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510(k) Data Aggregation

    K Number
    K211042
    Date Cleared
    2021-07-15

    (98 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 Procedural Ear-loop Face Mask is 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 a single use, disposable device(s), provided non-sterile.

    Device Description

    The proposed device(s) are Blue color, and Flat Pleated type mask, utilizing Ear Loops way for wearing, and they all has Nose clips design for fitting the face mask around the nose. The proposed device(s) are manufactured with three layers, the inner and outer layers are made of spun-bond polypropylene, and the middle layer is made of melt blown polypropylene filter. The model of proposed device, ear loops, is held in place over the users' mouth and nose by two elastic ear loops welded to the face mask. The elastic ear loops are made of nylon and Dacron. The nose piece contained in the proposed device(s) is in the layers of face mask to allow the user to fit the face mask around their nose, which is made of polypropylene and iron. The proposed device(s) are sold non-sterile and are intended to be single use, disposable device.

    AI/ML Overview

    The provided text is a 510(k) summary for a medical device (Disposable Procedural Ear-loop Face Mask) and focuses on demonstrating substantial equivalence to a predicate device. It contains information about non-clinical testing to support this claim, but it does not describe an AI/ML powered device or the types of studies typically conducted for such devices (e.g., studies involving human readers, ground truth establishment by experts, analysis of AI performance metrics like sensitivity/specificity).

    Therefore, I will extract information related to the performance of the device as tested in the provided document, but many of the requested points regarding AI/ML powered device studies cannot be answered from this text.

    Here's an analysis based on the provided document:

    1. Table of acceptance criteria and the reported device performance

    ItemAcceptance Criteria (Level 3)Reported Device Performance (K211042)Result
    Fluid Resistance Performance ASTM F186229 out of 32 pass at 160 mmHg32 out of 32 per lot pass at 160 mmHg, 3 non-consecutive lots testedPASS
    Particulate Filtration Efficiency ASTM F2299≥ 98%Lot1: 98.92%, Lot2: 98.70%, Lot3: 98.71% (3 non-consecutive lots tested, using a sample size of 32/lot)PASS
    Bacterial Filtration Efficiency ASTM F2101≥ 98%Lot1: 98.89%, Lot2: 98.79%, Lot3: 98.77% (3 non-consecutive lots tested, using a sample size of 32/lot)PASS
    Differential Pressure (Delta P) EN 14683 Annex C
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