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510(k) Data Aggregation

    K Number
    K191500
    Date Cleared
    2019-09-03

    (89 days)

    Product Code
    Regulation Number
    888.3060
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The NuVasive® ACP System is intended for anterior screw fixation of the cervical spine C2-C7 for the following indications: degenerative disc disease (as defined by neck pain of discogenic origin with degeneration of the disc confirmed by patient history and radiographic studies), trauma (including fractures), tumors, deformity (defined as kyphosis, lordosis, or scoliosis), pseudarthrosis, failed previous fusion, spondylolisthesis, and spinal stenosis.

    Device Description

    The NuVasive ACP System is an anterior cervical plating system that consists of a variety of implant components including screws and plates, as well as associated manual general surgical instruments. The implants are available in a variety of different shapes and sizes to suit the individual pathology and anatomical conditions of the patient. The subject device components are manufactured from titanium alloy (Ti-6Al-4V ELI) conforming to ASTM F136 or ISO 5832-3.

    AI/ML Overview

    The provided document is a 510(k) summary for the NuVasive® ACP System, an anterior cervical plating system. It details the device's indications for use, technological characteristics, and performance data to demonstrate substantial equivalence to previously cleared devices.

    1. Table of acceptance criteria and the reported device performance

    Acceptance Criteria (Test Standard)Reported Device Performance (Summary of Results)
    Static and Dynamic Compression (ASTM F1717)Meets or exceeds the performance of the predicate device.
    Static Torsion (ASTM F1717)Meets or exceeds the performance of the predicate device.

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

    The document does not detail specific sample sizes for the mechanical testing. It refers generally to "testing" and "studies" but doesn't quantify the number of units tested. The data provenance is not explicitly stated as retrospective or prospective, but given it's mechanical testing of a new device for regulatory submission, it would inherently be a prospective testing program. The country of origin of the data is implied to be the US, where the manufacturer is located and the regulatory submission is made.

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

    This section is not applicable. The study described is nonclinical mechanical testing, not a clinical study involving human or expert evaluation for ground truth.

    4. Adjudication method for the test set

    This section is not applicable. Mechanical testing does not involve adjudication.

    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

    This section is not applicable. The document describes nonclinical mechanical testing, not an MRMC study or AI-assisted interpretation.

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

    This section is not applicable. The document describes mechanical testing of a medical implant, not an algorithm or AI.

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

    The "ground truth" for this nonclinical study is the performance thresholds defined by the ASTM F1717 standard and the performance of the predicate devices. The device's mechanical properties were tested against these established criteria.

    8. The sample size for the training set

    This section is not applicable. This is a nonclinical mechanical testing study, not a machine learning study that would have a training set.

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

    This section is not applicable. This is a nonclinical mechanical testing study, not a machine learning study.

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