Plasma SARS-CoV-2 RNA Levels as a Biomarker of Lower Respiratory Tract SARS-CoV-2 Infection in Critically Ill Patients With COVID-19

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Abstract

Plasma SARS-CoV-2 viral RNA (vRNA) levels are predictive of COVID-19 outcomes in hospitalized patients, but whether plasma vRNA reflects lower respiratory tract (LRT) vRNA levels is unclear. We compared plasma and LRT vRNA levels in serially collected samples from mechanically ventilated patients with COVID-19. LRT and plasma vRNA levels were strongly correlated at first sampling (n = 33, r = 0.83, P < 10−9) and then declined in parallel in available serial samples except in nonsurvivors who exhibited delayed vRNA clearance in LRT samples. Plasma vRNA measurement may offer a practical surrogate of LRT vRNA burden in critically ill patients, especially early after ICU admission.

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  1. SciScore for 10.1101/2022.01.10.22269018: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: IRB Approvals: All research protocols (protocols STUDY19050099 and STUDY20040036) were approved by University of Pittsburgh institutional review board and were performed in accordance with the Declaration of Helsinki.
    Consent: Written informed consent was obtained from all research participants or their legally authorized representatives.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    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.