Symptoms and signs of long COVID: A rapid review and meta-analysis.
Journal
Journal of global health
ISSN: 2047-2986
Titre abrégé: J Glob Health
Pays: Scotland
ID NLM: 101578780
Informations de publication
Date de publication:
21 May 2022
21 May 2022
Historique:
entrez:
21
5
2022
pubmed:
22
5
2022
medline:
25
5
2022
Statut:
epublish
Résumé
Long COVID is defined as symptoms and signs related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are present at least four weeks following acute infection. These symptoms and signs are poorly characterised but may be associated with significant morbidity. We sought to synthesise the evidence on their incidence to guide future research, policy and practice. We searched Medline and Embase for longitudinal cohort studies from January 2020 to July 2021 that investigated adults with long COVID at least four weeks after acute infection. Risk of bias was assessed using the Joanna Briggs Institute checklist for cohort studies. Random-effects meta-analyses were performed with subgroup analysis by follow-up time (4-12 vs more than 12 weeks). 19 studies were included, 13 of which included patients hospitalised with COVID-19. The total sample size was 10 643 and the follow-up time ranged from 30 to 340 days. Risk of bias was assessed as high in one study, moderate in two studies and low in the remaining 16 studies. The most common symptoms and signs seen at any time point in long COVID were fatigue (37%; 95% confidence interval (CI) = 23-55), dyspnoea (21%; 95% CI = 14-30), olfactory dysfunction (17%; 95% CI = 9-29), myalgia (12%; 95% CI = 5-25), cough (11%; 95% CI = 6-20) and gustatory dysfunction (10%; 95% CI = 7-17). High heterogeneity was seen for all meta-analyses and the presence of some funnel plot asymmetry may indicate reporting bias. No effect of follow-up time was found for any symptom or sign included in the subgroup analysis. We have summarised evidence from longitudinal cohort studies on the most common symptoms and signs associated with long COVID. High heterogeneity seen in the meta-analysis means pooled incidence estimates should be interpreted with caution. This heterogeneity may be attributable to studies including patients from different health care settings and countries.
Sections du résumé
Background
UNASSIGNED
Long COVID is defined as symptoms and signs related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are present at least four weeks following acute infection. These symptoms and signs are poorly characterised but may be associated with significant morbidity. We sought to synthesise the evidence on their incidence to guide future research, policy and practice.
Methods
UNASSIGNED
We searched Medline and Embase for longitudinal cohort studies from January 2020 to July 2021 that investigated adults with long COVID at least four weeks after acute infection. Risk of bias was assessed using the Joanna Briggs Institute checklist for cohort studies. Random-effects meta-analyses were performed with subgroup analysis by follow-up time (4-12 vs more than 12 weeks).
Results
UNASSIGNED
19 studies were included, 13 of which included patients hospitalised with COVID-19. The total sample size was 10 643 and the follow-up time ranged from 30 to 340 days. Risk of bias was assessed as high in one study, moderate in two studies and low in the remaining 16 studies. The most common symptoms and signs seen at any time point in long COVID were fatigue (37%; 95% confidence interval (CI) = 23-55), dyspnoea (21%; 95% CI = 14-30), olfactory dysfunction (17%; 95% CI = 9-29), myalgia (12%; 95% CI = 5-25), cough (11%; 95% CI = 6-20) and gustatory dysfunction (10%; 95% CI = 7-17). High heterogeneity was seen for all meta-analyses and the presence of some funnel plot asymmetry may indicate reporting bias. No effect of follow-up time was found for any symptom or sign included in the subgroup analysis.
Conclusions
UNASSIGNED
We have summarised evidence from longitudinal cohort studies on the most common symptoms and signs associated with long COVID. High heterogeneity seen in the meta-analysis means pooled incidence estimates should be interpreted with caution. This heterogeneity may be attributable to studies including patients from different health care settings and countries.
Identifiants
pubmed: 35596571
doi: 10.7189/jogh.12.05014
pmc: PMC9125197
doi:
Types de publication
Journal Article
Meta-Analysis
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
05014Subventions
Organisme : Chief Scientist Office
ID : COV/LTE/20/15
Pays : United Kingdom
Informations de copyright
Copyright © 2022 by the Journal of Global Health. All rights reserved.
Déclaration de conflit d'intérêts
Competing Interests: The authors completed the ICMJE Unified Competing Interest Form (available upon request from the corresponding author) and declare no conflicts of interest.
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