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510(k) Data Aggregation

    K Number
    K070407
    Manufacturer
    Date Cleared
    2007-03-26

    (42 days)

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

    The Dukal medical / surgical masks are indicated as a protective nose and mouth covering for healthcare workers and patients involved in medical and surgical procedures. The masks are indicated in any procedure or situation where there is a risk of microorganism, body fluid and particulate aerosol transfer.

    Device Description

    Dukal Surgical Masks are pleated 3 - ply masks. Inner and outer layers are made of either medical grade tissue or 100% spun-bond polypropylene. Middle layer is made of 100% melt blown polypropylene filter. Ear loops are made of soft latex free elastic loops. The nose piece for all Dukal Masks is a malleable aluminum wire. Masks with splash visors have an anti fog treated plastic shield attached to masks. All of the material used in the construction of the Dukal face masks are being used in currently marketed devices (see predicate information)

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for a non-sterile surgical mask (Dukal Surgical Face Mask, referenced as K070407). However, the information provided focuses primarily on regulatory aspects, device description, and intended use, rather than conducting a detailed study with specific acceptance criteria and performance data in the way a diagnostic AI device would.

    Based on the provided text, here's a breakdown regarding acceptance criteria and study information:

    1. Table of Acceptance Criteria and Reported Device Performance

    For this surgical mask, the "acceptance criteria" are defined by the adherence to a recognized performance standard, specifically ASTM 2100-04. The document states, "Recognized Performance Standard: ASTM 2100-04 Refer to submission for applicable standards."

    The document does not explicitly list the quantitative acceptance criteria defined within ASTM 2100-04 or the specific test results showing the device performing against these criteria in a table format within the provided excerpt. It simply refers to the standard as being part of the larger submission.

    However, based on general knowledge of ASTM F2100 (which is the standard for Medical Face Mask Materials, often referred to as ASTM 2100-04 in older documents), the acceptance criteria typically cover:

    Performance MetricAcceptance Criteria (from ASTM F2100 - General Expectations, not explicitly stated in the provided text for this specific device)Reported Device Performance (Not explicitly detailed in the provided text, only a general assertion of conformance to the standard)
    Bacterial Filtration Efficiency (BFE)Typically >= 95% or >= 98% (depending on level)Implied to meet relevant level of ASTM 2100-04
    Particulate Filtration Efficiency (PFE)Typically >= 95% or >= 98% (depending on level)Implied to meet relevant level of ASTM 2100-04
    Differential Pressure (Delta P)Typically < 5.0 mm H2O/cm² (breathing resistance)Implied to meet relevant level of ASTM 2100-04
    Synthetic Blood Penetration ResistancePass at a certain pressure (e.g., 80 or 120 mmHg)Implied to meet relevant level of ASTM 2100-04
    FlammabilityClass 1 (or other specified class)Implied to meet relevant level of ASTM 2100-04

    Important Note: The provided text only states that ASTM 2100-04 is the recognized standard and refers to the full submission for applicable standards. It does not provide a table with the specific quantitative results for the Dukal Surgical Mask against the various criteria of ASTM 2100-04. The "device performance" in this context is implicitly stated as meeting the requirements of the standard, rather than providing raw data.


    Regarding the other requested information (which is not applicable to a physical surgical mask in the same way it would be for an AI/diagnostic device):

    The questions regarding sample size for test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth types (pathology, outcomes), and training set details are not applicable to the evaluation of a non-sterile surgical mask like the one described in K070407.

    These questions are specifically designed for evaluating the performance of diagnostic algorithms or AI-driven medical devices that interpret images, generate diagnoses, or assist human readers. Surgical masks are physical barrier devices whose performance is assessed through standardized laboratory tests (like those in ASTM F2100) that measure physical properties (filtration, breathability, fluid resistance, flammability), not through clinical studies involving expert interpretation of data or AI model training.

    Therefore, for this device:

    1. Sample size used for the test set and data provenance: Not applicable. Performance is determined by laboratory tests on material samples, not a "test set" of patient data.
    2. Number of experts used to establish the ground truth for the test set and qualifications of those experts: Not applicable. Ground truth for a surgical mask is established by validated laboratory testing methods.
    3. Adjudication method: Not applicable.
    4. Multi Reader Multi Case (MRMC) comparative effectiveness study: Not applicable.
    5. Standalone (i.e., algorithm only without human-in-the-loop performance) study: Not applicable.
    6. Type of ground truth used: For surgical masks, the "ground truth" comes from the results of standardized laboratory tests conducted according to methods specified in ASTM F2100, which define the physical properties and performance characteristics of the mask material.
    7. Sample size for the training set: Not applicable. This is not an AI/ML device.
    8. How the ground truth for the training set was established: Not applicable.

    In summary, the provided document for K070407 confirms conformity to ASTM 2100-04 as the basis for performance acceptance, but does not provide the detailed results of those tests or involve the types of studies relevant to AI/diagnostic software.

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