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510(k) Data Aggregation

    K Number
    K211454
    Device Name
    Surgical mask
    Date Cleared
    2021-08-18

    (100 days)

    Product Code
    Regulation Number
    878.4040
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The surgical masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids, and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single-use, disposable device, and provided as sterile.

    Level 3 Surgical mask model (Ear-loop): XT10A1
    Level 3 Surgical mask model (Tie-on): XT10B1

    Device Description

    The surgical mask consists of a mask body, a nose piece, and ear loops or ties. The mask body is divided into three layers, the inner and outer layers are made of polypropylene materials; the middle layer is composed of melt-blown cloth (polypropylene); the nose piece is made of polyethylene coated steel wire, the ear loops are made of polyester silk & polyurethane filament, and the ties are made of polypropylene.

    The size specification of the surgical mask:

    • Mask body for ear-loop type: 17.5cm×9.5cm & 14.5cm×9.5cm;
    • Mask body for Tie-on type: 17.5cm×9.5cm
    AI/ML Overview

    The provided text is a 510(k) summary for a surgical mask (K211454) and focuses on demonstrating substantial equivalence to a predicate device through non-clinical testing. It does not describe a study involving human readers or AI assistance. Therefore, information related to AI performance, human reader improvement with AI, or MRMC studies is not available in this document.

    Here's the breakdown of the acceptance criteria and the study proving the device meets them, based solely on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    Name of Test Methodology (standard)PurposeAcceptance CriteriaReported Device Performance (Results)
    ASTM F1862-17Fluid Resistance Performance29 out of 32 pass at 160 mmHgLot 1# pass at 160mmHg; Lot 2# pass at 160mmHg; Lot 3# pass at 160mmHg
    ASTM F2101-19Bacterial Filtration Efficiency Performance≥ 98%Lot 1# 99.7%-99.9%; Lot 2# 99.7%-99.9%; Lot 3# 99.7%-99.9%
    EN 14683:2019Differential Pressure (Delta-P)< 6.0mm H2O/cm²Lot 1# 2.3-4.6; Lot 2# 2.3-4.5; Lot 3# 2.0-3.9
    ASTM F2299-2007Particulate Filtration Efficiency Performance≥ 98%Lot 1# 99.2%-99.8%; Lot 2# 99.0%-99.7%; Lot 3# 99.3%-99.7%
    16 CFR Part 1610FlammabilityClass ILot 1# Class I; Lot 2# Class I; Lot 3# Class I
    ISO 10993-5CytotoxicityNon-cytotoxicUnder the conditions of the study, the subject device was non-cytotoxic
    ISO 10993-10SensitizationNon-sensitizingUnder the conditions of the study, the subject device was non-sensitizing
    ISO 10993-10IrritationNon-irritatingUnder the conditions of the study, the subject device was non-irritating

    2. Sample Size Used for the Test Set and Data Provenance

    The document mentions testing "Lot 1#", "Lot 2#", and "Lot 3#" for Fluid Resistance, Bacterial Filtration Efficiency, Differential Pressure, Particulate Filtration Efficiency, and Flammability. For Fluid Resistance, it specifies "32 Out of 32 pass", indicating a sample size of 32 for that particular test per lot. The exact sample sizes for other performance tests are implied by the "Lot #" reporting but not explicitly stated numerically as a single count per test.

    The data provenance is from non-clinical performance testing conducted on the proposed device's materials and finished products, performed by Jiangsu Xingtong Biotechnology Group Co., Ltd. through various standard test methodologies (e.g., ASTM, EN, ISO). This is prospective testing of the manufactured device. There is no indication of country of origin for the specific data collection, but the manufacturer is based in China.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

    Not applicable. This is a non-clinical study involving standardized physical, chemical, and biological tests, not subjective expert evaluation of medical images or conditions. The "ground truth" is established by the predefined acceptance criteria of the testing standards.

    4. Adjudication Method for the Test Set

    Not applicable. As this is non-clinical testing against standardized criteria, there is no need for expert adjudication. The tests have objective outcomes against set thresholds.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

    No, an MRMC comparative effectiveness study was not done. The submission is for a surgical mask and relies on non-clinical performance and biocompatibility testing for substantial equivalence, not AI or human-in-the-loop performance.

    6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done

    No, a standalone AI algorithm performance study was not done. This device is a physical surgical mask, not an AI-powered diagnostic or therapeutic device.

    7. The Type of Ground Truth Used

    The ground truth for evaluating the surgical mask's performance is based on pre-defined acceptance criteria set by international and national standards for medical device performance and biocompatibility. These include:

    • Physical performance standards: ASTM F1862-17 (Fluid Resistance), ASTM F2101-19 (Bacterial Filtration Efficiency), EN 14683:2019 (Differential Pressure), ASTM F2299-2007 (Particulate Filtration Efficiency), 16 CFR Part 1610 (Flammability).
    • Biocompatibility standards: ISO 10993-5 (Cytotoxicity), ISO 10993-10 (Sensitization, Irritation).
    • Sterilization validation standards: ISO 11135:2014, ISO 11737-1:2018, ISO 10993-7:2008.

    8. The Sample Size for the Training Set

    Not applicable. This is a physical medical device, not an AI/machine learning model. Therefore, no training set for an algorithm was used.

    9. How the Ground Truth for the Training Set was Established

    Not applicable, as there is no training set for an AI algorithm.

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