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510(k) Data Aggregation

    K Number
    K051623
    Manufacturer
    Date Cleared
    2005-07-19

    (29 days)

    Product Code
    Regulation Number
    888.3660
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    ANATOMICAL SHOULDER KEELED GLENOID

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

    This device is intended for cemented use in treatment of the following:

    • Advanced wear and tear of the shoulder joint resulting from degenerative, posttraumatic or rheumatoid arthritis.
    • Omarthrosis.
    • Rheumatoid arthritis.
    • Revision of shoulder prosthesis.
    • Traumatology: the only cone to be used in traumatological indications is the traumatology cone.
    Device Description

    The keeled glenoid component is part of the Anatomical Shoulder System. It provides surgeons with another bone anchorage option while maintaining the system's articular surface geometry.

    AI/ML Overview

    This document is a Summary of Safety and Effectiveness for the Zimmer Anatomical Shoulder™ System Keeled Glenoid, which is a shoulder prosthesis.

    Based on the provided text, the device's acceptance criteria and the study that proves it meets those criteria are as follows:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance CriterionReported Device Performance
    SafetyTesting completed as part of the design assurance process demonstrated that this device is safe.
    EffectivenessTesting completed as part of the design assurance process demonstrated that this device is effective.
    Substantial EquivalenceThe device is substantially equivalent to the predicate device (Anatomica All-Polyethylene Glenoid Component, Zimmer GmbH, K990136). The only modification is minor and does not change the intended use or fundamental scientific technology.
    Manufacturing ProcessesThe device is manufactured, packaged, and sterilized using the same materials and processes as the predicate device.

    2. Sample Size Used for the Test Set and Data Provenance

    • The document refers to "Testing completed as part of the design assurance process" which implies non-clinical testing.
    • Sample Size: Not specified.
    • Data Provenance: The data is described as "Non-Clinical Performance" and directly linked to "design assurance." This indicates in-house testing by the manufacturer (Zimmer, Inc.) rather than external or patient data. It is retrospective in the sense that it's part of the product development and verification process.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

    • This information is not provided in the document. The testing described is non-clinical performance, so it wouldn't involve expert establishment of ground truth in the same way clinical studies do. The "truth" here would be derived from engineering specifications and testing standards.

    4. Adjudication Method for the Test Set

    • This information is not provided. Given that the testing is non-clinical, an adjudication method for a test set (as typically seen in clinical trials with human readers/assessors) is not applicable or described.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the Effect Size of how much human readers improve with AI vs without AI assistance

    • No, an MRMC comparative effectiveness study was not done. This device is a shoulder prosthesis, not an AI-assisted diagnostic tool. Therefore, the concept of human readers improving with AI assistance is not relevant to this submission.

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

    • No, a standalone study (in the context of an algorithm) was not done. This is a medical device (implant), not a software algorithm. The "standalone" performance here refers to the device's physical and mechanical performance, which was assessed through non-clinical testing.

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

    • The ground truth for the non-clinical testing would be based on engineering specifications, mechanical testing standards, and established material properties. For example, tests for strength, wear, and fatigue would have predefined pass/fail criteria based on industry standards and the predicate device's performance.

    8. The sample size for the training set

    • Not applicable. This document describes a medical implant, not a device involving machine learning or AI that would require a "training set."

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

    • Not applicable. As stated above, this device does not utilize AI/ML, so there is no training set or associated ground truth establishment in that context.
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