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Methodological assessment of systematic reviews and meta-analyses on COVID-19: A meta-epidemiological study.
Rosenberger, Kristine J; Xu, Chang; Lin, Lifeng.
  • Rosenberger KJ; Department of Statistics, Florida State University, Tallahassee, Florida, USA.
  • Xu C; Department of Population Medicine, College of Medicine, Qatar University, Doha, Qatar.
  • Lin L; Department of Statistics, Florida State University, Tallahassee, Florida, USA.
J Eval Clin Pract ; 27(5): 1123-1133, 2021 10.
Article in English | MEDLINE | ID: covidwho-1218146
ABSTRACT
RATIONALE, AIMS, AND

OBJECTIVES:

COVID-19 has caused an ongoing public health crisis. Many systematic reviews and meta-analyses have been performed to synthesize evidence for better understanding this new disease. However, some concerns have been raised about rapid COVID-19 research. This meta-epidemiological study aims to methodologically assess the current systematic reviews and meta-analyses on COVID-19.

METHODS:

We searched in various databases for systematic reviews with meta-analyses published between 1 January 2020 and 31 October 2020. We extracted their basic characteristics, data analyses, evidence appraisal, and assessment of publication bias and heterogeneity.

RESULTS:

We identified 295 systematic reviews on COVID-19. The median time from submission to acceptance was 33 days. Among these systematic reviews, 73.9% evaluated clinical manifestations or comorbidities of COVID-19. Stata was the most used software programme (43.39%). The odds ratio was the most used effect measure (34.24%). Moreover, 28.14% of the systematic reviews did not present evidence appraisal. Among those reporting the risk of bias results, 14.64% of studies had a high risk of bias. Egger's test was the most used method for assessing publication bias (38.31%), while 38.66% of the systematic reviews did not assess publication bias. The I2 statistic was widely used for assessing heterogeneity (92.20%); many meta-analyses had high values of I2 . Among the meta-analyses using the random-effects model, 75.82% did not report the methods for model implementation; among those meta-analyses reporting implementation methods, the DerSimonian-Laird method was the most used one.

CONCLUSIONS:

The current systematic reviews and meta-analyses on COVID-19 might suffer from low transparency, high heterogeneity, and suboptimal statistical methods. It is recommended that future systematic reviews on COVID-19 strictly follow well-developed guidelines. Sensitivity analyses may be performed to examine how the synthesized evidence might depend on different methods for appraising evidence, assessing publication bias, and implementing meta-analysis models.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: J Eval Clin Pract Journal subject: Health Services Research Year: 2021 Document Type: Article Affiliation country: Jep.13578

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: J Eval Clin Pract Journal subject: Health Services Research Year: 2021 Document Type: Article Affiliation country: Jep.13578