Evidence map›Paper›PMID 37876436›Full record

ArticleHeliyon2023

Overprescription of antibiotics for treating hospitalized COVID-19 patients: A systematic review & meta-analysis.

Fazle Rabbi, Laura Banfield, Mehnaz Munir, Zain Chagla, Alexandra Mayhew, Russell J de Souza

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Fazle RabbiGlobal Health Graduate Programs, McMaster University, Hamilton, Ontario, Canada.
Laura BanfieldHealth Sciences Library, McMaster University, Hamilton, Ontario, Canada.
Mehnaz MunirGlobal Health Graduate Programs, McMaster University, Hamilton, Ontario, Canada.
Zain ChaglaFaculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada.
Alexandra MayhewDepartment of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada.
Russell J de SouzaGlobal Health Graduate Programs, McMaster University, Hamilton, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Empirical use of antibiotics was reported throughout the coronavirus disease of 2019 (COVID-19) pandemic; however, evidence of bacterial coinfection or secondary bacterial infection among COVID-19 patients was sparse. Antibiotic overprescription for COVID-19 patients without confirmed bacterial coinfection can increase antimicrobial resistance (AMR). The objective of this study is to assess the appropriateness of antibiotic use during COVID-19 by summarizing the frequency of antibiotic use among hospitalized COVID-19 and the frequency of antibiotic use in patients with COVID-19. Methods: A systematic search was conducted of the Embase, Medline, Web of Science, and Cochrane Library databases by generating search terms using the concepts of "COVID-19," "Bacterial Coinfection," "Secondary bacterial infection," and "Antimicrobial resistance" to identify studies reporting antibiotic prescription for hospitalized COVID-19 patients with or without bacterial coinfection. We excluded studies on outpatients, studies informed infection due to mechanical ventilation, and randomized controlled trials. The pooled estimate of the percentage of the total and confirmed appropriate antibiotic prescriptions provided to hospitalized COVID-19 patients was generated using a random effect meta-analysis with inverse variance weighting. The study protocol registration DOI is osf.io/d3fpm. Results: Of 157,623 participants from 29 studies (11 countries, 45 % women) included in our review, antibiotics were prescribed to 67 % of participants (CI 64 %-71 %, P < 0·001), of which 80 % (CI 76 %-83 %, P < 0·001) of prescriptions were for COVID-19 patients without confirmed bacterial coinfections. Antibiotic overprescription varied during different periods of the pandemic and between High-Income and Upper and Lower Middle-Income Countries. We found heterogeneity among the studies ( Discussion: We find greater than expected use of antibiotics to treat hospitalized COVID-19 patients without bacterial coinfections, which may contribute to AMR globally. Concrete guidelines for using antibiotics to treat COVID-19 patients, strict monitoring, and administering Antimicrobial Stewardship are needed to prevent overprescription.

Identifiers

PMID37876436
PMCPMC10590847

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.