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Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends
One of the main causes of death is out-of-hospital cardiac arrest (OHCA), which has a poor prognosis and poor neurological outcomes. This phenomenon has attracted increasing attention. However, there is still no published bibliometric analysis of OHCA. This bibliometric analysis of publications on O...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443760/ https://www.ncbi.nlm.nih.gov/pubmed/37603499 http://dx.doi.org/10.1097/MD.0000000000034783 |
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author | Li, Yue Li, Zhaoying Li, Chunjie Cai, Wei Liu, Tao Li, Ji Fan, Haojun Cao, Chunxia |
author_facet | Li, Yue Li, Zhaoying Li, Chunjie Cai, Wei Liu, Tao Li, Ji Fan, Haojun Cao, Chunxia |
author_sort | Li, Yue |
collection | PubMed |
description | One of the main causes of death is out-of-hospital cardiac arrest (OHCA), which has a poor prognosis and poor neurological outcomes. This phenomenon has attracted increasing attention. However, there is still no published bibliometric analysis of OHCA. This bibliometric analysis of publications on OHCA aimed to visualize the current status of research, determine the frontiers of research, and identify future trends. Publications on OHCA were downloaded from the web of science database. The data elements included year, countries/territories, institutions, authors, journals, research areas, citations of publications, etc. Joinpoint regression and exponential models were used to identify and predict the trend of publications, respectively. Knowledge domain maps were applied to conduct contribution and collaboration, cooccurrence, cocitation, and coupled analyses. Timeline and burst detection analysis were used to identify the frontiers in the field. A total of 3 219 publications on OHCA were found from 1998 to 2022 (average annual percentage change = 16.7; 95% CI 14.4, 19.1). It was estimated that 859 articles and reviews would be published in 2025. The following research hotpots were identified: statement, epidemiology, clinical care, factors influencing prognosis and emergency medical services. The research frontier identification revealed that 7 categories were classified, including therapeutic hypothermia, emergency medical services, airway management, myocardial infarction, extracorporeal cardiopulmonary resuscitation, stroke foundation and trial. The burst detection analysis revealed that percutaneous coronary intervention, neurologic outcome, COVID-19 and extracorporeal cardiopulmonary resuscitation are issues that should be given continual attention in the future. This bibliometric analysis may reflect the current status and future frontiers of OHCA research. |
format | Online Article Text |
id | pubmed-10443760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-104437602023-08-23 Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends Li, Yue Li, Zhaoying Li, Chunjie Cai, Wei Liu, Tao Li, Ji Fan, Haojun Cao, Chunxia Medicine (Baltimore) 3400 One of the main causes of death is out-of-hospital cardiac arrest (OHCA), which has a poor prognosis and poor neurological outcomes. This phenomenon has attracted increasing attention. However, there is still no published bibliometric analysis of OHCA. This bibliometric analysis of publications on OHCA aimed to visualize the current status of research, determine the frontiers of research, and identify future trends. Publications on OHCA were downloaded from the web of science database. The data elements included year, countries/territories, institutions, authors, journals, research areas, citations of publications, etc. Joinpoint regression and exponential models were used to identify and predict the trend of publications, respectively. Knowledge domain maps were applied to conduct contribution and collaboration, cooccurrence, cocitation, and coupled analyses. Timeline and burst detection analysis were used to identify the frontiers in the field. A total of 3 219 publications on OHCA were found from 1998 to 2022 (average annual percentage change = 16.7; 95% CI 14.4, 19.1). It was estimated that 859 articles and reviews would be published in 2025. The following research hotpots were identified: statement, epidemiology, clinical care, factors influencing prognosis and emergency medical services. The research frontier identification revealed that 7 categories were classified, including therapeutic hypothermia, emergency medical services, airway management, myocardial infarction, extracorporeal cardiopulmonary resuscitation, stroke foundation and trial. The burst detection analysis revealed that percutaneous coronary intervention, neurologic outcome, COVID-19 and extracorporeal cardiopulmonary resuscitation are issues that should be given continual attention in the future. This bibliometric analysis may reflect the current status and future frontiers of OHCA research. Lippincott Williams & Wilkins 2023-08-18 /pmc/articles/PMC10443760/ /pubmed/37603499 http://dx.doi.org/10.1097/MD.0000000000034783 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | 3400 Li, Yue Li, Zhaoying Li, Chunjie Cai, Wei Liu, Tao Li, Ji Fan, Haojun Cao, Chunxia Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends |
title | Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends |
title_full | Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends |
title_fullStr | Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends |
title_full_unstemmed | Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends |
title_short | Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends |
title_sort | out-of-hospital cardiac arrest: a data-driven visualization of collaboration, frontier identification, and future trends |
topic | 3400 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443760/ https://www.ncbi.nlm.nih.gov/pubmed/37603499 http://dx.doi.org/10.1097/MD.0000000000034783 |
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