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510(k) Data Aggregation

    K Number
    K100154
    Date Cleared
    2010-05-21

    (121 days)

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

    FIXCET SPINAL FACET SCREW SYSTEM

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

    The X-spine Systems, Inc. Fixcet Spinal Facet Screw system is intended for posterior fixation to the lumbar spine (L1 to S1 inclusive). The system is intended for bilateral, transfacet fixation of the facet joint in order to provide stability for fusion. The system.is indicated for posterior surgical treatment of any or all of the following at the L1 to S1 (inclusive) spinal levels:

    • Degenerative disc disease (as defined by back pain of discogenic origin with degeneration of the disc . as confirmed by patient history and radiographic studies),
    • . Degenerative disease of the facets with pain and/or instability on plain flexion and extension lateral radiographs where there is movement of the vertebral bodies relative to each other of more than 4mm,
    • . Trauma (i.e., fractures and/or dislocations),
    • . Spondylolisthesis,
    • . Spondylolysis,
    • . Pseudoarthrosis and/or failed previous fusions.
    Device Description

    The X-spine Fixcet Spinal Facet Screw System is designed to provide bilateral, transfacet fixation of the spinal facet joint in the lumbar spine. This system consists of titanium alloy bone screws designed to transfix the facet articular process in the spine to enhance spinal fusion and stability. The self-tapping 4.5mm diameter facet screws are available in two configurations: (1) single-threaded screws offered in lengths of 25-45mm (in 5 mm increments); and (2) dual-threaded screws offered in lengths of 30-45mm (in 5 mm increments). The screws are composed of medical grade Titanium alloy (Ti6Al4V) that complies with ASTM F-136.

    The implant components are provided clean and non-sterilized by a healthcare professional using Steam Autoclave in accordance to the instructions for use provided by X-spine Systems Inc., as well as the instructions provided by the manufacturer of the Autoclave.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the Fixcet™ Spinal Facet Screw System. This is a medical device and the submission focuses on its substantial equivalence to previously marketed devices based on mechanical performance tests, rather than a study involving human subjects or AI performance.

    Therefore, many of the requested categories regarding acceptance criteria for AI/human reader performance, sample sizes for test/training sets, expert involvement, and ground truth types are not applicable in this context.

    Here's the information that can be extracted or deduced from the provided text:

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

    The acceptance criteria are implied by the standards the device was tested against. The reported performance is that the device met these standards and was found substantially equivalent to predicate devices.

    Acceptance Criteria (Standard & Test)Reported Device Performance
    ASTM F2193 – Static Compression BendingIndicates substantial equivalence and ability to perform in accordance with intended use.
    ASTM F2193 – Fatigue Compression BendingIndicates substantial equivalence and ability to perform in accordance with intended use.
    ASTM F543 – Torsional Yield StrengthIndicates substantial equivalence and ability to perform in accordance with intended use.
    ASTM F543 – Insertion TorqueIndicates substantial equivalence and ability to perform in accordance with intended use.
    ASTM F543 – Removal TorqueIndicates substantial equivalence and ability to perform in accordance with intended use.
    ASTM F543 – Pullout ForceIndicates substantial equivalence and ability to perform in accordance with intended use.
    ASTM F543 – Self-Tapping PerformanceIndicates substantial equivalence and ability to perform in accordance with intended use.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Sample Size for Test Set: Not specified. The performance data section refers to "implant components" being tested using standards, which implies in-vitro mechanical testing rather than human subject data.
    • Data Provenance: Not specified. Given it's mechanical testing of implant components, location of testing might be relevant, but patient data provenance is not. This is a premarket notification for a medical device focusing on mechanical properties, not clinical data from human subjects.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    Not applicable. "Ground truth" in the context of expert consensus or clinical outcomes is not relevant for this mechanical device testing. The "ground truth" for mechanical testing is adherence to the specified ASTM standards.

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

    Not applicable. This is not a study involving human reader interpretation.

    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

    No. This is not a study comparing human reader performance with or without AI assistance.

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

    No. This document does not pertain to an algorithm or AI.

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

    The "ground truth" for this device's performance is adherence to established engineering and material science standards as defined by ASTM F2193 and ASTM F543 for orthopedic implants.

    8. The sample size for the training set

    Not applicable. This is not an AI or machine learning study, so there is no concept of a "training set."

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

    Not applicable. There is no training set.

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