Clinical presentation, disease course, and outcome of COVID-19 in hospitalized patients with and without pre-existing cardiac disease: a cohort study across 18 countries

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Abstract

Aims

Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality.

Methods and results

We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66–75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02–1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10–1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20–1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients.

Conclusion

Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization.

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  1. SciScore for 10.1101/2021.03.11.21253106: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: The informed consent procedure varied per study site, following local and national rules and regulations during the pandemic.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data is collected in a REDCap database after pseudonymization which is managed by the University Medical Center Utrecht, Utrecht, the Netherlands.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    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:
    Limitations: Our study determines associations on a population level (e.g., all patients with heart failure) rather than individual risks and is limited to patients with COVID-19 that were hospitalized. In some countries that provided data, hospitalization and potentially life-sustaining treatments such as mechanical ventilation, might have been withheld in those with high frailty, including those with severe heart failure, which may have led to an overestimation of the found associations. Furthermore, we could not reliably investigate associations between heart disease subtypes and HDU/ICU admission since we observed that patients admitted to a critical care unit were overall younger with fewer comorbidities. Since age in particular is well-known to be associated with a more severe COVID-19 disease course, this difference in baseline characteristics in those admitted to HDU/ICU is suggestive of an underlying selection of patients admitted for critical care. The mechanisms behind this selection are likely complex, influenced by amongst others the variability in critical care bed numbers across participating countries and available staff that may have led to demand for life-saving resources (nearly) exceeding supply, patient preference as well as cultural differences in clinical decision making. A further study limitation is that we only examined the impact of pre-existing CVD on in-hospital mortality, which excludes the many deaths that have occurred in community settings and...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04325412RecruitingCardiac complicAtions in Patients With SARS Corona vIrus 2 (…
    NCT04325412RecruitingCardiac complicAtions in Patients With SARS Corona vIrus 2 (…


    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.