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510(k) Data Aggregation

    K Number
    K213783
    Device Name
    Apyx
    Manufacturer
    Date Cleared
    2022-04-05

    (123 days)

    Product Code
    Regulation Number
    884.4530
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Apyx is intended for attaching sutures to ligaments of the pelvic floor.

    Device Description

    The Apyx device is indicated for anchoring sutures to ligaments of the pelvic floor. The device consists of an implantable nitinol anchor with 4 prongs configured with either non-absorbable or resorbable suture. The anchor-suture assembly is contained within a cartridge, wherein the anchor/suture assembly is deployed to the target site from the cartridge with an applicator. An optional retriever can be used to remove the anchor in the event of sub-optimal placement of an Anchor during the index procedure. The Apyx device is a single use device which is supplied sterile.

    AI/ML Overview

    The provided text describes a 510(k) submission for the Apyx device, which is intended for attaching sutures to ligaments of the pelvic floor. The submission claims substantial equivalence to the predicate device, POP Medical Solutions, NeuGuide (K160569). However, the document does not contain a table of acceptance criteria and reported device performance or information about a specific study proving the device meets acceptance criteria related to efficacy metrics for an AI/ML algorithm.

    The information provided is primarily related to the mechanical and biocompatibility testing of the Apyx device as a medical instrument, not an AI/ML system. Therefore, I cannot fulfill the request for information on acceptance criteria and a study proving an AI/ML device meets them, as those details are not present in the provided text.

    Based on the available text, I can only extract general performance data categories and a cadaver study description for the mechanical device as follows:


    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not provide a table of acceptance criteria with specific numerical targets for performance metrics (e.g., sensitivity, specificity, accuracy) for an AI/ML device. It lists general performance data categories for the Apyx medical device (a mechanical fixation device), along with a summary of cadaver testing.

    Performance Data Category (for Apyx Mechanical Device)Reported Device Performance
    Biocompatibility testing (ISO 10993)Consistent with intended duration of contact for Cytotoxicity, Sensitization, Pyrogenicity, Irritation, Intracutaneous reactivity.
    Chemical characterization & toxicological risk assessment (ISO 10993-18)Addresses biocompatibility endpoints of Genotoxicity, Acute systemic toxicity, Chronic systemic toxicity, Carcinogenicity, Developmental/reproductive toxicity.
    Sterilization validation (ISO 11135)Performed.
    Packaging validationPerformed.
    Shelf-life validationPerformed.
    Dimensional verificationPerformed.
    Anchor fracture resistancePerformed.
    Anchor fixation pull outPerformed.
    Suture detachmentPerformed.
    Suture tensile strengthPerformed.
    MRI compatibilityPerformed.
    Corrosion resistance (ASTM F2129)Performed.
    Bond strengthPerformed.
    Cadaver TestingUsers successfully delivered and retrieved anchors through a transvaginal approach. No complications or unanticipated risks. All anchors accurately delivered to target ligament, no damage to surrounding structures. Concluded device meets design requirements and is suitable for intended use.

    The subsequent questions (2-9) are specifically tailored to the evaluation of an AI/ML-based medical device. Since the provided document describes a mechanical medical instrument (Apyx) and not an AI/ML product, these questions are not applicable to the information given. The text does not mention any AI/ML components, software algorithms, or their performance evaluation. Therefore, I cannot answer questions 2 through 9 based on the provided input.

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