ddPCR: a more sensitive and accurate tool for SARS-CoV-2 detection in low viral load specimens

  1. Tao Suo
  2. Xinjin Liu
  3. Jiangpeng Feng
  4. Ming Guo
  5. Wenjia Hu
  6. Dong Guo
  7. Hafiz Ullah
  8. Yang Yang
  9. Qiuhan Zhang
  10. Xin Wang
  11. Muhanmmad Sajid
  12. Zhixiang Huang
  13. Liping Deng
  14. Tielong Chen
  15. Fang Liu
  16. Xu Ke
  17. Yuan Liu
  18. Qi Zhang
  19. Yingle Liu
  20. Yong Xiong
  21. Guozhong Chen
  22. Ke Lan
  23. Yu Chen

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Abstract

Real time fluorescent quantitative PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load in patient throats and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, early treat, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 nucleic acid from 77 clinical throat swab samples, including 63 suspected outpatients with fever and 14 supposed convalescents who were about to discharge after treatment, and compared with RT-PCR in terms of the diagnostic accuracy. In this double-blind study, we tested, surveyed subsequently and statistically analyzed 77 clinical samples. According to our study, 26 samples from COVID-19 patients with RT-PCR negative were detected as positive by ddPCR. No FPRs of RT-PCR and ddPCR were observed. The sensitivity, specificity, PPV, NPV, NLR and accuracy were improved from 40% (95% CI: 27–55%), 100% (95% CI: 54–100%), 100%, 16% (95% CI: 13–19%), 0.6 (95% CI: 0.48–0.75) and 47% (95% CI: 33–60%) for RT-PCR to 94% (95% CI: 83–99%), 100% (95% CI: 48–100%), 100%, 63% (95% CI: 36–83%), 0.06 (95% CI: 0.02–0.18) and 95% (95% CI: 84–99%) for ddPCR, respectively. Moreover, 14 (42.9 %) convalescents still carry detectable SARS-CoV-2 after discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the current standard RT-PCR. It also suggests that the current clinical practice that the convalescent after discharge continues to be quarantined for at least 2 weeks is completely necessary which can prevent potential viral transmission.

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  1. ScreenIT

    SciScore for 10.1101/2020.02.29.20029439: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics statement: The institutional review board of Renmin Hospital of Wuhan University approved this study (WDRY2020-K089).
    Consent: Written informed consents were obtained.
    RandomizationTo perform the tests of clinical samples, throat swab samples of 63 suspected outpatients and 14 supposed convalescents were randomly collected by the medical staffs from COVID-19 designated Renmin and Zhongnan Hospital of Wuhan University.
    BlindingAll the events happened in hospitals and laboratories are blinded to each other during the tests.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    In addition, plots of linear regression were conducted with GraphPad Prism 7.00, and probit analysis for LoD was conducted with MedCalc software v19.2.1.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)

    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.

  2. Version published to 10.1101/2020.02.29.20029439 on medRxiv
  3. Version published to 10.1080/22221751.2020.1772678