Self-sampling of capillary blood for SARS-CoV-2 serology

  1. Lottie Brown
  2. Rachel L. Byrne
  3. Alice Fraser
  4. Sophie I. Owen
  5. Ana I. Cubas-Atienzar
  6. Christopher T. Williams
  7. Grant A. Kay
  8. Luis E. Cuevas
  9. Joseph R. A. Fitchett
  10. Tom Fletcher
  11. Gala Garrod
  12. Konstantina Kontogianni
  13. Sanjeev Krishna
  14. Stefanie Menzies
  15. Tim Planche
  16. Chris Sainter
  17. Henry M. Staines
  18. Lance Turtle
  19. Emily R. Adams

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Abstract

Serological testing is emerging as a powerful tool to progress our understanding of COVID-19 exposure, transmission and immune response. Large-scale testing is limited by the need for in-person blood collection by staff trained in venepuncture, and the limited sensitivity of lateral flow tests. Capillary blood self-sampling and postage to laboratories for analysis could provide a reliable alternative. Two-hundred and nine matched venous and capillary blood samples were obtained from thirty nine participants and analysed using a COVID-19 IgG ELISA to detect antibodies against SARS-CoV-2. Thirty eight out of thirty nine participants were able to self-collect an adequate sample of capillary blood (≥ 50 µl). Using plasma from venous blood collected in lithium heparin as the reference standard, matched capillary blood samples, collected in lithium heparin-treated tubes and on filter paper as dried blood spots, achieved a Cohen’s kappa coefficient of > 0.88 (near-perfect agreement, 95% CI 0.738–1.000). Storage of capillary blood at room temperature for up to 7 days post sampling did not affect concordance. Our results indicate that capillary blood self-sampling is a reliable and feasible alternative to venepuncture for serological assessment in COVID-19.

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  1. Version published to 10.1038/s41598-021-86008-5
  2. ScreenIT

    SciScore for 10.1101/2020.09.25.20183459: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Participants gave consent for the use of their samples for this purpose.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Detection of SARS-CoV-2 antibodies in capillary and venous blood: On the day following sample collection (day 1), the venous and capillary samples (refrigerated and stored at room temperate) were run in triplicate on the COVID-19 IgG ELISA (Omega Diagnostics Ltd, Littleport, Cambridgeshire, UK) according to manufacturer’s instructions; positive, cut-off, and negative controls were run in duplicate.
    COVID-19 IgG
    suggested: None
    Samples with a mean OD value of 10% greater than the cut-off control, as defined in the manufacturer’s instructions, were regarded as positive for SARS-CoV-2 antibodies (Adams et al., 2020; Staines et al., 2020).
    SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using Prism (version 8, GraphPad, USA).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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 10.1101/2020.09.25.20183459v1 on medRxiv