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510(k) Data Aggregation

    Why did this record match?
    Device Name :

    TAMPAX PEARL SCENTED AND UNSCENTED TAMPONS - JUNIOR, REGULAR, SUPER & SUPER PLUS

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    TAMPAX® Pearl Scented Tampons & TAMPAX® Pearl Unscented Tampons are tampons that are used to absorb menstrual fluid.

    Device Description

    Each tampon is wrapped in an individual plastic film wrapper and packaged in sealed multi-unit containers for retail sale.

    AI/ML Overview

    This looks like a 510(k) premarket notification for a menstrual tampon. These types of devices generally do not involve AI or complex algorithms with acceptance criteria, ground truth, or multi-reader studies in the way medical imaging or CAD devices do.

    The provided text does not contain information about an AI device, acceptance criteria related to algorithmic performance, or a study proving that an AI device meets such criteria.

    Instead, the submission focuses on:

    • Device Description: TAMPAX® Pearl Scented and Unscented Tampons with plastic applicators.
    • Intended Use: To be inserted into the vagina to absorb menstrual fluid.
    • Technological Characteristics: Comparison to predicate devices, noting differences in shape of the uncompressed pad, overwrap material, withdrawal cord, fragrance composition, and applicator color.
    • Safety Assessment: Relying on in vitro microbiological testing, biocompatibility testing, and safety-in-use clinical testing to demonstrate equivalence to predicate devices.
    • Effectiveness: Stating that the device complies with the syngyna absorbency requirements of 21 CFR 801.430. This is the key "acceptance criterion" for effectiveness mentioned, and it's a regulatory standard, not an AI performance metric.
    • Conclusion: The device is safe, effective, and substantially equivalent to predicate devices.

    Therefore, I cannot provide the requested table or answer the questions related to AI device performance, sample sizes for test/training sets, experts for ground truth, or MRMC studies, as these concepts are not relevant to this traditional medical device submission.

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