The University of Southampton
University of Southampton Institutional Repository

Diabetes, obesity, hypertension and risk of severe COVID-19: a protocol for systematic review and meta-analysis

Diabetes, obesity, hypertension and risk of severe COVID-19: a protocol for systematic review and meta-analysis
Diabetes, obesity, hypertension and risk of severe COVID-19: a protocol for systematic review and meta-analysis
Introduction: previous evidence from several countries, including China, Italy, Mexico, UK and the USA, indicates that among patients with confirmed COVID-19 who were hospitalised, diabetes, obesity and hypertension might be important risk factors for severe clinical outcomes. Several preliminary systematic reviews and meta-analyses have been conducted on one or more of these non-communicable diseases, but the findings have not been definitive, and recent evidence has become available from many more populations. Thus, we aim to conduct a systematic review and meta-analysis of observational studies to assess the relationship of diabetes, obesity and hypertension with severe clinical outcomes in patients with COVID-19.

Method and analysis: we will search 16 major databases (MEDLINE, Embase, Global Health, CAB Abstracts, PsycINFO, CINAHL, Academic Research Complete, Africa Wide Information, Scopus, PubMed Central, ProQuest Central, WHO Virtual Health Library, Homeland Security COVID-19 collection, SciFinder, Clinical Trials and Cochrane Library) for articles published between December 2019 and December 2020. We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2016 guidelines for the design and reporting the results. We will include observational studies that assess the associations of pre-existing diabetes, obesity and hypertension in patients with COVID-19 with risk of severe clinical outcomes such as intensive care unit admission, receiving mechanical ventilation or death. Stata V.16.1 and R-Studio V.1.4.1103 statistical software will be used for statistical analysis. Meta-analysis will be used to estimate the pooled risks and to assess potential heterogeneities in risks.

Ethics and dissemination: the study was reviewed for human subjects concerns by the US CDC Center for Global Health and determined to not represent human subjects research because it uses data from published studies. We plan to publish results in a peer-reviewed journal and present at national and international conferences.
2044-6055
Li, Chaoyang
db9d2cb1-8e73-4915-8f4f-03ee1494854e
Islam, Nazrul
e5345196-7479-438f-b4f6-c372d2135586
Gutierrez, Juan Pablo
76cc8f18-01ca-4133-8097-90aff0a06591
Lacey, Ben
38227149-1faa-42d3-bf28-a9345d0c0872
Moolenaar, Ronald L
e6ab53a2-6025-4a4d-9514-30e1594624ba
Richter, Patricia
ae318b48-9a25-4edb-8d4c-0f44967b10f0
Li, Chaoyang
db9d2cb1-8e73-4915-8f4f-03ee1494854e
Islam, Nazrul
e5345196-7479-438f-b4f6-c372d2135586
Gutierrez, Juan Pablo
76cc8f18-01ca-4133-8097-90aff0a06591
Lacey, Ben
38227149-1faa-42d3-bf28-a9345d0c0872
Moolenaar, Ronald L
e6ab53a2-6025-4a4d-9514-30e1594624ba
Richter, Patricia
ae318b48-9a25-4edb-8d4c-0f44967b10f0

Li, Chaoyang, Islam, Nazrul, Gutierrez, Juan Pablo, Lacey, Ben, Moolenaar, Ronald L and Richter, Patricia (2021) Diabetes, obesity, hypertension and risk of severe COVID-19: a protocol for systematic review and meta-analysis. BMJ Open, 11 (11), [e051711]. (doi:10.1136/bmjopen-2021-051711).

Record type: Article

Abstract

Introduction: previous evidence from several countries, including China, Italy, Mexico, UK and the USA, indicates that among patients with confirmed COVID-19 who were hospitalised, diabetes, obesity and hypertension might be important risk factors for severe clinical outcomes. Several preliminary systematic reviews and meta-analyses have been conducted on one or more of these non-communicable diseases, but the findings have not been definitive, and recent evidence has become available from many more populations. Thus, we aim to conduct a systematic review and meta-analysis of observational studies to assess the relationship of diabetes, obesity and hypertension with severe clinical outcomes in patients with COVID-19.

Method and analysis: we will search 16 major databases (MEDLINE, Embase, Global Health, CAB Abstracts, PsycINFO, CINAHL, Academic Research Complete, Africa Wide Information, Scopus, PubMed Central, ProQuest Central, WHO Virtual Health Library, Homeland Security COVID-19 collection, SciFinder, Clinical Trials and Cochrane Library) for articles published between December 2019 and December 2020. We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2016 guidelines for the design and reporting the results. We will include observational studies that assess the associations of pre-existing diabetes, obesity and hypertension in patients with COVID-19 with risk of severe clinical outcomes such as intensive care unit admission, receiving mechanical ventilation or death. Stata V.16.1 and R-Studio V.1.4.1103 statistical software will be used for statistical analysis. Meta-analysis will be used to estimate the pooled risks and to assess potential heterogeneities in risks.

Ethics and dissemination: the study was reviewed for human subjects concerns by the US CDC Center for Global Health and determined to not represent human subjects research because it uses data from published studies. We plan to publish results in a peer-reviewed journal and present at national and international conferences.

Text
e051711.full - Version of Record
Available under License Creative Commons Attribution.
Download (426kB)

More information

Accepted/In Press date: 28 October 2021
Published date: 2021

Identifiers

Local EPrints ID: 470558
URI: http://eprints.soton.ac.uk/id/eprint/470558
ISSN: 2044-6055
PURE UUID: 5013c2a4-fb08-4097-a627-dc58cc46f69b
ORCID for Nazrul Islam: ORCID iD orcid.org/0000-0003-3982-4325

Catalogue record

Date deposited: 13 Oct 2022 16:30
Last modified: 17 Mar 2024 04:15

Export record

Altmetrics

Contributors

Author: Chaoyang Li
Author: Nazrul Islam ORCID iD
Author: Juan Pablo Gutierrez
Author: Ben Lacey
Author: Ronald L Moolenaar
Author: Patricia Richter

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×