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510(k) Data Aggregation

    K Number
    K140417
    Date Cleared
    2014-07-09

    (141 days)

    Product Code
    Regulation Number
    888.3060
    Why did this record match?
    Device Name :

    DIVERGENCE MINI-PLATE ANTERIOR CERVICAL FUSION SYSTEM

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

    The DIVERGENCE™ anterior cervical plate and bone screw components are intended for anterior interbody screw fixation from C2-T1. The indications of spinal instrumentation systems should be well understood by the surgeon. The plate and bone screw components are in the temporary stabilization of the anterior spine during the development of spinal first with: 1) degenerative disease (as defined by neck pain of discogenic origin with degeneration of the disc confirmed by paiient history and radios), 2) trauma (including fractures). 3) tunors, 4) defined as kyphosis, lordosis, or scoliosis). 5) pseudoarthrosis, and/or 6) failed previous fusions.

    "The DIVERGENCE™ anterior cervical cage component is intended to be used for amerior cervical interbody fusion procedures in skeletally mature patients with cervical dise disease at one level from the C2-C3 disc . Cervical disc disease is defined as intractable radior myclopathy with herniated disc and/or osteophyte formation on posterior vertebral endplates producing symplomatic nerve root and/or spinal confirmed by radiographic studies. This cage is to be used in patients who have had six weeks of non-overative treatment. The DIVERGENCE™ cage must be used with supplemental fixation. The DIVERGENCE™ cage is also required to be used with antogenous bone graft and/or allogenic bone graft comprised of cancellous bone grafi and is to be implanted via an open, anterior approach.

    When used together, the DIVERGENCE™M components can be used only to treat cervical dise disease.

    Device Description

    The DIVERGENCE™ Anterior Cervical Fusion System consists of temporary implants (plates and bone screws) intended for anterior screw fixation, and fusion devices (interbody cages) intended to stabilize and promote bone fusion during the normal healing process following surgical correction of disorders of the spine. The DIVERGENCE™ anterior cervical plates and bone screws are available in broad range of size offerings that are intended for anterior screw fixation intended for stabilization use during the normal healing process following surgical correction of disorders of the spine. Fixation is provided by bone screws inserted into the vertebral body of the cervical spine using an anterior approach. The DIVERGENCE™ anterior cervical plate and bone screws are made from titanium allov and are provided sterile.

    The DIVERGENCE™ anterior cervical cages available in various widths and heights can be inserted between two cervical vertebral bodies to give support and correction during cervical interbody fusion surgeries. The hollow geometry of the implants allows them to be packed with autogenous bone graft and/or allogenic bone graft comprised of cancellous and/or corticocancellous bone graft. These implants must be used with supplemental fixation. The device is made from medical grade polyetheretherketone (PEEK OPTIMA™), contains titanium alloy wire markers and is provided sterile.

    AI/ML Overview

    The DIVERGENCE™ Anterior Cervical Fusion System is a medical device subject to regulatory review. The provided text is a 510(k) summary, which focuses on demonstrating "substantial equivalence" to previously cleared predicate devices, rather than presenting a detailed study with specific acceptance criteria and performance data as might be found in a clinical trial report or a comprehensive engineering validation study. As such, the information you're requesting regarding quantitative acceptance criteria and detailed study outcomes (like sample sizes for test/training sets, expert qualifications, MRMC studies, and explicit ground truth definitions) is not explicitly available in this type of summary.

    However, based on the text provided, here is how we can interpret and present the available information:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria CategoryReported Device Performance
    Mechanical Performance (Spinal Implants in a Vertebrectomy Model)Met the pre-determined acceptance criteria for all tests according to ASTM F1717-13.
    Mechanical Performance (Intervertebral Body Fusion Devices)Met the pre-determined acceptance criteria for all tests according to ASTM F2077-11.
    Subsidence (Intervertebral Body Fusion Device Under Static Axial Compression)Met the pre-determined acceptance criteria for all tests according to ASTM F2267-04(2011).
    Substantial EquivalenceDemonstrated substantial equivalence to listed predicate devices based on non-clinical test results and supporting documentation.

    Explanation of "Acceptance Criteria" in this context:

    For a 510(k) submission, "acceptance criteria" are typically defined by the recognized consensus standards (like the ASTM standards cited) and the comparative performance to the predicate device. The device "met the pre-determined acceptance criteria for all tests," which implies that its mechanical performance (strength, stability, resistance to subsidence) was comparable to or better than that of the predicate devices and within the established safety and performance limits set by the standards. The exact quantitative values for these criteria are not disclosed in this summary but would be part of the full submission.

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

    • Sample Size for Test Set: Not explicitly stated in the 510(k) summary. These tests are typically conducted on a representative number of physical devices according to the specified ASTM standards.
    • Data Provenance: The tests are non-clinical (laboratory-based mechanical testing) performed to recognized consensus standards (ASTM). No human or animal data is described, so country of origin for clinical data or retrospective/prospective status is not applicable here.

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

    This question is not applicable to this type of submission. The "ground truth" for the non-clinical tests is established by the specified ASTM standards and the measurements obtained during the mechanical testing of the physical devices. There are no human experts "establishing ground truth" in the way one would for image interpretation or diagnosis.

    4. Adjudication Method for the Test Set

    Not applicable. This refers to adjudication of discrepancies in human interpretation, which is not relevant for mechanical testing against standards.

    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 510(k) for a physical medical implant (spinal fusion system), not a software or AI-powered diagnostic device. Therefore, MRMC studies involving human readers and AI assistance are not relevant to this submission.

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

    Not applicable. As above, this is for a physical implant, not an algorithm.

    7. The Type of Ground Truth Used

    The "ground truth" for the performance evaluation in this 510(k) is the mechanical performance measured against established ASTM consensus standards and the comparative performance to the predicate devices. The goal is to demonstrate that the device performs mechanically in a manner substantially equivalent to legally marketed devices and meets relevant safety standards.

    8. The Sample Size for the Training Set

    Not applicable. "Training set" refers to data used to train an algorithm. This is a physical device, and therefore, an algorithmic training set is not relevant.

    9. How the Ground Truth for the Training Set was Established

    Not applicable, as there is no training set for an algorithm.

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