An umbrella review and meta-analysis of the use of renin-angiotensin system drugs and COVID-19 outcomes: what do we know so far?

  1. Amanj Kurdi
  2. Natalie Weir
  3. Tanja Mueller

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Abstract

Backgrounds

Evidence from several meta-analyses are still controversial about the effects of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin-receptor blockers (ARBs) on COVID-19 outcomes.

Purpose

Umbrella review of systematic reviews/meta-analysis to provide comprehensive assessment of the effect of ACEIs/ARBs on COVID-19 related outcomes by summarising the currently available evidence.

Data Source

Medline (OVID), Embase, Scopus, Cochrane library and medRxiv from inception to 1 st February 2021.

Study Selection

Systematic reviews with meta-analysis that evaluated the effect of ACEIs/ARBs on COVID-19 related clinical outcomes

Data Extraction

Two reviewers independently extracted the data and assessed studies’ risk of bias using AMSTAR 2 Critical Appraisal Tool.

Data Synthesis

Pooled estimates were combined using the random-effects meta-analyses model including several sub-group analyses. Overall, 47 reviews were eligible for inclusion. Out of the nine COVID-19 outcomes evaluated, there was significant associations between ACEIs/ARBs use and each of death (OR=0.80, 95%CI=0.75-0.86; I 2 =51.9%), death/ICU admission as composite outcome (OR=0.86, 95%CI=0.80-0.92; I 2 =43.9%), severe COVID-19 (OR=0.86, 95%CI=0.78-0.95; I 2 =68%), and hospitalisation (OR=1.23, 95%CI=1.04-1.46; I 2 = 76.4%). The significant reduction in death/ICU admission, however, was higher among studies which presented adjusted measure of effects (OR=0.63, 95%CI=0.47-0.84) and were of moderate quality (OR=0.74, 95%CI=0.63-0.85).

Limitations

The effect of unmeasured confounding could not be ruled out. Only 21.3% (n=10) of the studies were of ‘moderate’ quality.

Conclusion

Collective evidence from observational studies indicate a good quality evidence on the significant association between ACEIs/ARBs use and reduction in death and death/ICU admission, but poor-quality evidence on both reducing severe COVID-19 and increasing hospitalisation. Our findings further support the current recommendations of not discontinuing ACEIs/ARBs therapy in patients with COVID-19.

Registration

The study protocol was registered in PROSPERO (CRD42021233398).

Funding Source

None

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  1. ScreenIT

    SciScore for 10.1101/2022.03.20.22272664: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationTo ensure consistency in the study selection process 10% of the articles’ titles/abstracts and full texts were randomly selected and screened independently by two researchers (NW and TM).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: The databases Medline
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    , EMBASE, Scopus, Cochrane, and medRxiv were searched in February 2021.
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Cochrane
    suggested: (Cochrane Library, RRID:SCR_013000)
    Article selection: Article selection was conducted using Covidence software (9).
    Covidence
    suggested: (Covidence, RRID:SCR_016484)
    Data extraction: Data were extracted from the reviews using Microsoft Excel.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Data were analysed using STATA 12.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    Strengths and limitations: This review presents the most comprehensive and systematic overview on the impact using RAAS inhibitors on COVID-19 related clinical outcomes, with a wide range of sensitivity (sub-group) analyses to assess the strength, validity and robustness of the evidence while accounting for potential confounding variables. Furthermore, none of the pooled meta-analysis estimates for the nine studied outcomes was affected/dominated by a single individual study. Although most of the included studies were classified as ‘low’ or ‘critically low’ quality when assessed using AMSTAR 2 tool, it is widely acknowledged that the AMSTAR 2 tool has a high standard with most reviews rated as ‘critically low’ (69, 70). The AMSTAR 2 tool is also prone to subjective biases (71), and assessment results are at the discretion of the reviewers regarding what is a “comprehensive” literature search or “satisfactory” explanation of heterogeneity or risk of bias assessment (71); therefore, quality assessment was conducted fully independent in this review and further criteria were set by the assessors to ensure inter-rater consistency. Alternatives tools to AMSTAR 2 exist such as the ROBIS tool, however the measurement categories are found to be broadly similar with the AMSTAR 2 tool considered more reliable (71). Additionally, we accounted for this issue by conducting a sub-group analysis based on the level of studies’ quality.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  2. Version published to 10.1101/2022.03.20.22272664v1 on medRxiv