Performance of Saliva Specimens for the Molecular Detection of SARS-CoV-2 in the Community Setting: Does Sample Collection Method Matter?

  1. Marta Fernández-González
  2. Vanesa Agulló
  3. Alba de la Rica
  4. Ana Infante
  5. Mar Carvajal
  6. José Alberto García
  7. Nieves Gonzalo-Jiménez
  8. Claudio Cuartero
  9. Montserrat Ruiz-García
  10. Carlos de Gregorio
  11. Manuel Sánchez
  12. Mar Masiá
  13. Félix Gutiérrez

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Abstract

Data on the performance of saliva specimens for diagnosing coronavirus disease 2019 (COVID-19) in ambulatory patients are scarce and inconsistent. We assessed saliva-based specimens for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse transcriptase PCR (RT-PCR) in the community setting and compared three different collection methods.

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  1. Version published to 10.1128/jcm.03033-20
  2. ScreenIT

    SciScore for 10.1101/2020.12.01.20241349: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Elche COVID-19 Institutional Advisory Board.
    Consent: After obtaining written consent, demographic and clinical findings were recorded.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisWith this sample size the study would have a statistical power of 80% to detect a 10% difference in sensitivity between the different collection methods.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    For the graphical analysis, the ggplot2 package [15] was used.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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:
    The study has limitations. The investigation focused on comparing three specific methods for collection of saliva samples and was powered to detect rather large differences among groups. The sample size does not allow to draw conclusions on the performance in particular subgroups, including children and patients tested at different time point of illness. Noteworthy, a substantial proportion of the children recruited were unable to provide saliva, suggesting that this specimen might be less suitable for this group. In addition, we used a particular detection system (Cobas z 480 Analyzer), other platforms may have yielded different results. Strengths of the study are that it was population-based and carried out in real-life conditions, enrolling consecutive outpatients of all ages presenting for testing due to symptoms and asymptomatic people who had come into contact with confirmed cases. In conclusion, our results indicate that the adequate collection of samples may be essential for the molecular diagnosis of COVID-19 when using saliva specimens. Saliva specimens obtained under supervision perform comparably to NPS and should be considered as a reliable sample for the diagnosis in the community setting in both symptomatic and asymptomatic individuals, particularly to detect individuals with significant risk of transmission. Although self-collected saliva would be the most advantageous way of sampling if mass testing were considered, these specimens had less sensitivity in our...

    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 10.1101/2020.12.01.20241349 on medRxiv