COVID-19 serology in nephrology healthcare workers

  1. Thomas Reiter
  2. Sahra Pajenda
  3. Ludwig Wagner
  4. Martina Gaggl
  5. Johanna Atamaniuk
  6. Barbara Holzer
  7. Irene Zimpernik
  8. Daniela Gerges
  9. Katharina Mayer
  10. Christof Aigner
  11. Robert Straßl
  12. Sonja Jansen-Skoupy
  13. Manuela Födinger
  14. Gere Sunder-Plassmann
  15. Alice Schmidt

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Abstract

Background

Chronic kidney disease patients show a high mortality in cases of a severe acute respiratory syndrome coronavirus-2 (SARS-CoV‑2) infection. Thus, information on the sero-status of nephrology personnel might be crucial for patient protection; however, limited information exists about the presence of SARS-CoV‑2 antibodies in asymptomatic individuals.

Methods

We examined the seroprevalence of SARS-CoV‑2 IgG and IgM antibodies among healthcare workers of a tertiary care kidney center during the the first peak phase of the corona virus disease 2019 (COVID-19) crisis in Austria using an orthogonal test strategy and a total of 12 commercial nucleocapsid protein or spike glycoprotein-based assays as well as Western blotting and a neutralization assay.

Results

At baseline 60 of 235 study participants (25.5%, 95% confidence interval, CI 20.4–31.5%) were judged to be borderline positive or positive for IgM or IgG using a high sensitivity/low specificity threshold in one test system. Follow-up analysis after about 2 weeks revealed IgG positivity in 12 (5.1%, 95% CI: 2.9–8.8%) and IgM positivity in 6 (2.6%, 95% CI: 1.1–5.6) in at least one assay. Of the healthcare workers 2.1% (95% CI: 0.8–5.0%) showed IgG nucleocapsid antibodies in at least 2 assays. By contrast, positive controls with proven COVID-19 showed antibody positivity among almost all test systems. Moreover, serum samples obtained from healthcare workers did not show SARS-CoV‑2 neutralizing capacity, in contrast to positive controls.

Conclusion

Using a broad spectrum of antibody tests the present study revealed inconsistent results for SARS-CoV‑2 seroprevalence among asymptomatic individuals, while this was not the case among COVID-19 patients.

Trial registration number

CONEC, ClinicalTrials.gov number NCT04347694

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  1. Version published to 10.1007/s00508-021-01848-5
  2. ScreenIT

    SciScore for 10.1101/2020.07.21.20136218: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: We report here the baseline data of the CONEC study, which was approved by the institutional review board (IRB) at the Medical University of Vienna (unique IRB identifier: 1357/2020).
    Consent: All participants provided written informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    At baseline, participants were screened for the presence of serum anti-SARS-CoV-2 IgG and IgM antibodies by means of the ImmunoDiagnostics test system (ImmunoDiagnostics, HongKong).
    anti-SARS-CoV-2 IgG
    suggested: None
    IgM
    suggested: None
    Laboratory analysis: We used a set of ten commercial serologic tests for detection of anti SARS-CoV-2 IgG (two for antigenic target nucleocapsid protein, two for antigenic target spike glycoprotein), of anti-SARS-CoV-2 IgM (two antigenic target nucleocapsid protein, one antigenic target spike glycoprotein), of anti-SARS-CoV-2 IgA (one antigenic target spike glycoprotein), and of anti-SARS-CoV-2 total antibody (one antigenic target nucleocapsid protein, one antigenic target spike glycoprotein) including enzyme-linked immunosorbent assays (ELISA)
    anti SARS-CoV-2 IgG
    suggested: None
    In subjects with IgG antibodies at follow-up and for Covid-19 control samples we also used two additional IgG ELISAs.
    IgG
    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:
    A potential limitation to this study relies in the lack of unambiguous Covid-19 cases among study participants, which was not expected to be the case at the beginning of this study in March 2020. We also did not do a formal laboratory test performance analysis. This is largely counterbalanced by the strength of this study, namely the orthogonal test strategy with confirmation in separate serum samples using a very broad range of SARS-CoV-2 antibody tests. In summary, our study demonstrates that single antibody tests are not reliable to assess the SARS-CoV-2 immune response in mostly asymptomatic individuals. This finding has important implications for testing cohorts with a low Covid-19 prevalence to determine whether herd immunity has been reached. Containment strategies by the City of Vienna and the Medical University of Vienna proved to be extremely effective given the very low seroprevalence in a cohort of high-risk health care workers during the peak of the pandemic crisis in Austria. However, caution has still to be taken, since health care workers are prone to Covid-19 infections and transmission to patients.

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

    IdentifierStatusTitle
    NCT04347694RecruitingStudy to Determine the Immunization Status Among Nephrologic…

    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 10.1101/2020.07.21.20136218 on medRxiv