TY - JOUR
T1 - Characterisation of the long-term physical and mental health consequences of SARSCoV- 2 infection
T2 - A systematic review and meta-analysis protocol
AU - Kuodi, Paul
AU - Gorelik, Yanay
AU - Edelstein, Michael
N1 - Publisher Copyright:
Copyright © 2022 Kuodi et al.
PY - 2022/4
Y1 - 2022/4
N2 - Background: As of July 2021, there has been more than 185 million documented cases of the novel coronavirus (SARS-CoV-2) infections and more than 4 million deaths globally. Despite more than 90% of documented cases being classified as "recovered"from SARS-CoV-2 infection, a proportion of patients reported a wide variety of persisting symptoms after the initial onset or acute phase of the infection, often referred to as "Long Covid". As data on the symptomatology of post-acute SARS-CoV-2 infection gradually becomes available, there is an urgent need to organise and synthesise the data in order to define what constitutes Long Covid and assist with its management in clinical and community settings. Methods: This protocol follows the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA-P) guidelines. A comprehensive literature search strategy will be developed in accordance with the Cochrane highly sensitive search guidelines. The following electronic databases will be searched for studies to include in the systematic review and meta-analysis: MEDLINE (via PubMed), Scopus, Google Scholar, Web of Science (Web of Knowledge), Science direct, EMBASE, Mednar, Psych INFO, and EBSCOhost. Dual screening will be applied at every screening stage. Two reviewers will independently screen titles, abstracts and full text of potentially eligible studies following the predefined inclusion and exclusion criteria in order to select studies to include in the review. As heterogeneity is anticipated between the included studies, data will be pooled in a meta-analysis using a random effects model. A clustering analytic approach will be applied to identify symptoms groupings and assign the symptoms into clusters. R statistical software will be used for the meta-analysis. Highly heterogenous data will be synthesised narratively. The studies will be assessed, for quality using quality assessment tools appropriate for each study design. Two reviewers will independently undertake the quality of studies assessments. Dissemination plans: Findings of the systematic review will be disseminated through a peer-reviewed publication and presentation of findings at conferences, workshops and government and private sector stakeholder engagement meetings.
AB - Background: As of July 2021, there has been more than 185 million documented cases of the novel coronavirus (SARS-CoV-2) infections and more than 4 million deaths globally. Despite more than 90% of documented cases being classified as "recovered"from SARS-CoV-2 infection, a proportion of patients reported a wide variety of persisting symptoms after the initial onset or acute phase of the infection, often referred to as "Long Covid". As data on the symptomatology of post-acute SARS-CoV-2 infection gradually becomes available, there is an urgent need to organise and synthesise the data in order to define what constitutes Long Covid and assist with its management in clinical and community settings. Methods: This protocol follows the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA-P) guidelines. A comprehensive literature search strategy will be developed in accordance with the Cochrane highly sensitive search guidelines. The following electronic databases will be searched for studies to include in the systematic review and meta-analysis: MEDLINE (via PubMed), Scopus, Google Scholar, Web of Science (Web of Knowledge), Science direct, EMBASE, Mednar, Psych INFO, and EBSCOhost. Dual screening will be applied at every screening stage. Two reviewers will independently screen titles, abstracts and full text of potentially eligible studies following the predefined inclusion and exclusion criteria in order to select studies to include in the review. As heterogeneity is anticipated between the included studies, data will be pooled in a meta-analysis using a random effects model. A clustering analytic approach will be applied to identify symptoms groupings and assign the symptoms into clusters. R statistical software will be used for the meta-analysis. Highly heterogenous data will be synthesised narratively. The studies will be assessed, for quality using quality assessment tools appropriate for each study design. Two reviewers will independently undertake the quality of studies assessments. Dissemination plans: Findings of the systematic review will be disseminated through a peer-reviewed publication and presentation of findings at conferences, workshops and government and private sector stakeholder engagement meetings.
UR - http://www.scopus.com/inward/record.url?scp=85127647735&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0266232
DO - 10.1371/journal.pone.0266232
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C2 - 35381027
AN - SCOPUS:85127647735
SN - 1932-6203
VL - 17
JO - PLoS ONE
JF - PLoS ONE
IS - 4 April
M1 - e0266232
ER -