Alternative Qualitative Fit Testing Method for N95 Equivalent Respirators in the Setting of Resource Scarcity at the George Washington University

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Abstract

The 2019 Novel Coronavirus (COVID-19) has caused an acute shortage of personal protective equipment (PPE) globally as well as shortage in the ability to test PPE such as respirator fit testing. This limits not only the ability to fit PPE to medical practitioners, but also the ability to rapidly prototype and produce alternative sources of PPE as it is difficult to validate fit. At the George Washington University, we evaluated an easily sourced method of qualitative fit testing using a nebulizer or “atomizer” and a sodium saccharin solution in water. If aerosolized saccharin entered candidate masks due to poor fit or inadequate filtration, then a sweet taste was detected in the mouth of the user. This method was tested against previously fit tested Milwaukee N95 and 3D Printed Reusable N95 Respirator as a positive control. A Chinese sourced KN95, cotton cloth material, and surgical mask were tested as other masks of interest. Sensitivity testing was done with no mask prior to fit test. A sweet taste was detected for both the surgical mask and cotton cloth, demonstrating a lack of seal. However, there was no sweet taste detected for the Milwaukee N95, 3D Printed Reusable N95 Respirator, or Chinese KN95. These results demonstrate this could be a valuable methodology for rapid prototyping, evaluation, and validation of fit in a non-clinical environment for use in creation of PPE. This method should be not be used without confirmation in a formal qualitative or quantitative fit test but can be used to preserve those resources until developers are confident that potential new N95 comparable respirators will pass. We strongly suggest validation of masks and respirators with Occupational Safety and Health Administration (OSHA) approved fit testing prior to use in a clinical environment.

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  1. SciScore for 10.1101/2020.04.06.20055368: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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: We detected the following sentences addressing limitations in the study:
    However, this study does allow for rapid testing and cycling of designs and may speed development of PPE during the COVID-19 pandemic in the setting of resource 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.