Mortality and Severity in COVID-19 Patients on ACEIs and ARBs—A Systematic Review, Meta-Analysis, and Meta-Regression Analysis

  1. Romil Singh
  2. Sawai Singh Rathore
  3. Hira Khan
  4. Abhishek Bhurwal
  5. Mack Sheraton
  6. Prithwish Ghosh
  7. Sohini Anand
  8. Janaki Makadia
  9. Fnu Ayesha
  10. Kiran S. Mahapure
  11. Ishita Mehra
  12. Aysun Tekin
  13. Rahul Kashyap
  14. Vikas Bansal

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Abstract

Purpose: The primary objective of this systematic review is to assess association of mortality in COVID-19 patients on Angiotensin-converting-enzyme inhibitors (ACEIs) and Angiotensin-II receptor blockers (ARBs). A secondary objective is to assess associations with higher severity of the disease in COVID-19 patients.

Materials and Methods: We searched multiple COVID-19 databases (WHO, CDC, LIT-COVID) for longitudinal studies globally reporting mortality and severity published before January 18th, 2021. Meta-analyses were performed using 53 studies for mortality outcome and 43 for the severity outcome. Mantel-Haenszel odds ratios were generated to describe overall effect size using random effect models. To account for between study results variations, multivariate meta-regression was performed with preselected covariates using maximum likelihood method for both the mortality and severity models.

Result: Our findings showed that the use of ACEIs/ARBs did not significantly influence either mortality (OR = 1.16 95% CI 0.94–1.44, p = 0.15, I 2 = 93.2%) or severity (OR = 1.18, 95% CI 0.94–1.48, p = 0.15, I 2 = 91.1%) in comparison to not being on ACEIs/ARBs in COVID-19 positive patients. Multivariate meta-regression for the mortality model demonstrated that 36% of between study variations could be explained by differences in age, gender, and proportion of heart diseases in the study samples. Multivariate meta-regression for the severity model demonstrated that 8% of between study variations could be explained by differences in age, proportion of diabetes, heart disease and study country in the study samples.

Conclusion: We found no association of mortality or severity in COVID-19 patients taking ACEIs/ARBs.

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  1. Version published to 10.3389/fmed.2021.703661
  2. ScreenIT

    SciScore for 10.1101/2021.03.14.21253557: (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

    No key resources detected.

    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:
    However, despite all the strengths, there are still certain limitations. The major limitation of the meta-regression is the presence of unknown confounders. Multiple previous studies have reported that gender, age, smoking history, and presence of diabetes influence COVID-19 results. Even though these confounders are reported in most of the included studies, further studies focusing on the adjustment of confounders are necessary. We included studies from the medRxiv.org databases and other preprint database which did not go through peer review at that time. We considered this as a limitation, as peer reviewers could catch more deficiencies in reporting methods and other details. However, it was anticipated that majority of these studies would be peer-reviewed. Third, the use of ACE/ARB has been via medical record review which could be less reliable. Finally, the definition of COVID-19 severity and outcomes were not uniform among the included studies. In conclusion, meta-regression analysis suggest that the use of ACEIs/ARBs in patients with COVID-19 is not associated with increased mortality or increased severity. However, multivariate meta-regression model for mortality indicated that 36% study variation could be due to differences in age, female gender, proportion of heart diseases in the study samples. Similarly, multivariate meta-regression for the severity model exhibited that 8% of study variations could be explained by differences in age, proportion of diabetes, heart ...

    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.
    • Thank you for including a protocol registration statement.

    About SciScore

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  3. Version published to 10.1101/2021.03.14.21253557v1 on medRxiv