ReviewEnvironmental sustainability (Singapore)2021
Antibacterial agents used in COVID-19: A systematic review and meta-analysis.
Review in Environmental sustainability (Singapore), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Antibiotics for the treatment of COVID-19.The Cochrane database of systematic reviews · 2021Pooled it
- Human Antimicrobial Use in Bangladesh: Five-Year Trend Analysis Including COVID-19 Pandemic Era.Antibiotics (Basel, Switzerland) · 2025Article
- Personal Care Products as a Contributing Factor to Antimicrobial Resistance: Current State and Novel Approach to Investigation.Antibiotics (Basel, Switzerland) · 2023Review
- Azithromycin use and outcomes in patients with COVID-19: an observational real-world study.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Observational
- Substituted Imidazole Carboxamides as Novel Antibacterial Agents.ACS medicinal chemistry letters · 2022Article
- Article
- Azithromycin Misuse During the COVID-19 Pandemic: A Cross-Sectional Study from Jordan.Infection and drug resistance · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There have been speculations regarding rise in antimicrobial resistance (AMR) globally owing to indiscriminate antibiotic usage during the COVID-19 pandemic. To curb the menace through decisive policies, it is essential to assess the antibiotics, particularly the antibacterial agents. This systematic review and meta-analysis were performed to assess antibiotic use in COVID-19 patients. A thorough systematic search was undertaken in databases like PubMed, Cochrane library, Google Scholar, World Health Organization (WHO) database and clinicaltrials.gov by two independent reviewers for articles in English published from January 1, 2019 to October 31, 2020. Studies were included if they assessed confirmed COVID-19 cases and mentioned the use of antibiotics. The primary outcome was the proportion of COVID-19 patients subjected to specific antibacterial agents. An attempt to stratify the data based on study settings and disease severity was also performed. Of the total 6012 studies screened, 40 were eligible for qualitative review and 19 for meta-analysis. Specific antibacterial agents were mentioned in 23 studies (57.5%). In the random effect meta-analysis, pooled prevalence of azithromycin use was 24.5% (95% CI 22.9-26.2%) followed by cephalosporins as 26.6% (95% CI 24.9-28.4). None of the studies clearly specified indications for antibiotic use. Ten studies (25%) mentioned empirical use of antibiotics. Bacterial co-infections/secondary infections were documented in four studies with mean prevalence of infection of 1.9% (95% CI 1.2-2.8%). There is lack of data on use of specific antibacterial agents, indications for their use based on severity of infections and microbiological evidence of bacterial co-infections.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.