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COVID-19 meta-analyses: a scoping review and quality assessment.

Authors :
Natan Pires, Gabriel
Gomes Bezerra, Andréia
Baenningerde Oliveira, Thainá
Fen I Chen, Samuel
Apostolakis Malfatti, Victor Davis
Ferreira de Mello, Victoria Feiner
Niyama, Alyne
Selva Pinto, Vitor Luiz
Levy Andersen, Monica
Tufik, Sergio
Source :
Einstein (16794508). 2021, Vol. 19, p1-8. 8p.
Publication Year :
2021

Abstract

Objective: To carry out a scoping review of the meta-analyses published regarding about coronavirus disease 2019 (COVID-19), evaluating their main characteristics, publication trends and methodological quality. Methods: A bibliometric search was performed in PubMed®, Scopus and Web of Science, focusing on meta-analyses about COVID-2019 disease. Bibliometric and descriptive data for the included articles were extracted and the methodological quality of the included metaanalyses was evaluated using A Measurement Tool to Assess Systematic Reviews. Results: A total of 348 meta-analyses were considered eligible. The first meta-analysis about COVID-19 disease was published on February 26, 2020, and the number of meta-analyses has grown rapidly since then. Most of them were published in infectious disease and virology journals. The greatest number come from China, followed by the United States, Italy and the United Kingdom. On average, these meta-analyses included 23 studies and 15,200 participants. Overall quality was remarkably low, and only 8.9% of them could be considered as of high confidence level. Conclusion: Although welldesigned meta-analyses about COVID-19 disease have already been published, the majority are of low quality. Thus, all stakeholders playing a role in COVID-19 deseases, including policy makers, researchers, publishers and journals, should prioritize well-designed meta-analyses, performed only when the background information seem suitable, and discouraging those of low quality or that use suboptimal methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16794508
Volume :
19
Database :
Academic Search Index
Journal :
Einstein (16794508)
Publication Type :
Academic Journal
Accession number :
152803433
Full Text :
https://doi.org/10.31744/einstein_journal/2021AO6002