Contamination of personal protective equipment during COVID-19 autopsies

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Abstract

Confronted with an emerging infectious disease at the beginning of the COVID-19 pandemic, the medical community faced concerns regarding the safety of autopsies on those who died of the disease. This attitude has changed, and autopsies are now recognized as indispensable tools for understanding COVID-19, but the true risk of infection to autopsy staff is nevertheless still debated. To clarify the rate of SARS-CoV-2 contamination in personal protective equipment (PPE), swabs were taken at nine points in the PPE of one physician and one assistant after each of 11 full autopsies performed at four centers. Swabs were also obtained from three minimally invasive autopsies (MIAs) conducted at a fifth center. Lung/bronchus swabs of the deceased served as positive controls, and SARS-CoV-2 RNA was detected by real-time RT-PCR. In 9 of 11 full autopsies, PPE samples tested RNA positive through PCR, accounting for 41 of the 198 PPE samples taken (21%). The main contaminated items of the PPE were gloves (64% positive), aprons (50% positive), and the tops of shoes (36% positive) while the fronts of safety goggles, for example, were positive in only 4.5% of the samples, and all the face masks were negative. In MIAs, viral RNA was observed in one sample from a glove but not in other swabs. Infectious virus isolation in cell culture was performed on RNA-positive swabs from the full autopsies. Of all the RNA-positive PPE samples, 21% of the glove samples, taken in 3 of 11 full autopsies, tested positive for infectious virus. In conclusion, PPE was contaminated with viral RNA in 82% of autopsies. In 27% of autopsies, PPE was found to be contaminated even with infectious virus, representing a potential risk of infection to autopsy staff. Adequate PPE and hygiene measures, including appropriate waste deposition, are therefore essential to ensure a safe work environment.

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  1. SciScore for 10.1101/2021.07.12.21260357: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Written consent was obtained from the next of kin to perform the autopsies.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Vero E6 cells were maintained and cultivated under standard conditions (15).
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    The RT-qPCR was conducted using the QuantStudio 5 Dx real-time PCR Instrument, and the data were analyzed and interpreted using QuantStudio™ design and analysis software (v.1.2x, Thermo Fisher, Carlsbad, CA, USA).
    QuantStudio™
    suggested: None
    All calculations were performed using the statistics package Sigmaplot 13.0
    Sigmaplot
    suggested: (SigmaPlot, RRID:SCR_003210)

    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.