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510(k) Data Aggregation

    K Number
    K040537
    Date Cleared
    2004-04-22

    (51 days)

    Product Code
    Regulation Number
    884.5980
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    AMS APOGEE VAULT SUSPENSION SYSTEM

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

    The Apoqee™ Vault Suspension System is intended for use in vaginal vault suspension to treat pelvic organ prolapse.

    Device Description

    The Apogee™ Vault Suspension System consists of needles and connectors used to pass a polypropylene mesh for support of the vaginal vault.

    AI/ML Overview

    The provided text is a 510(k) Summary submission for the AMS Apogee™ Vault Suspension System. It primarily focuses on demonstrating substantial equivalence to predicate devices for regulatory approval, rather than detailing a specific study to prove the device meets pre-defined acceptance criteria with performance metrics.

    Therefore, many of the requested sections (Table of acceptance criteria and reported device performance, sample size, data provenance, number of experts, adjudication method, MRMC study, effect size, standalone performance, type of ground truth for test set, training set details) cannot be fully populated from the provided text.

    Here's an attempt to answer based only on the information available in the given text:

    1. Table of acceptance criteria and the reported device performance

    The document does not explicitly state quantitative acceptance criteria or reported device performance metrics in numerical terms. Instead, it states: "The mesh used in the Apogee™ Vault Suspension System has been tested in accordance with FDA's Guidance for the Preparation of a Premarket Notification Application for a Surgical Mesh and has been shown to be equivalent to the listed predicate devices. In addition, the other components have demonstrated substantial equivalence to the predicate devices in terms of mechanical performance and biocompatibility."

    This implies that the acceptance criteria revolved around demonstrating equivalence to predicate devices in the following areas:

    Acceptance CriteriaReported Device Performance
    Equivalence to predicate devices for surgical mesh in accordance with FDA guidance."has been shown to be equivalent to the listed predicate devices."
    Substantial equivalence in mechanical performance for other components."have demonstrated substantial equivalence to the predicate devices in terms of mechanical performance."
    Substantial equivalence in biocompatibility for other components."have demonstrated substantial equivalence to the predicate devices in terms of ... biocompatibility."

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

    Not provided in the document. The text mentions "tested," but no details about the sample sizes or the nature (retrospective/prospective, country of origin) of the data, if any clinical data was involved. The testing appears to be primarily bench or material-based to demonstrate equivalence.

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

    Not applicable. The provided text describes tests for material equivalence and mechanical performance, not diagnostic performance requiring expert interpretation or ground truth establishment in a clinical context.

    4. Adjudication method for the test set

    Not applicable. This concept applies to studies involving human interpretation or clinical endpoints, which are not detailed here.

    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

    Not applicable. This is a medical device, not an AI or imaging diagnostic device where MRMC studies are typical.

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

    Not applicable. This is a medical device, not an AI or imaging diagnostic algorithm.

    7. The type of ground truth used

    For the mesh, the ground truth was established by adherence to "FDA's Guidance for the Preparation of a Premarket Notification Application for a Surgical Mesh" and its comparison to the characteristics of the predicate devices. For other components, ground truth for mechanical performance and biocompatibility would be based on established engineering standards and biological safety assessments, again likely benchmarked against predicate devices. No specific "ground truth" in the clinical sense (e.g., pathology, outcomes data) is mentioned as being directly used in this summary.

    8. The sample size for the training set

    Not applicable. This is a medical device, not a machine learning model where a training set would be relevant.

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

    Not applicable (as above).

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