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Identifying common baseline clinical features of COVID-19: a scoping review

OBJECTIVES: Our research question was: what are the most frequent baseline clinical characteristics in adult patients with COVID-19? Our major aim was to identify common baseline clinical features that could help recognise adult patients at high risk of having COVID-19. DESIGN: We conducted a scopin...

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Autores principales: Ferreira-Santos, Daniela, Maranhão, Priscila, Monteiro-Soares, Matilde
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7496569/
https://www.ncbi.nlm.nih.gov/pubmed/32938604
http://dx.doi.org/10.1136/bmjopen-2020-041079
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author Ferreira-Santos, Daniela
Maranhão, Priscila
Monteiro-Soares, Matilde
author_facet Ferreira-Santos, Daniela
Maranhão, Priscila
Monteiro-Soares, Matilde
author_sort Ferreira-Santos, Daniela
collection PubMed
description OBJECTIVES: Our research question was: what are the most frequent baseline clinical characteristics in adult patients with COVID-19? Our major aim was to identify common baseline clinical features that could help recognise adult patients at high risk of having COVID-19. DESIGN: We conducted a scoping review of all the evidence available at LitCovid, until 23 March 2020. SETTING: Studies conducted in any setting and any country were included. PARTICIPANTS: Studies had to report the prevalence of sociodemographic characteristics, symptoms and comorbidities specifically in adults with a diagnosis of infection by SARS-CoV-2. RESULTS: In total, 1572 publications were published on LitCovid. We have included 56 articles in our analysis, with 89% conducted in China and 75% containing inpatients. Three studies were conducted in North America and one in Europe. Participants’ age ranged from 28 to 70 years, with balanced gender distribution. The proportion of asymptomatic cases were from 2% to 79%. The most common reported symptoms were fever (4%–99%), cough (4%–92%), dyspnoea/shortness of breath (1%–90%), fatigue (4%–89%), myalgia (3%–65%) and pharyngalgia (2%–61%), while regarding comorbidities, we found cardiovascular disease (1%–40%), hypertension (0%–40%) and cerebrovascular disease (1%–40%). Such heterogeneity impaired the conduction of meta-analysis. CONCLUSIONS: The infection by COVID-19 seems to affect people in a very diverse manner and with different characteristics. With the available data, it is not possible to clearly identify those at higher risk of being infected with this condition. Furthermore, the evidence from countries other than China is, at the moment, too scarce.
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spelling pubmed-74965692020-09-18 Identifying common baseline clinical features of COVID-19: a scoping review Ferreira-Santos, Daniela Maranhão, Priscila Monteiro-Soares, Matilde BMJ Open Epidemiology OBJECTIVES: Our research question was: what are the most frequent baseline clinical characteristics in adult patients with COVID-19? Our major aim was to identify common baseline clinical features that could help recognise adult patients at high risk of having COVID-19. DESIGN: We conducted a scoping review of all the evidence available at LitCovid, until 23 March 2020. SETTING: Studies conducted in any setting and any country were included. PARTICIPANTS: Studies had to report the prevalence of sociodemographic characteristics, symptoms and comorbidities specifically in adults with a diagnosis of infection by SARS-CoV-2. RESULTS: In total, 1572 publications were published on LitCovid. We have included 56 articles in our analysis, with 89% conducted in China and 75% containing inpatients. Three studies were conducted in North America and one in Europe. Participants’ age ranged from 28 to 70 years, with balanced gender distribution. The proportion of asymptomatic cases were from 2% to 79%. The most common reported symptoms were fever (4%–99%), cough (4%–92%), dyspnoea/shortness of breath (1%–90%), fatigue (4%–89%), myalgia (3%–65%) and pharyngalgia (2%–61%), while regarding comorbidities, we found cardiovascular disease (1%–40%), hypertension (0%–40%) and cerebrovascular disease (1%–40%). Such heterogeneity impaired the conduction of meta-analysis. CONCLUSIONS: The infection by COVID-19 seems to affect people in a very diverse manner and with different characteristics. With the available data, it is not possible to clearly identify those at higher risk of being infected with this condition. Furthermore, the evidence from countries other than China is, at the moment, too scarce. BMJ Publishing Group 2020-09-16 /pmc/articles/PMC7496569/ /pubmed/32938604 http://dx.doi.org/10.1136/bmjopen-2020-041079 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Epidemiology
Ferreira-Santos, Daniela
Maranhão, Priscila
Monteiro-Soares, Matilde
Identifying common baseline clinical features of COVID-19: a scoping review
title Identifying common baseline clinical features of COVID-19: a scoping review
title_full Identifying common baseline clinical features of COVID-19: a scoping review
title_fullStr Identifying common baseline clinical features of COVID-19: a scoping review
title_full_unstemmed Identifying common baseline clinical features of COVID-19: a scoping review
title_short Identifying common baseline clinical features of COVID-19: a scoping review
title_sort identifying common baseline clinical features of covid-19: a scoping review
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7496569/
https://www.ncbi.nlm.nih.gov/pubmed/32938604
http://dx.doi.org/10.1136/bmjopen-2020-041079
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