Comparing lateral flow testing with a rapid RT‐PCR method for SARS‐CoV‐2 detection in the United Kingdom—A retrospective diagnostic accuracy study

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Background and Aims

In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) emerged in Wuhan, China. Rapid global spread led to the coronavirus disease 2019 (Covid‐19) pandemic. Accurate detection of SARS‐CoV‐2 has become a vitally important tool in controlling the spread of the virus. Lateral flow devices (LFDs) offer the potential advantage of speed and on‐site testing. The sensitivity of these devices compared to reverse transcription‐polymerase chain reaction (RT‐PCR) has been questioned.

Methods

We compared the sensitivity of the Innova LFD, used widely in the United Kingdom, with our rapid RT‐PCR method using stored positive samples. Samples with a range of viral loads (original Ct values 18.9–36.5) were tested.

Results

The Innova LFD was found to be 6000–10,000 times less sensitive than RT‐PCR for SARS‐CoV‐2 detection. Overall, the LFD detected 46.2% of the positives detected by RT‐PCR, with 50% of these observed to be weak LFD positives. At lower viral loads, such as 10,000–100,000 RNA copies/ml, the LFD detected 22.2% of positives. In addition, two strong positives (3 and 1.5 million RNA copies/ml) were not detected by the LFD.

Conclusion

The argument for use of LFD kits is that they detect infectious virus and hence contagious individuals. However, there is a lack of conclusive evidence supporting this claim. The Innova LFD has been subject to a Class I recall by the US Food and Drug Administration, but is still approved and widely used in the United Kingdom.

Article activity feed

  1. SciScore for 10.1101/2021.10.08.21264742: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was reviewed and approved by the Micropathology Ltd Ethics Committee Review Board composed of Professor Sheila Crispin (MA, VetMB, DVA, DVOphthal, DipEVCO, FRCVS), Professor Christopher Dowson (BSc, PhD), Rt Hon Countess of Mar, Most Rev Dr Gordon Mursell (MA, Hon DD) and William NH Taylor (BTech)).
    Consent: No additional consent was necessary.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis: Probit regression (MedCalc) was used to determine the LLoD (with 95% confidence interval) of both methods.
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)
    The correlation between viral load and LFD result was calculated in Excel by first converting the LFD results into a score of 0-3 reflecting the number of replicates with a positive result.
    Excel
    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: 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.

    Results from scite Reference Check: We found no unreliable references.


    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.