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510(k) Data Aggregation

    K Number
    K240258
    Date Cleared
    2024-04-18

    (78 days)

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

    The Disposable Medical Face Mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. The Disposable Medical Face Mask is intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This a single use, disposable device(s), provided non-sterile.

    Device Description

    The Disposable Medical Face Mask is blue color, single use, flat-folded masks with nose piece and ear loops. The blue colorant is polypropylene (PP) master batch.

    The body of the mask is composed of three layers: the inner (3rd layer) and outer (1st layers are made of spun-bond polypropylene, the middle (2nd layer) is made of melt blown polypropylene. The nose piece is made of Iron core coated with polypropylene, ear loop is made of Nylon and Spandex.

    Each mask contains ear loops to secure the mask over the user's face and mouth with a bendable nose piece to firmly fit over the nose. This device is not made with natural rubber latex.

    The Disposable Medical Face Masks are sold and are intended to be single use, disposable devices.

    The mask is designed and manufactured in accordance with ASTM F2100-23 Standard Specification for Performance of Materials Used in Medical Face Masks.

    AI/ML Overview

    This document is a 510(k) Premarket Notification for a Disposable Medical Face Mask (M643BE). It details the non-clinical testing performed to demonstrate substantial equivalence to a predicate device.

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

    1. A table of acceptance criteria and the reported device performance:

    Test MethodologyPurposeAcceptance Criteria (for Level 3 Barrier, assumed to be the target for this device given the predicate and tests)Reported Device Performance (3 non-consecutive lots tested, using a sample size of 32/lot)
    Bacterial Filtration Efficiency (ASTM F2101)Measure bacterial filtration efficiency≥95%Passed: Lot 0923: ≥95% Lot 1023: ≥95% Lot 1123: ≥95%
    Differential Pressure (mmH2O/cm²) (EN 14683:2019 Annex C)Determine breathability of the mask<5.0 mmH2O/cm²Passed: Lot 0923: <5.0 Lot 1023: <5.0 Lot 1123: <5.0
    Sub-micron Particulate Filtration Efficiency (ASTM F3502-2022a 8.1)Measure initial particle filtration efficiency≥80%Passed: Lot 0923: ≥80% Lot 1023: ≥80% Lot 1123: ≥80%
    Resistance to Penetration by Synthetic Blood (ASTM F1862-17)Evaluate the resistance to penetration by impact of small volume of synthetic blood32 out of 32 pass at 80 mmHgPassed: Lot 0923: 32 out of 32 pass at 80 mmHg Lot 1023: 32 out of 32 pass at 80 mmHg Lot 1123: 32 out of 32 pass at 80 mmHg
    Flammability (16 CFR Part 1610-2008)Response of materials to heat and flameClass 1Passed: Lot 0923: Class 1 Lot 1023: Class 1 Lot 1123: Class 1
    ISO 10993-5 (Tests for in vitro cytotoxicity)Evaluate potential for cytotoxicityUnder the conditions of the study, non-cytotoxicPassed
    ISO 10993-10 (Tests for irritation and skin sensitization)Evaluate potential for irritationUnder the conditions of the study, not an irritantPassed
    ISO 10993-10 (Tests for irritation and skin sensitization)Evaluate potential for skin sensitizationUnder the conditions of the study, not a sensitizerPassed

    2. Sample size used for the test set and the data provenance:

    • Sample Size: For performance testing (BFE, Differential Pressure, Particulate Filtration, Synthetic Blood Resistance, Flammability), the sample size used was 32 units per lot for 3 non-consecutive lots.
    • Data Provenance: The document does not explicitly state the country of origin where the tests were performed or if the data was retrospective or prospective. Given that the applicant is in Taiwan and the submission correspondent is in China, the testing likely occurred in one of these regions. The testing described is prospective (i.e., new tests conducted specifically for this submission).

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

    This submission does not involve a clinical study or human interpretation of data for the ground truth. The "ground truth" for the performance testing is established by the specified ASTM, EN, and CFR standards' methodologies and acceptance criteria. The qualifications of the personnel performing these standardized laboratory tests are not detailed but are assumed to meet the requirements of the testing laboratories.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

    Not applicable. This is not a study involving human readers or subjective interpretation that would require adjudication. The tests are objective, laboratory-based performance measurements against defined standards.

    5. 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:

    No. This document pertains to a physical medical device (face mask), not an AI-assisted diagnostic tool. Therefore, an MRMC comparative effectiveness study was not performed.

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

    Not applicable. This is not an algorithm-based device. The "standalone" performance here refers to the physical properties of the mask tested in a laboratory setting.

    7. The type of ground truth used:

    The ground truth for this device's performance is based on established industry standards and regulatory requirements (ASTM, EN, CFR, ISO standards). These standards define the test methods and the acceptable performance thresholds for medical face masks.

    8. The sample size for the training set:

    Not applicable. This device is a physical product, not a machine learning model; therefore, there is no "training set."

    9. How the ground truth for the training set was established:
    Not applicable, as there is no training set for a physical medical device.

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