Antihypertensive medications and COVID‐19 diagnosis and mortality: Population‐based case‐control analysis in the United Kingdom

  1. Emma Rezel‐Potts
  2. Abdel Douiri
  3. Phil J. Chowienczyk
  4. Martin C. Gulliford

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Abstract

Antihypertensive drugs have been implicated in coronavirus disease 2019 (COVID‐19) susceptibility and severity, but estimated associations may be susceptible to bias. We aimed to evaluate antihypertensive medications and COVID‐19 diagnosis and mortality, accounting for healthcare‐seeking behaviour.

Methods

A population‐based case‐control study was conducted including 16 866 COVID‐19 cases and 70 137 matched controls from the UK Clinical Practice Research Datalink. We evaluated all‐cause mortality among COVID‐19 cases. Exposures were angiotensin‐converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), beta‐blockers (B), calcium‐channel blockers (C), thiazide diuretics (D) and other antihypertensive drugs (O). Analyses were adjusted for covariates and consultation frequency.

Results

ACEIs were associated with lower odds of COVID‐19 diagnosis (adjusted odds ratio [AOR] 0.82, 95% confidence interval [CI] 0.77‐0.88) as were ARBs (AOR 0.87, 95% CI 0.80‐0.95) with little attenuation from adjustment for consultation frequency. C and D were also associated with lower odds of COVID‐19 diagnosis. Increased odds of COVID‐19 for B (AOR 1.19, 95% CI 1.12‐1.26) were attenuated after adjustment for consultation frequency (AOR 1.01, 95% CI 0.95‐1.08). Patients treated with ACEIs or ARBs had similar odds of mortality (AOR 1.00, 95% CI 0.83‐1.20) to patients treated with classes B, C, D or O or patients receiving no antihypertensive therapy (AOR 0.99, 95% CI 0.83‐1.18).

Conclusions

There was no evidence that antihypertensive therapy is associated with increased risk of COVID‐19 diagnosis or mortality; most classes of antihypertensive therapy showed negative associations with COVID‐19 diagnosis.

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  1. Version published to 10.1111/bcp.14873
  2. ScreenIT

    SciScore for 10.1101/2020.09.25.20201731: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationUp to five control patients for each case were randomly sampled from the entire registered population of CPRD GOLD, matching on age, gender, index date and general practice.
    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:
    Strengths and weaknesses of the study: This study drew on a large, longitudinal population-based data resource that enabled us to conduct a matched case-control analysis of risk factors for clinical COVID-19 diagnosis, as well as a cohort study of risk factors for COVID-19 mortality. As noted above, most cases were diagnosed clinically as suspected cases because of the limited capacity for testing in the early stage of the pandemic. General practice systems capture comprehensive data for all prescriptions issued by the general practice, so we can be confident that this exposure was accurately recorded. However, prescription utilisation may not be universal and non-adherence to prescribed medicines may be widespread. Data for covariates was not always completely recorded. Data on ethnicity were missing for almost half the sample as reported by others;25 an important limitation given the disproportionate impact COVID-19 has had on ethnic minority populations in the US and UK.14,30,31 COVID-19 susceptibility and severity have also been associated with measures of deprivation.14 Matching on practice may have accounted for differences in area-level deprivation to an extent, but deprivation based on participants’ home postcodes or individual-level deprivation measures might improve precision. It is known that observational studies on COVID-19 outcomes may be susceptible to collider bias.22,23 This can lead to spurious associations if both antihypertensive therapy and COVID-19 are a...

    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 10.1101/2020.09.25.20201731v1 on medRxiv