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510(k) Data Aggregation

    K Number
    K201629
    Date Cleared
    2020-12-14

    (181 days)

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

    The Medical Face 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(s), provided non-sterile.

    Device Description

    The Medical Face Masks are Flat Pleated type mask, utilizing Ear Loops way for wearing, and they all have Nose Piece design for fitting the face mask around the nose. The Medical Face Masks are manufactured with three layers. The outer layer is made of spun-bonded polypropylene (PP) non-woven fabric. The middle layer with filtration function is made of melt blown polypropylene (PP) non-woven fabric. The inner layer contact with face is made of polypropylene (PP) fabric. The face mask is provided white color. The Medical Face Masks are single use, disposable device, provided non-sterile.

    AI/ML Overview

    The provided text describes the 510(k) summary for a Medical Face Mask, comparing it to a predicate device. It details the device's characteristics, indications for use, and the non-clinical testing performed to establish substantial equivalence.

    However, the request asks for information related to a study proving a device meets acceptance criteria, specifically in the context of an AI/algorithm-based medical device. The provided document is for a physical medical device (face mask) and therefore does not contain the information requested regarding:

    • AI/algorithm performance metrics
    • Sample sizes for test sets and training sets in an AI context
    • Data provenance for AI models
    • Number of experts and their qualifications for AI ground truth
    • Adjudication methods for AI ground truth
    • Multi-reader multi-case (MRMC) studies for AI
    • Standalone algorithm performance
    • Types of ground truth (pathology, outcomes data) for AI
    • Ground truth establishment for training sets in an AI context

    Given this discrepancy, I will extract the available "acceptance criteria" and "performance" information from the provided document, which are related to the physical properties and performance of the medical face mask. I will clearly state where the requested information is not applicable or not present in the document.


    Acceptance Criteria and Device Performance for Medical Face Mask

    The acceptance criteria for the Medical Face Mask are established through its compliance with specific international and national standards. The "device performance" is demonstrated by the test results showing that the proposed device meets these standards and is substantially equivalent to the predicate device.

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Standard & Parameter)Reported Device Performance (as demonstrated by testing compliance)
    Biocompatibility:
    ISO 10993-5: In Vitro CytotoxicityComplies (test results show pass the requirements)
    ISO 10993-10: Irritation and Skin SensitizationComplies (test results show pass the requirements)
    Performance (per ASTM F2100-19 for Level 2):(Implied compliance to achieve Level 2)
    Bacterial Filtration Efficiency (BFE)Complies with ASTM F2101-19
    Particulate Filtration EfficiencyComplies with ASTM F2299-03 (using latex spheres)
    Fluid ResistanceComplies with ASTM F1862M-17 (Resistance to synthetic blood penetration)
    FlammabilityComplies with 16 CFR 1610 (Standard for Flammability of clothing textiles)
    Dimensional:
    Length17.5 ± 0.88 cm (within predicate's range of 17.5 ± 1 cm)
    Width9.5 ± 0.48 cm (within predicate's range of 9.5 ± 1 cm)

    Note: The document states that "test results demonstrated that the proposed device complies with the following standards," indicating that the device met the performance requirements specified within each standard for its intended classification (ASTM Level 2).

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

    • Sample Size: Not explicitly stated for each specific test in the provided summary. Performance testing is generally conducted on a representative sample of the device.
    • Data Provenance: The tests were conducted by the manufacturer (Shandong Shengquan New Material Co., Ltd., China) to support the 510(k) submission. The document implies these were laboratory tests, not clinical studies.

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

    • Not applicable. This device is a physical product, not an AI/algorithm-based diagnostic tool requiring expert consensus for ground truth on medical images or data. Ground truth for its performance is established through standardized laboratory testing protocols (e.g., measuring filtration efficiency, fluid resistance, biocompatibility).

    4. Adjudication method for the test set

    • Not applicable. This is not an AI/algorithm study involving human interpretation or adjudication for ground truth. The evaluation is based on objective, standardized laboratory test results.

    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 is a physical medical device (face mask), not an AI-assisted diagnostic tool. No MRMC study was performed or is relevant.

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

    • No. This is a physical medical device, not an AI algorithm. Its performance is inherent to its physical properties, not an algorithm.

    7. The type of ground truth used

    • The "ground truth" for this device is based on objective measurements and laboratory testing against established physical and biological standards (e.g., filtration rates, fluid resistance, cytotoxicity, skin sensitization). It is not based on expert consensus, pathology, or outcomes data in the context of diagnostic accuracy.

    8. The sample size for the training set

    • Not applicable. This is a physical device, not an AI model. There is no concept of a "training set" in this context.

    9. How the ground truth for the training set was established

    • Not applicable. As there is no "training set" for a physical medical device, there is no ground truth to be established for it in this context.
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