Mortality and use of angiotensin-converting enzyme inhibitors in COVID 19 disease: a systematic review

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Abstract

Background:

Interest exists concerning the use of angiotensin-converting enzyme inhibitors (ACEis) in patients with COVID-19 disease.

Objectives:

The aim of the study was to perform a systematic review on mortality associated to the use of ACEi in patients with COVID-19 disease.

Methods:

Search in Medline (PubMed), in ISI Web of Knowledge and in medRxiv database; use of other sources.

Results:

A total of 33 articles were evaluated. Concerning the papers used to produce the meta-analyses, 7 studies were selected, 5 of which were used. These 5 studies involved a total number of 944 patients treated with ACEi and 5173 not treated with ACEi. Increased mortality was seen in association to the use of ACEi in the context of COVID-19 disease (ACEi users vs nonusers; odds ratio, 1.48; 95% confidence interval, 1.02–2.15; P  = .04). When compared to mortality in patients treated with angiotensin receptor blockers, mortality of patients treated with ACEi was not significantly different (odds ratio, 0.96; 95% confidence interval, 0.76–1.21; P  = .74). Concerning the remaining reports, different types of data adjustments were used by several authors, after which increased mortality was not seen in association to the use of ACEi in this context.

Conclusions:

ACEi use could act as a marker of increased mortality risk in some but not all COVID-19 disease settings. The data now presented do not prove a causal relation but argue in favor of carrying out clinical trials studying ACEi in COVID-19 patients, to establish the safety of ACEi use in this context.

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  1. SciScore for 10.1101/2020.05.29.20116483: (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 study started with a search on Medline (PubMed), in ISI Web of Knowledge and in medRxiv databases, using the query “Covid-19” AND
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.