Nasal-Swab Testing Misses Patients with Low SARS-CoV-2 Viral Loads

  1. Cody Callahan
  2. Rose A. Lee
  3. Ghee Rye Lee
  4. Kate Zulauf
  5. James E. Kirby
  6. Ramy Arnaout

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Abstract

The urgent need for large-scale diagnostic testing for SARS-CoV-2 has prompted pursuit of sample-collection methods of sufficient sensitivity to replace sampling of the nasopharynx (NP). Among these alternatives is collection of nasal-swab samples, which can be performed by the patient, avoiding the need for healthcare personnel and personal protective equipment.

Previous studies have reached opposing conclusions regarding whether nasal sampling is concordant or discordant with NP. To resolve this disagreement, we compared nasal and NP specimens collected by healthcare workers in a cohort consisting of individuals clinically suspected of COVID-19 and outpatients known to be SARS-CoV-2 RT-PCR positive undergoing follow-up. We investigated three different transport conditions, including traditional viral transport media (VTM) and dry swabs, for each of two different nasal-swab collection protocols on a total of 308 study participants, and compared categorical results and Ct values to those from standard NP swabs collected at the same time from the same patients. All testing was performed by RT-PCR on the Abbott SARS-CoV-2 RealTime EUA (limit of detection [LoD], 100 copies viral genomic RNA/mL transport medium). We found high concordance (Cohen’s kappa >0.8) only for patients with viral loads above 1,000 copies/mL. Those with viral loads below 1,000 copies/mL, the majority in our cohort, exhibited low concordance (Cohen’s kappa = 0.49); most of these would have been missed by nasal testing alone. Previous reports of high concordance may have resulted from use of assays with higher LoD (≥1,000 copies/mL). These findings counsel caution in use of nasal testing in healthcare settings and contact-tracing efforts, as opposed to screening of asymptomatic, low-prevalence, low-risk populations. Nasal testing is an adjunct, not a replacement, for NP.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.12.20128736: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was reviewed and approved by BIDMC’s institutional review board (IRB protocol no. 2020P000451).
    RandomizationWe used bootstrapping to test whether the n results for a given arm exhibited appreciable differences from others, specifically by testing whether a given arm differed from random samples from (i) results pooled across the three arms that used the same nasal-swab sampling procedure or (ii) all results.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Transport conditions and swabs used: Standard nasal swabs were compared under three different specimen-transport conditions: (i) a guanidine thiocyanate (GITC) transport buffer, part of the Abbott multi-Collect Specimen Collection Kit, catalog no. 09K12-004; Abbott Laboratories, Abbott Park, IL), (ii) dry, with no buffer; and (iii) in modified CDC viral transport media (VTM) (Hank’s balanced salt solution containing 2% heat inactivated FBS, 100µg/mL gentamicin, 0.5µg/mL fungizone, and 10mg/L Phenol red, produced by the Beth Israel Deaconess Medical Center [BIDMC
    Abbott Laboratories
    suggested: None
    Dry swabs were eluted in 2mL of Abbott mWash1
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    We used Python (v3.6-3.8) and its NumPy, SciPy, Matplotlib, Pandas, and ct2vl libraries for the above analyses and related visualizations.
    Python
    suggested: (IPython, RRID:SCR_001658)
    NumPy
    suggested: (NumPy, RRID:SCR_008633)
    SciPy
    suggested: (SciPy, RRID:SCR_008058)
    Matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)
    Literature review: We searched Pubmed and the preprint servers bioRxiv and medRxiv through June 1, 2020 for all literature on nasal-swab sampling for SARS-CoV-2 and extracted sample sizes, collection methods, RT-PCR assay information, and 2×2 contingency table data comparing nasal swabs to NP swabs wherever available.
    Pubmed
    suggested: (PubMed, RRID:SCR_004846)
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)

    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:
    Interestingly, we found no difference among transport media conditions and between sampling protocols, suggesting that lower sensitivity of nasal swab sampling is an overall limitation of the anatomical location of nasal swabs and that the protocols and media conditions we tested are interchangeable. Thus, for patients above a critical threshold of 1,000 copies/mL (Fig. 2), nasal swabs collected in VTM, GITC transport medium, and as dry swabs are all likely to perform equally well in the population, providing multiple potential options for specimen acquisition. Our results suggest several settings in which nasal swabs may and may not best be used. Peak infectiousness is likely to occur near or shortly before symptom onset20,21 and nasopharyngeal viral load is often undetectable a week after symptom onset2. Lower-sensitivity testing would therefore likely miss patients with early developing presymptomatic infections and patients presenting multiple days after symptom onset. Notably, for those presenting later to care, a false-negative diagnosis could bear significant clinical implications in not only erroneously reassuring the patient and clinical team, but also excluding them from potentially useful and rationed therapies such as remdesivir22 or others. Importantly, based on viral load distribution in first-time tested individuals at our institution, ∼20% of newly presenting SARS-CoV-2 positive individuals would be missed if sampled solely using nasal swabs6, highlighting the...

    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 10.1101/2020.06.12.20128736v1 on medRxiv