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. 2021 Sep:43:100910.
doi: 10.1016/j.nmni.2021.100910. Epub 2021 Jul 1.

Bacterial coinfection among coronavirus disease 2019 patient groups: an updated systematic review and meta-analysis

S Soltani  1   2 , S Faramarzi  3 , M Zandi  1   2 , R Shahbahrami  2 , A Jafarpour  2   4 , S Akhavan Rezayat  5 , I Pakzad  6 , F Abdi  7 , P Malekifar  8 , R Pakzad  9   10
Affiliations

Bacterial coinfection among coronavirus disease 2019 patient groups: an updated systematic review and meta-analysis

S Soltani et al. New Microbes New Infect. 2021 Sep.

Abstract

The pandemic of severe acute respiratory syndrome coronavirus 2 raised the attention towards bacterial coinfection and its role in coronavirus disease 2019 (COVID-19) disease. This study aims to systematically review and identify the pooled prevalence of bacterial coinfection in the related articles. A comprehensive search was conducted in international databases, including MEDLINE, Scopus, Web of Science, and Embase, to identify the articles on the prevalence of bacterial coinfections in COIVD-19 patients from 1 December 2019 until 30 December 2020. All observational epidemiological studies that evaluated the prevalence of bacterial coinfections in patients with COVID-19 were included without any restriction. Forty-two studies including a total sample size of 54,695 were included in the analysis. The pooled estimate for the prevalence of bacterial coinfections was 20.97% (95% CI: 15.95-26.46), and the pooled prevalence of bacterial coinfections was 5.20% (95% CI: 2.39-8.91) for respiratory subtype and 4.79% (95% CI: 0.11-14.61) for the gastrointestinal subtype. The pooled prevalence for Eastern Mediterranean Regional Office and South-East Asia Regional Office was 100% (95% CI: 82.35-100.00) and 2.61% (95% CI: 1.74-3.62). This rate of coinfection poses a great danger towards patients, especially those in critical condition. Although there are multiple complications and adverse effects related to extensive use of antibiotics to treat patients with COVID-19, it seems there is no other option except applying them, and it needs to be done carefully.

Keywords: COVID-19; Coinfection; coronavirus; meta-analysis; systematics review.

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Figures

Fig. 1
Fig. 1
PRISMA flow diagram of the process of study selection for analysis.
Fig. 2
Fig. 2
Forest plot for the prevalence of bacterial coinfections in patients with COVID-19 based on a random effects model. Each study identifies by the first author (year) and country. Each line segment's midpoint shows the prevalence estimate, length of line segment indicates 95% CI in each study, and diamond mark illustrates the pooled estimate.
Fig. 3
Fig. 3
Pooled prevalence with 95% CI and heterogeneity indices of bacterial coinfections in patients with COVID-19 based on the type of the bacteria, different regional places (AMRO: Regional Office of Americas; EURO: Regional Office for Europe; SEARO: Regional Office for South-East Asia; EMRO: Regional Office for the Eastern Mediterranean; WPRO; Regional Office for the Western Pacific) and the type of the study. The diamond mark illustrates the pooled prevalence, and the length of the diamond indicates the 95% CI. N is the number of the study in the analysis. The prevalence for EMRO (N = 1) was 100 % (95% CI: 82.35–100.00).
Fig. 4
Fig. 4
Association among prevalence of age (A) and sample size (B) with the prevalence of bacterial coinfections by means of meta-regression. The size of circles indicates the precision of each study. There is no significant association with respect to the prevalence of bacterial coinfections with age and sample size.
See this image and copyright information in PMC

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