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510(k) Data Aggregation

    K Number
    K092580
    Device Name
    TIDI FACEMASK
    Manufacturer
    Date Cleared
    2010-02-23

    (186 days)

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

    Surgical mask are devices that are intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating personnel from transfer of micro-organisms, body fluids and particulate material.

    Device Description

    The TIDI® Facemask, are pleated multi-ply design which are supplied non sterile. The outer layers are made of 100% spun-bound polypropylene (SBPP). The filter media is composed of 100% melt-blown polypropylene (MBPP). The inner layer is made of either 100% SBPP or 100% medical grade tissue paper. The ear loops are made of latex free elastic. The nosepieces are made of malleable aluminum, and can be supplied with an anti fog strip made of polyester urethane foam. All materials used in the construction of the mask are being used in currently marketed devices. The mask covers the nose and mouth, and is secured to the face using the attached ear loops. The TIDI® Facemasks are intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating personnel from transfer of microorganisms, body fluids and particulate material.

    AI/ML Overview

    The document provided describes the TIDI® Facemask, a surgical mask, and its nonclinical testing to demonstrate substantial equivalence to predicate devices, rather than a novel AI/software medical device. As such, most of the requested information regarding AI device evaluation (e.g., sample sizes for test/training sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth for training data) is not applicable to this submission.

    However, I can extract the acceptance criteria and performance data for the TIDI® Facemask as presented in the document.

    Acceptance Criteria and Reported Device Performance

    The study referenced is a nonclinical test performed to demonstrate that the TIDI® Facemask meets the specified acceptance criteria of ASTM F 2100-07 Standard Specification for Performance of Materials Used in Medical Face Mask. This standard defines requirements for different performance classes (Low Barrier, Moderate Barrier, High Barrier). The TIDI® Facemask was tested against these criteria.

    Performance CharacteristicsAcceptance Criteria (High Barrier)TIDI® Facemask Test Results Summary
    Bacterial Filtration Efficiency Performance (%) (ASTM 2101)≥98>99.9
    Differential Pressure (Delta-P) (mm H2O/cm²) (MIL-M 36954C)<4.03.4
    Sub-micron Particulate Filtration Efficiency at 0.1 micron Performance (%) (ASTM F 2299)≥9899.6
    Resistance to penetration by synthetic blood, Minimum pressure in mmHg for pass results. (ASTM F 1862)160 (for High Barrier)Pass @ 80 mm Hg
    Flammability Class (16CFR Part 1610)Class 1Class 1

    Additional Information (Not applicable to AI devices, but relevant to this submission):

    • Sample sized used for the test set and the data provenance: Not specified, as it refers to performance testing of physical materials, not an AI model. The tests are for the mask material itself.
    • Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for masks is established by standardized physical/biological tests.
    • Adjudication method for the test set: Not applicable.
    • If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable, as this is a physical medical device (surgical mask), not an AI device.
    • If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
    • The type of ground truth used: Standardized laboratory test results for physical properties and filtration efficacy.
    • The sample size for the training set: Not applicable, as this is not an AI/machine learning device.
    • How the ground truth for the training set was established: Not applicable.
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