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510(k) Data Aggregation

    K Number
    K191961
    Device Name
    OrthoGold
    Date Cleared
    2019-11-26

    (126 days)

    Product Code
    Regulation Number
    878.4685
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K182682

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

    The OrthoGold 100™ is indicated to provide acoustic pressure shockwaves in the treatment of chronic, full-thickness diabetic foot ulcers with wound areas measuring no larger than 16 cm2, which extend through the epidermis, dermis, tendon, or capsule, but without bone exposure. The OrthoGold 100 is indicated for adult (22 years and older), diabetic patients presenting with diabetic foot ulcers greater than 30 days in duration and is indicated for use in conjunction with standard diabetic ulcer care.

    Device Description

    The OrthoGold 100™ is a pulsed acoustic wave device. It includes an electrically powered generator to generate transient compressed air that rapidly expands to create the acoustic waves, which in turn are propagated through a water-filled coupling membrane attached to the hand-held applicator. The hand-held applicator reflects the acoustic waves towards the treatment area through a silicone membrane and ultrasound transmission gel.

    AI/ML Overview

    The provided document is a 510(k) Premarket Notification from the FDA regarding the OrthoGold 100 device. While it attests to the device's substantial equivalence based on non-clinical performance and a literature review, it does not contain the kind of detailed information typically found in a clinical study report for an AI/device performance evaluation that would include acceptance criteria, specific performance metrics for the device, and detailed information about test sets, ground truth establishment, or multi-reader studies.

    Therefore, I cannot extract the specific information requested in your prompt regarding:

    1. A table of acceptance criteria and the reported device performance.
    2. Sample size used for the test set and data provenance.
    3. Number of experts used to establish ground truth and their qualifications.
    4. Adjudication method for the test set.
    5. MRMC comparative effectiveness study details (effect size of human reader improvement with AI).
    6. Standalone (algorithm only) performance.
    7. Type of ground truth used.
    8. Sample size for the training set.
    9. How ground truth for the training set was established.

    The document discusses "Performance Data – Non-Clinical" (electrical safety, EMC, pressure field measurements) and "Performance Data – Clinical" which refers to a literature review demonstrating successful clinical use and efficacy. It states:

    • Clinical Performance: "A literature review represents the published literature with the subject device through systematic, comprehensive literature searches and those articles known to the manufacturer. These studies demonstrate the successful clinical use with the OrthoGold technology in 224 diabetic foot ulcers. The studies show significant results in complete wound healing and reduction of wound area. The data from these studies establish the efficacy of the subject device to treat chronic, full-thickness diabetic foot ulcers with wound areas measuring no larger than 16 cm2, which extend through the epidermis, dermis, tendon, or capsule, but without bone exposure and the safety of the device as shown with the lack of adverse events."

    This describes the basis for efficacy and safety claims, but not a specific study with defined acceptance criteria and performance metrics for a device (especially an AI-driven one, which this is not) against a held-out test set as per your prompt's requirements. The OrthoGold 100 is an extracorporeal shock wave device, not an AI/software as a medical device (SaMD) that would typically have the metrics and study designs you are asking for.

    The core of this document is a 510(k) submission seeking substantial equivalence to a predicate device, not necessarily a de novo clinical trial proving novel performance against specific statistical targets like an AI model would need.

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