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510(k) Data Aggregation

    K Number
    K051728
    Date Cleared
    2005-07-20

    (23 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MODIFICATION TO SHOULDER FIXATION SYSTEM

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

    The Modified Shoulder Fixation System is intended for fractures and fracture dislocations, osteotomies, and non-unions of the proximal Humerus.

    Device Description

    The Modified Shoulder Fixation System is a set of orthopedic plates and fasteners supplied in a sterilization tray together with several reusable and disposable tools. The set of orthopedic plates and fasteners provided in the sterilization tray consists of the following implantable devices: • Shoulder Plates • Multidirectional and 90° Lock Screws • 90° Set Screws • Pegs Also, provided in the sterilization tray are the re-useable instruments

    AI/ML Overview
    1. Table of Acceptance Criteria and Reported Device Performance:

    The provided document does not contain explicit acceptance criteria and device performance metrics in the format of a table. Instead, it describes a "Summary of Substantial Equivalence" and states that "The equivalence was confirmed through pre-clinical testing."

    Acceptance CriteriaReported Device Performance
    Substantially equivalent to predicate device (Shoulder Fixation System, K042059)Equivalence confirmed through pre-clinical testing.
    1. Sample size used for the test set and the data provenance:

    The document does not specify a distinct "test set" or its sample size. The substantial equivalence was confirmed through "pre-clinical testing," which typically involves mechanical and/or bench testing rather than studies with patient data. Therefore, data provenance in terms of country of origin or retrospective/prospective is not applicable as patient data was not used.

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

    This information is not provided in the document. Given that the equivalence was based on "pre-clinical testing," ground truth would likely be established through engineering specifications and test standards, not expert medical consensus on a test set.

    1. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

    This information is not provided. As mentioned, the evaluation was based on pre-clinical testing, making formal adjudication methods for a medical test set irrelevant.

    1. 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:

    A multi-reader multi-case (MRMC) comparative effectiveness study was not done. The device is a physical orthopedic implant (Shoulder Fixation System) and not an AI-powered diagnostic or assistive tool for human readers. Therefore, there is no discussion of human reader improvement with or without AI assistance.

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

    A "standalone" performance study in the context of an algorithm or AI was not done. The device is a physical orthopedic implant, not an algorithm.

    1. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

    The ground truth for demonstrating substantial equivalence was based on pre-clinical testing which would involve engineering and mechanical performance data, often compared against established standards for material properties and mechanical strength of similar devices. It is not based on expert consensus, pathology, or outcomes data in the clinical sense.

    1. The sample size for the training set:

    The concept of a "training set" is not applicable as this is a medical device (implant) clearance, not an AI or machine learning model.

    1. How the ground truth for the training set was established:

    Not applicable, as there is no training set for this type of device.

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