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510(k) Data Aggregation

    K Number
    K150005
    Manufacturer
    Date Cleared
    2015-02-19

    (48 days)

    Product Code
    Regulation Number
    874.1820
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Checkpoint® Head & Neck is a single-use device intended to provide electrical stimulation of exposed motor nerves or muscle tissue to locate and identify nerves and to test nerve and muscle excitability.

    Device Description

    The Checkpoint Head & Neck is a small handheld device used by a surgeon to deliver electrical stimulation intraoperatively to locate and identify nerves, and to test nerve integrity and muscle excitability. These are sterile disposable devices designed to use with one-handed control.

    The device uses a stimulating probe that is attached to the distal end and a cable attached to a needle return electrode on the proximal end. The microcontroller in the device includes embedded firmware that controls the function of the Stimulator. The firmware cannot be modified by the user. The stimulator is powered by internal batteries that are not user replaceable, thereby minimizing the potential for re-use.

    AI/ML Overview

    The provided text is a 510(k) summary for the NDI Medical, LLC Checkpoint® Head & Neck surgical nerve stimulator. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed clinical study with acceptance criteria and performance metrics typical of a novel device approval process.

    Therefore, the requested information regarding acceptance criteria, reported device performance, sample sizes, ground truth establishment, expert qualifications, adjudication methods, multi-reader multi-case studies, and standalone performance is not explicitly available within the provided document.

    Here's a breakdown of what can be extracted regarding testing and related information, and where the information is missing:


    Summary of Device Acceptance Criteria and Performance (Based on Available Information)

    As this is a 510(k) submission for a device modification, the "acceptance criteria" are primarily based on demonstrating substantial equivalence to the predicate device and meeting general safety and performance standards for surgical nerve stimulators. The document does not provide specific quantitative acceptance criteria (e.g., minimum sensitivity, specificity, or accuracy) for clinical performance in the way one might expect for an AI diagnostic device. Instead, "performance" is demonstrated through various engineering and safety tests.

    Acceptance Criteria CategoryReported Device Performance / Evaluation Method
    BiocompatibilityTesting performed, results not detailed
    Electrical SafetyTesting performed (current and patient leakage current), results not detailed
    Electromagnetic Compatibility (EMC)Testing performed, results not detailed
    Design Verification & ValidationTesting performed, results not detailed
    Functionality (Stimulus Delivery)LED indicators for stimulus delivery and non-delivery, software/firmware control
    Intended UseMeets the same intended use as the predicate device
    Technological CharacteristicsSimilar to predicate device, with noted differences in shut-off time and pulse duration settings.

    Missing Information and Why it's Not Present:

    The provided document is a 510(k) summary, which is a premarket notification to the FDA. For devices seeking 510(k) clearance, the primary goal is often to demonstrate "substantial equivalence" to a legally marketed predicate device, rather than proving the safety and effectiveness from scratch through extensive clinical studies with detailed performance metrics.

    For this specific device, a surgical nerve stimulator/locator, the demonstration of substantial equivalence relies heavily on:

    • Same intended use.
    • Similar technological characteristics.
    • Biocompatibility, electrical safety, and EMC testing to ensure it meets general performance standards for such devices.

    Therefore, the document does not contain the following information:

    1. Sample size used for the test set and the data provenance: Clinical performance data (like sensitivity/specificity studies) with designated test sets is not detailed as the primary path for clearance here is substantial equivalence based on engineering and safety testing.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as a formal test set with expert-established ground truth is not described.
    3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
    4. 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 is a medical device, not an AI diagnostic imaging algorithm. MRMC studies are not relevant here.
    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is a human-operated surgical tool.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable for the type of testing described in this 510(k). The "ground truth" for electrical stimulation devices often relates to known electrical properties and physiological responses, tested in a laboratory or preclinical setting.
    7. The sample size for the training set: Not applicable, this is not an AI/ML device requiring a training set.
    8. How the ground truth for the training set was established: Not applicable.

    In conclusion: The provided 510(k) summary focuses on the technical and regulatory aspects of device modification and substantial equivalence. It confirms that "biocompatibility testing, electrical testing (safety and electromagnetic compatibility), as well as design verification and validation testing" were performed, but it does not provide the specific quantitative results or the detailed clinical study data that you would expect for a diagnostic AI device requiring the specified acceptance criteria and ground truth information.

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