The effect of angiotensin converting enzyme inhibitors and angiotensin receptor blockers on death and severity of disease in patients with coronavirus disease 2019 (COVID-19): A meta-analysis

  1. S Ghosal
  2. Jagat J Mukherjee
  3. B Sinha
  4. K Gangopadhyay

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Abstract

Aims and Methods

Effect of angiotensin converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB) on outcomes in patients with coronavirus disease 2019 (COVID-19) is uncertain. Available evidence is limited to a few retrospective observational studies with small number of patients. We did a meta-analysis to assess the effect of ACEi/ARB in patients with COVID-19 on severity of disease, risk for hospitalisation, and death compared to those not on ACEi/ARB. We searched the Cochrane library, PubMed, Embase, ClinicalTrial.gov and medRxiv for studies published until 25.04.2020. Inclusion criteria included all studies with patients with confirmed COVID-19 either taking, or not taking, ACEi/ARB. Depending on degree of heterogeneity, fixed or random effect model was selected to calculate effect size (Odds ratio).

Results

Six studies were eligible for this meta-analysis. These included 423 patients on ACEi/ARB, and 1419 not on ACEi/ARB. Compared to patients with COVID-19 not on ACEi/ARB, there was a statistically significant 43% reduction (OR 0.57, CI: 0.37–0.88, I 2 : 0.000) in the odds of death in those on ACEi/ARB. There was a statistically non-significant 38% reduction (OR: 0.62, 95% CI: 0.31–1.23, I 2 =70.36) in the odds of developing severe disease and 19% reduction (OR 0.81; 95% CI: 0.42–1.55, I 2 : 0.000) in the odds of hospitalisation among those on ACEi/ARB.

Discussion

It is safe to use ACEi/ARB in patients with COVID-19 requiring these medications for associated comorbidities. Although limited by confounding factors typical of a meta-analysis of retrospective observational studies, our data suggests that use of these medications may reduce the odds of death.

Conclusion

Our meta-analysis of the updated studies on SARS-CoV-2 reassures the medical fraternity on the use of and continuation of ACEi/ARB, supporting all recent recommendations.

Evidence before this study

  • The postulated dual role of angiotensin-converting enzyme (ACE) inhibitors (ACEi) and angiotensin receptor blockers (ARB) in patients with coronavirus disease 2019 (COVID-19) has created a dilemma for clinicians.

  • On the one hand, there is speculation that by upregulating ACE2, ACEi/ARBs might increase the risk and severity of COVID-19.

  • On the other hand, there is evidence that downregulation of ACE2 can mediate acute lung injury. Further evidence is urgently needed to guide clinicians in the use of ACEi/ARB in patients with COVID-19 with co-morbidities.

What does this article add

  • Our meta-analysis, which is the first to assess the effect of use of ACEi/ARB in patients with COVID-19, reports that use of ACEi/ARB statistically significantly reduced the risk of death, with a trend towards reduction in risk of severe disease and hospitalisation compared to those who were not on ACEi/ARB.

  • Further information from on-going RCTs shall take time to fruition; in the interim, based on these findings, clinicians can safely continue to use ACEi/ARB in patients with COVID-19 with comorbidities.

Review Criteria

  • A web-based search was conducted using the Cochrane library, PubMed, Embase, ClinicalTrial.gov and medRxiv using specific keywords.

  • Narrowing down of the citations was done based on full text availability and a set of pre-determined inclusion criteria.

  • Meta-analysis was conducted on the pooled data comparing ACEi/ARB group versus the non-ACEi/ARB group on death, severity of disease and hospitalization using the CMA software version 3, Biostat Inc., Englewood, NJ, USA.

  • Effect size was reported as odds ratio with a 95% confidence interval and the degree of heterogeneity of the pooled data.

Message for the clinic

  • There is no indication from present evidence to withhold or withdraw ACEi/ARB in patients with SARS-CoV-2.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.23.20076661: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blinding2.3 Study quality assessment: Quality of individual studies were assessed using the Cochrane collaboration tool using random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcomes assessment, incomplete outcome data, selective reporting and other bias as assessment attributes.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    An electronic database search was conducted using the Cochrane library, PubMed, Embase, CT.gov and mdRxiv.
    Cochrane library
    suggested: (Cochrane Library, RRID:SCR_013000)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    2.3 Study quality assessment: Quality of individual studies were assessed using the Cochrane collaboration tool using random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcomes assessment, incomplete outcome data, selective reporting and other bias as assessment attributes.
    Cochrane collaboration tool
    suggested: None
    Heterogeneity was assessed using the Cochrane Q and Higgin’s I2 test and publication bias was assessed by funnel plots.
    Cochrane Q
    suggested: None
    Where relative risk or odds ratio were not reported odds ratio was calculated from the reported events using Medcalc statistical software,
    Medcalc
    suggested: (MedCalc, RRID:SCR_015044)

    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:
    Our meta-analysis has a few limitations. The six studies included for analysis used different primary and secondary end-points that led to a moderate degree of heterogeneity in the reported results; we circumvented this by restricting our meta-analysis to clinically relevant end-points of death, hospitalisation and severity of disease, which resulted in negligible heterogeneity in our analysis on hospitalisation and death. The number of patients in the individual studies were small and there were various confounders, which were partly addressed by pooling of the data from the individual studies. Last, but not the least, due to a very small number of patients in the studies that reported outcomes independently in patients with COVID-19 on an ACEi or ARB, we were unable to assess the independent effect of ACEi or ARB on death and severity of disease in patients with COVID-19. The strength of our meta-analysis lies in the fact that in an evolving infectious disease pandemic with acute consequences, where generation of evidence at the earliest is crucial to guide management, the best way to increase the predictability of the question in focus is to perform pooled analysis, till results of a randomized controlled trial (RCT) becomes available. By pooling data from multiple small observational studies with multiple inherent confounding factors, and by performing a meta-analysis, we have largely circumvented the problems associated with the individual studies. This meta-analysis, hi...

    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.

  2. Version published to 10.1101/2020.04.23.20076661v2 on medRxiv
  3. Version published to 10.1101/2020.04.23.20076661v1 on medRxiv