Cardiac Arrhythmias in Patients with COVID-19: A Systematic review and Meta-analysis

  1. Omar Hamam
  2. Ahmed Goda
  3. Moustafa Eldalal
  4. Amr Ussama
  5. Mostafa Fahmy
  6. Karim Elyamany
  7. Waleed Ikram
  8. Ahmed Mahdy
  9. Renu Bhandari
  10. Mohammad A. Elbahnasawy
  11. Hosam Asal
  12. Alexander Egbe

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Abstract

Background: Cardiac arrhythmia cannot be overlooked in patients with coronavirus disease 2019 (COVID-19) as it carries a great influence on the outcomes. Hence, this study aimed to build concrete evidence regarding the incidence of cardiac arrhythmia in patients with COVID-19. Methods: We performed a systematic search for trusted databases/search engines including PubMed, Scopus, Cochrane library and web of science. After screening, the relevant data were extracted and the incidences from the different included studies were pooled for meta-analysis. Results: Nine studies were finally included in our study consisting of 1445 patients. The results of meta-analysis showed that the incidence of arrhythmia in patients with COVID-19 was 19.7% with 95% confidence interval (CI) ranging from 11.7 to 27.6%. There was also a significant heterogeneity (I2 = 94.67%). Conclusion: Cardiac arrhythmias were highly frequent in patients with COVID-19 and observed in 19.7% of them. Appropriate monitoring by electrocardiogram with accurate and early identification of arrhythmias is important for better management and outcomes.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.09.20209379: (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

    Software and Algorithms
    SentencesResources
    We searched PubMed, Web of Science, Scopus, and Cochrane Library for relevant articles to be included.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Cochrane Library
    suggested: (Cochrane Library, RRID:SCR_013000)
    An additional online and manual search was performed on Google Scholar and Preprint Servers to ensure adequate inclusion of all studies.
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    Values of I2 >50 and P<0.1 are significant markers of heterogeneity among studies according to Cochrane’s handbook14.
    Cochrane’s
    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:
    However, this study suffered from several limitations. Although the number of patients from our pooled studies was 1445 patients, the number of studies was only nine which lead us to avoid testing for publication bias and performing meta-regression according to the reported recommendations for those tests that need at least 10 studies to be well performed. Moreover, the types of cardiac arrhythmias were not specified so we could not provide more specific subgroup analysis based upon the included studies. The studies were all observational retrospective and this type of studies has its own known limitations. Further studies that can explore cardiac arrhythmias in COVID-19 patients with more details on determinants are highly recommended. To recapitulate, cardiac arrhythmias were highly frequent in patients with COVID-19 and observed in 19.7% of them. Appropriate monitoring by electrocardiogram with accurate and early identification of arrhythmias is important for better management and outcomes.

    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 10.1101/2020.10.09.20209379v3 on medRxiv
  3. Version published to 10.1101/2020.10.09.20209379v2 on medRxiv
  4. Version published to 10.1101/2020.10.09.20209379v1 on medRxiv