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COVID-19-related medical research: a meta-research and critical appraisal
BACKGROUND: Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-review...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780085/ https://www.ncbi.nlm.nih.gov/pubmed/33397292 http://dx.doi.org/10.1186/s12874-020-01190-w |
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author | Raynaud, Marc Zhang, Huanxi Louis, Kevin Goutaudier, Valentin Wang, Jiali Dubourg, Quentin Wei, Yongcheng Demir, Zeynep Debiais, Charlotte Aubert, Olivier Bouatou, Yassine Lefaucheur, Carmen Jabre, Patricia Liu, Longshan Wang, Changxi Jouven, Xavier Reese, Peter Empana, Jean-Philippe Loupy, Alexandre |
author_facet | Raynaud, Marc Zhang, Huanxi Louis, Kevin Goutaudier, Valentin Wang, Jiali Dubourg, Quentin Wei, Yongcheng Demir, Zeynep Debiais, Charlotte Aubert, Olivier Bouatou, Yassine Lefaucheur, Carmen Jabre, Patricia Liu, Longshan Wang, Changxi Jouven, Xavier Reese, Peter Empana, Jean-Philippe Loupy, Alexandre |
author_sort | Raynaud, Marc |
collection | PubMed |
description | BACKGROUND: Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles. METHODS: The data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools. RESULTS: Among the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37–337). CONCLUSIONS: Since the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/5zjyx/ SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-020-01190-w. |
format | Online Article Text |
id | pubmed-7780085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77800852021-01-04 COVID-19-related medical research: a meta-research and critical appraisal Raynaud, Marc Zhang, Huanxi Louis, Kevin Goutaudier, Valentin Wang, Jiali Dubourg, Quentin Wei, Yongcheng Demir, Zeynep Debiais, Charlotte Aubert, Olivier Bouatou, Yassine Lefaucheur, Carmen Jabre, Patricia Liu, Longshan Wang, Changxi Jouven, Xavier Reese, Peter Empana, Jean-Philippe Loupy, Alexandre BMC Med Res Methodol Research Article BACKGROUND: Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles. METHODS: The data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools. RESULTS: Among the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37–337). CONCLUSIONS: Since the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/5zjyx/ SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-020-01190-w. BioMed Central 2021-01-04 /pmc/articles/PMC7780085/ /pubmed/33397292 http://dx.doi.org/10.1186/s12874-020-01190-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Raynaud, Marc Zhang, Huanxi Louis, Kevin Goutaudier, Valentin Wang, Jiali Dubourg, Quentin Wei, Yongcheng Demir, Zeynep Debiais, Charlotte Aubert, Olivier Bouatou, Yassine Lefaucheur, Carmen Jabre, Patricia Liu, Longshan Wang, Changxi Jouven, Xavier Reese, Peter Empana, Jean-Philippe Loupy, Alexandre COVID-19-related medical research: a meta-research and critical appraisal |
title | COVID-19-related medical research: a meta-research and critical appraisal |
title_full | COVID-19-related medical research: a meta-research and critical appraisal |
title_fullStr | COVID-19-related medical research: a meta-research and critical appraisal |
title_full_unstemmed | COVID-19-related medical research: a meta-research and critical appraisal |
title_short | COVID-19-related medical research: a meta-research and critical appraisal |
title_sort | covid-19-related medical research: a meta-research and critical appraisal |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780085/ https://www.ncbi.nlm.nih.gov/pubmed/33397292 http://dx.doi.org/10.1186/s12874-020-01190-w |
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