Risk of bias and certainty of evidence on the association between obesity and mortality in patients with SARS-COV-2: An umbrella review of meta-analyses.
Clin Nutr ESPEN
; 53: 13-25, 2023 02.
Article
in English
| MEDLINE | ID: covidwho-1982809
ABSTRACT
BACKGROUND & AIMS:
This umbrella review of systematic reviews with meta-analysis (SR-MAs) aimed to evaluate the risk of bias and the certainty of the evidence of SR-MAs on the association between obesity and mortality in patients with SARS-CoV-2.METHODS:
We conducted a comprehensive literature search until April 22, 2022, in several databases and assessed the risk of bias of SR-MAs according to AMSTAR-2 and the certainty of evidence using the GRADE approach. The degree of overlap between meta-analyses was based on the corrected covered area (CCA) index. The results of each MA [relative risk (RR), hazard ratio (HR), or odds ratio (OR)] were extracted to evaluate the magnitude of the association between obesity and mortality.RESULTS:
A total of 24 SR-MAs were eligible, and the association between obesity and mortality was not statistically significant in eight (33.3%) of them, while the OR/HR/RR ranged from 1.14 to 3.52 in the other SR-MAs. The overlap was slight (CCA = 4.82%). The majority of SR-MAs presented critically low quality according to AMSTAR-2 (66.7%), and the certainty of the evidence for most of them (83.4%) was "very low".CONCLUSIONS:
Obesity was associated with an increased risk of death in patients with SARS-CoV-2 infection in most SR-MAs; however, a critical appraisal pointed to a high risk of bias, and the certainty of their evidence was not well graded. The dissemination of poor SR-MAs may limit the interpretation of findings, and we should always aspire to trustworthy scientific evidence. PROSPERO PROSPERO 2021 CRD42021253142.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
SARS-CoV-2
/
COVID-19
Type of study:
Experimental Studies
/
Prognostic study
/
Reviews
/
Systematic review/Meta Analysis
Topics:
Long Covid
Limits:
Humans
Language:
English
Journal:
Clin Nutr ESPEN
Year:
2023
Document Type:
Article
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