Association of COVID-19 vaccination with risks of hospitalization due to cardiovascular and other diseases: A study of the UK

  1. Yong Xiang
  2. Yaning Feng
  3. Jinghong Qiu
  4. Ruoyu Zhang
  5. Hon-Cheong So

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Abstract

Background

Vaccines for COVID-19 represent a major breakthrough. However, worries about adverse effects led to vaccine hesitancy in some people. On the other hand, as COVID-19 may be associated with various sequelae, vaccination may protect against such sequelae via prevention of infections and severe disease.

Methods

We leveraged the UK-Biobank (UKBB) and studied associations of at least one dose of COVID-19 vaccination (BioNTech-BNT162b2 or Oxford-AstraZeneca-ChAdOx1) with short-term hospitalizations from cardiovascular and other selected diseases ( N =393,544; median follow-up = 54 days among vaccinated). Multivariable Cox and Poisson regression analyses were performed. We also performed adjustment using prescription-time distribution matching (PTDM) and prior-event rate ratio (PERR). PERR minimizes unmeasured confounding by comparing event hazards before introduction of vaccination.

Results

We observed that COVID-19 vaccination(at least one dose), when compared to no vaccination, was associated with reduced short-term risks of hospitalizations from stroke(hazard ratio[HR]=0.178, 95% CI: 0.127-0.250, P= 1.50e-23), venous thromboembolism (VTE) (HR=0.426, CI: 0.270-0.673, P= 2.51e-4), dementia(HR=0.114, CI: 0.060-0.216; P= 2.24e-11), non-COVID-19 pneumonia(NCP) (HR=0.108, CI: 0.080-0.145; P= 2.20e-49), coronary artery disease (CAD) (HR=0.563, CI: 0.416-0.762; P= 2.05e-4), chronic obstructive pulmonary disease (COPD) (HR=0.212, CI: 0.126-0.357; P= 4.92e-9), type-2 diabetes (T2DM) (HR=0.216, CI: 0.096-0.486, P= 2.12e-4), heart failure (HR=0.174, CI: 0.118-0.256, P= 1.34e-18) and renal failure (HR=0.415, CI: 0.255-0.677, P= 4.19e-4), based on Cox regression models. Among the above results, reduced hospitalizations for stroke, heart failure, NCP and dementia were consistently observed across all analyses, including regression/PTDM/PERR.

Conclusions

Taken together, this study provides further support to the safety and benefits of COVID-19 vaccination, and such benefits may extend beyond reduction of infection risk or severity per se. However, causal relationships cannot be concluded and further studies are required to verify the findings.

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  1. Version published to 10.1101/2021.08.15.21262097v3 on medRxiv
  2. Version published to 10.1101/2021.08.15.21262097v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.08.15.21262097: (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.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisFor better statistical power, we primarily present the results from any hospitalization or mortality from specific diseases.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    During the period of study, all subjects received either the BioNTech BNT162b2 or Oxford-AstraZeneca ChAdOx1 nCoV-19 vaccine.
    BioNTech
    suggested: None

    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 study is based on a relatively large sample with detailed phenotypic information and health records. We have conducted a comprehensive analysis covering a range of cardiovascular and other relevant diseases. We have also conducted analyses with different statistical models to evaluate if the findings are robust to different modeling strategies. To our knowledge, this is the first comprehensive study to investigate the association of COVID-19 vaccination with hospitalization/mortality for a wide range of diseases. There are several imitations of the present study. First and foremost, this is a real-world observational study without randomization of vaccination. As such, residual confounding cannot be excluded, and our results should not be regarded as confirmatory evidence of causal relationships between vaccination and the diseases under study. We have controlled for a wide range of covariates such as general health and comorbidities, but residual confounding is still likely present. For example, some subjects may not be vaccinated due to frailty or worry about their underlying conditions, but on the other hand underlying medical conditions may also motivate vaccinations in view of higher risks from COVID-19 complications. The effect size estimates may also be affected by residual confounding. For example, in this analysis, vaccination was associated with a relatively large reduction in cause-specific or all-cause mortality However, we caution ...

    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.

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

    About SciScore

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  4. Version published to 10.1101/2021.08.15.21262097v1 on medRxiv