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510(k) Data Aggregation

    K Number
    K231445
    Date Cleared
    2023-11-16

    (182 days)

    Product Code
    Regulation Number
    888.3660
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    General Indications:
    The LINK Embrace Shoulder System - Reverse Configuration is intended for reverse total shoulder arthroplasty.
    Indications:
    Primary, fracture, or revision total shoulder arthroplasty in a grossly rotator cuff deficient joint with severe arthropathy. A functional deltoid muscle is necessary, and the patient's joint must be anatomically and structurally suited to receive the implants.
    The Reverse Glenoid Baseplate component is intended for cementless fixation with the addition of bone screws.
    The Humeral Stems Standard with CaP (HX) and Short with CaP (HX) are intended for cementless fixation.
    The Humeral Stems Standard without CaP (HX) are intended for cemented or cementless fixation.
    The Humeral Fracture Stems and Proximal Bodies are intended for cemented or cementless fixation.
    The Modular Stems 75mm are intended for cemented or cementless fixation.
    The Modular Stems, fully corundum blasted, are intended for cementless fixation.
    The Modular Stems, fully polished, are intended for cemented fixation.

    Device Description

    This Line Extension portfolio includes:

    • Smaller 25 mm Ø Reverse Glenoid Baseplates (RGBs) in neutral designs and in wedged (10°, 15° and 20°) and lateralized variants (+3mm and +6mm). The new 25mm Ø RGB components include new peripheral 4.5mm Ø cortical screws in lengths of 20-60mm with a reduced head diameter as compared with the predicate 4.5mm Ø cortical screws cleared in K200368. The screws are available in standard and angle-stable/locking versions.
    • Glenospheres in sizes 36mm, 39mm and 42mm diameter with +3mm and +6mm lateralization.
    • Humeral Reverse Tray in a neutral (concentric) version with extended +5mm height.
    AI/ML Overview

    The provided document is a 510(k) summary for a medical device called the "LINK Embrace Shoulder System - Reverse Configuration." It is a premarket notification to the FDA for a new component (25mm diameter reverse glenoid baseplates, glenospheres, and a humeral reverse tray) to an existing shoulder replacement system.

    Based on the information provided in the document, here's a breakdown of the requested points:

    1. A table of acceptance criteria and the reported device performance

    The document does not present quantitative acceptance criteria or specific numerical performance results in a table format for this specific device modification. The performance testing section states:

    Acceptance CriteriaReported Device Performance
    Suitable for intended purpose and Substantially Equivalent to predicate or reference devices with respect to non-clinical performance and design."The results of non-clinical performance testing and evaluations demonstrate that the device is suitable for its intended purpose and Substantially Equivalent to the predicate or reference devices."

    The tests performed were:

    • Range of Motion analysis (ASTM F1378)
    • Bone screw testing
    • Wear testing rationale for no new worst case
    • Glenoid fretting fatigue rationale for no new worst case
    • Humeral fatigue test rationale for no new worst case
    • Micromotion test (ASTM F2028)
    • Biocompatibility Evaluation

    It's important to note that this 510(k) is for an addition/modification to an already cleared device, and the evaluation relies heavily on demonstrating "substantial equivalence" to existing predicate devices through non-clinical testing and rationales, rather than establishing entirely new performance benchmarks.

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

    The document explicitly states: "Clinical performance testing was not required to demonstrate the substantial equivalence of this device." Therefore, there was no clinical "test set" in the sense of human patient data. The "test set" consisted of components tested in laboratory/benchtop settings. The document does not specify the sample sizes (e.g., number of screws tested, number of components for micromotion) for each of the non-clinical tests.

    Data Provenance: The testing was non-clinical (laboratory/benchtop). The manufacturer, Waldemar Link GmbH & Co. KG, is based in Germany.

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

    Not applicable. Since no clinical testing was performed, there was no human "ground truth" to establish for a clinical test set. The "truth" for the non-clinical tests is derived from engineering and materials science principles, and standards (e.g., ASTM).

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

    Not applicable. No clinical test set requiring expert adjudication was used.

    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 physical implantable medical device (shoulder replacement components), not an AI/software device that assists human readers.

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

    Not applicable. This is a physical implantable medical device.

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

    For the non-clinical testing, the "ground truth" is based on:

    • Engineering design specifications
    • Performance requirements outlined in relevant ASTM standards (e.g., ASTM F1378 for Range of Motion, ASTM F2028 for Micromotion)
    • Material properties and biocompatibility standards.
    • Comparisons to the performance characteristics of predicate devices.

    8. The sample size for the training set

    Not applicable. This device is not an AI/machine learning model, so there is no "training set."

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

    Not applicable. As above, this device does not utilize a training set or machine learning.

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