Antimicrobial Use in COVID-19 Patients in the First Phase of the SARS-CoV-2 Pandemic: A Scoping Review

  1. Wenjuan Cong
  2. Ak Narayan Poudel
  3. Nour Alhusein
  4. Hexing Wang
  5. Guiqing Yao
  6. Helen Lambert

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Abstract

This scoping review provides new evidence on the prevalence and patterns of global antimicrobial use in the treatment of COVID-19 patients; identifies the most commonly used antibiotics and clinical scenarios associated with antibiotic prescribing in the first phase of the pandemic; and explores the impact of documented antibiotic prescribing on treatment outcomes in COVID-19 patients. The review complies with PRISMA guidelines for Scoping Reviews and the protocol is registered with the Open Science Framework. In the first six months of the pandemic, there was a similar mean antibiotic prescribing rate between patients with severe or critical illness (75.4%) and patients with mild or moderate illness (75.1%). The proportion of patients prescribed antibiotics without clinical justification was 51.5% vs. 41.9% for patients with mild or moderate illness and those with severe or critical illness. Comparison of patients who were provided antibiotics with a clinical justification with those who were given antibiotics without clinical justification showed lower mortality rates (9.5% vs. 13.1%), higher discharge rates (80.9% vs. 69.3%), and shorter length of hospital stay (9.3 days vs. 12.2 days). In the first 6 months of the pandemic, antibiotics were prescribed for COVID-19 patients regardless of severity of illness. A large proportion of antibiotic prescribing for mild and moderate COVID-19 patients did not have clinical evidence of a bacterial co-infection. Antibiotics may not be beneficial to COVID-19 patients without clinical evidence of a bacterial co-infection.

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  1. Version published to 10.3390/antibiotics10060745
  2. ScreenIT

    SciScore for 10.1101/2021.02.18.21251932: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: The following databases: Web of Science, EMBASE, PubMed and two Chinese academic databases (CNKI & VIP) were searched to identify relevant studies from 1 Dec 2019 up to 15 June 2020; no limits were set on the country where study was conducted, and we excluded any studies not available in English or Chinese.
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    In this review, data extraction and analysis were performed in Microsoft Excel.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This review and evidence synthesis also has several limitations. First, our search included five databases only. However, the inclusion of English and Chinese literature and search of reference list of eligible studies ensured that we were able to identify the majority of published studies. Due to the heterogeneity of the studies, meta-analysis was not conducted. However, the inclusion of a wide range of study designs may help in providing a complete picture of the global antibiotic prescribing patterns during the COVID-19 pandemic, which is lacking in the current scientific literature.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.02.18.21251932v1 on medRxiv