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510(k) Data Aggregation

    K Number
    K201430
    Manufacturer
    Date Cleared
    2020-06-20

    (19 days)

    Product Code
    Regulation Number
    888.3040
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The ExsoMed InFrame™ Cannulated Fixation System is intended for fixation of intra-articular fractures and non-unions of small bone fragments; arthrodesis of small joints; bunionectomies and osteotomies, including scaphoid and other carpal bones, metatarsals, metatarsals, patella, ulnar styloid, capitellum, radial head and radial styloid.

    Device Description

    The purpose of this Special 510(k) is to add additional sizes to INnate™ Cannulated Screw System. The InFrame™ Cannulated Fixation System includes cannulated stainless screws with a diameter of 2.0 mm and lengths ranging from 10 mm to 50 mm.

    AI/ML Overview

    The provided text describes the regulatory clearance for the ExsoMed InFrame™ Cannulated Fixation System, a metallic bone fixation fastener. However, it does not include information about AI/ML device performance or studies related to AI/ML.

    Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets those criteria for an AI/ML device, as the provided document pertains to a traditional medical device (a screw system for bone fixation).

    The document mainly focuses on:

    • Regulatory Clearance: A 510(k) premarket notification for a traditional medical device.
    • Device Description: Cannulated stainless screws for bone fixation.
    • Predicate Devices: Comparison to other similar, legally marketed screw systems.
    • Performance Testing (Non-Clinical): References testing according to ASTM F543 and engineering analysis for mechanical strength, screw fixation, and usability. This is standard for mechanical devices, not AI/ML.

    In summary, none of the requested information (AI/ML acceptance criteria, study details, sample sizes for test/training sets, expert ground truth, adjudication methods, MRMC studies, or standalone performance for an AI/ML component) is present in the provided text.

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