detalles Bibliográficos
Autores principales: Chen, Yong, Zhang, Qian, Ma, Jinhui, Yu, Yuexin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797656/
https://www.ncbi.nlm.nih.gov/pubmed/36589816
http://dx.doi.org/10.3389/fendo.2022.963213
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author Chen, Yong
Zhang, Qian
Ma, Jinhui
Yu, Yuexin
author_facet Chen, Yong
Zhang, Qian
Ma, Jinhui
Yu, Yuexin
author_sort Chen, Yong
collection PubMed
description INTRODUCTION: To map publication trends and explore research hotspots of insulin resistance (IR) in polycystic ovary syndrome (PCOS) study. METHODS: With the theme of “Polycystic ovary syndrome” AND “Insulin Resistance”, the key data set of Science Core Literature Collection (WoSCC) web from 2017 to 2021 was extracted and bibliometric analysis was performed. Through VOSviewer v1.6.10 software, the research trend in this field is analyzed visually. RESULTS: 2080 literatures about IR in PCOS from 2017 to 2021 were downloaded. The following basic information was collected for each article: country, author, institution, journal, references. The key words are divided into six categories: (1) The interaction between insulin resistance and chronic inflammation; (2) The relationship between insulin resistance and metabolic syndrome and nonalcoholic fatty liver disease; (3) The interaction between insulin resistance and hyperandrogenemia; (4) The relationship between insulin resistance and dyslipidemia; (5) Metformin may regulate insulin resistance in the treatment of PCOS; (6) The study of serum biomarkers in PCOS patients with insulin resistance. DISCUSSION: The six key words extracted can provide an in-depth perspective for the study of IR in PCOS, and provide valuable information to help researchers identify potential research directions, collaborators and cooperative institutions.
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spelling pubmed-97976562022-12-30 Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis Chen, Yong Zhang, Qian Ma, Jinhui Yu, Yuexin Front Endocrinol (Lausanne) Endocrinology INTRODUCTION: To map publication trends and explore research hotspots of insulin resistance (IR) in polycystic ovary syndrome (PCOS) study. METHODS: With the theme of “Polycystic ovary syndrome” AND “Insulin Resistance”, the key data set of Science Core Literature Collection (WoSCC) web from 2017 to 2021 was extracted and bibliometric analysis was performed. Through VOSviewer v1.6.10 software, the research trend in this field is analyzed visually. RESULTS: 2080 literatures about IR in PCOS from 2017 to 2021 were downloaded. The following basic information was collected for each article: country, author, institution, journal, references. The key words are divided into six categories: (1) The interaction between insulin resistance and chronic inflammation; (2) The relationship between insulin resistance and metabolic syndrome and nonalcoholic fatty liver disease; (3) The interaction between insulin resistance and hyperandrogenemia; (4) The relationship between insulin resistance and dyslipidemia; (5) Metformin may regulate insulin resistance in the treatment of PCOS; (6) The study of serum biomarkers in PCOS patients with insulin resistance. DISCUSSION: The six key words extracted can provide an in-depth perspective for the study of IR in PCOS, and provide valuable information to help researchers identify potential research directions, collaborators and cooperative institutions. Frontiers Media S.A. 2022-12-15 /pmc/articles/PMC9797656/ /pubmed/36589816 http://dx.doi.org/10.3389/fendo.2022.963213 Text en Copyright © 2022 Chen, Zhang, Ma and Yu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Chen, Yong
Zhang, Qian
Ma, Jinhui
Yu, Yuexin
Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis
title Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis
title_full Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis
title_fullStr Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis
title_full_unstemmed Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis
title_short Mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: A bibliometric analysis
title_sort mapping research trends of insulin resistance in polycystic ovary syndrome from 2017 to 2021: a bibliometric analysis
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797656/
https://www.ncbi.nlm.nih.gov/pubmed/36589816
http://dx.doi.org/10.3389/fendo.2022.963213
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