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A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery
BACKGROUND: Enhanced recovery after surgery (ERAS), a new clinical surgical concept, has been applied in many surgical disciplines with good clinical results for the past 20 years. Bibliometric analysis is an effective method to quantitatively evaluate the academic productivity. This report aimed to...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450939/ https://www.ncbi.nlm.nih.gov/pubmed/36090333 http://dx.doi.org/10.3389/fsurg.2022.894083 |
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author | Zhang, Mingjie Wang, Xiaoxue Chen, Xueting Song, Zixuan Wang, Yuting Zhou, Yangzi Zhang, Dandan |
author_facet | Zhang, Mingjie Wang, Xiaoxue Chen, Xueting Song, Zixuan Wang, Yuting Zhou, Yangzi Zhang, Dandan |
author_sort | Zhang, Mingjie |
collection | PubMed |
description | BACKGROUND: Enhanced recovery after surgery (ERAS), a new clinical surgical concept, has been applied in many surgical disciplines with good clinical results for the past 20 years. Bibliometric analysis is an effective method to quantitatively evaluate the academic productivity. This report aimed to perform a scientometric analysis of the ERAS research status and research hotspots. METHODS: Comprehensive scientific mapping analysis of a wide range of literature metadata using the scientometric tools, including the Bibliometrix R Package, Biblioshiny, and CiteSpace. Data were retrieved from the Web of Science Core Collection database of original articles from 2001 to 2020. Specific indicators and maps were analyzed to show the co-authorship, co-institute, co-country, co-citation, and international cooperation. Automatic literature screening, unsupervised cluster filtering, and topic cluster identification methods were used to display the conceptual framework and thematic evolution. RESULTS: A total of 1,403 research projects drafted by 6,966 authors and published in 413 sources were found. There was an exponential growth in the number of publications on ERAS. There were 709 collaborations between authors from different countries, and the US, China, and the UK had the greatest number of publications. The WORLD JOURNAL OF SURGERY, located in Bradford’s Law 1, had the highest number of published articles (n = 1,276; total citations = 3,193). CiteSpace network analysis revealed 15 highly correlated cluster ERAS studies, and the earliest study was on colonic surgery, and ERAS was recently applied in cardiac surgery. The etiology of ERAS is constantly evolving, with surgery and length of hospital as the main topics. Meta-analyses and perioperative care have tended to decline. CONCLUSION: This is the first scientometric analysis of ERAS to provide descriptive quantitative indicators. This can provide a better understanding of how the field has evolved over the past 20 years, help identify research trends, and provide insights and research directions for academic researchers, policymakers, and medical practitioners who want to collaborate in these areas in the future. |
format | Online Article Text |
id | pubmed-9450939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94509392022-09-08 A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery Zhang, Mingjie Wang, Xiaoxue Chen, Xueting Song, Zixuan Wang, Yuting Zhou, Yangzi Zhang, Dandan Front Surg Surgery BACKGROUND: Enhanced recovery after surgery (ERAS), a new clinical surgical concept, has been applied in many surgical disciplines with good clinical results for the past 20 years. Bibliometric analysis is an effective method to quantitatively evaluate the academic productivity. This report aimed to perform a scientometric analysis of the ERAS research status and research hotspots. METHODS: Comprehensive scientific mapping analysis of a wide range of literature metadata using the scientometric tools, including the Bibliometrix R Package, Biblioshiny, and CiteSpace. Data were retrieved from the Web of Science Core Collection database of original articles from 2001 to 2020. Specific indicators and maps were analyzed to show the co-authorship, co-institute, co-country, co-citation, and international cooperation. Automatic literature screening, unsupervised cluster filtering, and topic cluster identification methods were used to display the conceptual framework and thematic evolution. RESULTS: A total of 1,403 research projects drafted by 6,966 authors and published in 413 sources were found. There was an exponential growth in the number of publications on ERAS. There were 709 collaborations between authors from different countries, and the US, China, and the UK had the greatest number of publications. The WORLD JOURNAL OF SURGERY, located in Bradford’s Law 1, had the highest number of published articles (n = 1,276; total citations = 3,193). CiteSpace network analysis revealed 15 highly correlated cluster ERAS studies, and the earliest study was on colonic surgery, and ERAS was recently applied in cardiac surgery. The etiology of ERAS is constantly evolving, with surgery and length of hospital as the main topics. Meta-analyses and perioperative care have tended to decline. CONCLUSION: This is the first scientometric analysis of ERAS to provide descriptive quantitative indicators. This can provide a better understanding of how the field has evolved over the past 20 years, help identify research trends, and provide insights and research directions for academic researchers, policymakers, and medical practitioners who want to collaborate in these areas in the future. Frontiers Media S.A. 2022-06-08 /pmc/articles/PMC9450939/ /pubmed/36090333 http://dx.doi.org/10.3389/fsurg.2022.894083 Text en Copyright © 2022 Zhang, Wang, Chen, Song, Wang, Zhou and Zhang. 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) (https://creativecommons.org/licenses/by/4.0/) . 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 | Surgery Zhang, Mingjie Wang, Xiaoxue Chen, Xueting Song, Zixuan Wang, Yuting Zhou, Yangzi Zhang, Dandan A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery |
title | A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery |
title_full | A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery |
title_fullStr | A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery |
title_full_unstemmed | A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery |
title_short | A Scientometric Analysis and Visualization Discovery of Enhanced Recovery After Surgery |
title_sort | scientometric analysis and visualization discovery of enhanced recovery after surgery |
topic | Surgery |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450939/ https://www.ncbi.nlm.nih.gov/pubmed/36090333 http://dx.doi.org/10.3389/fsurg.2022.894083 |
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