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510(k) Data Aggregation

    K Number
    K981416
    Date Cleared
    1998-06-24

    (65 days)

    Product Code
    Regulation Number
    878.4400
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    MAGNATEK ELECTROSURGICAL UNITS MODELS, ESU-10, ESU-15

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

    The ESU-10 / ESU-15 units is to be used in order to cut and coagulate (burn) the skin in surgical procedures.

    Device Description

    Electrosurgical Units, Device Model: ESU-10 / ESU-15

    AI/ML Overview

    This document is a 510(k) clearance letter from the FDA for an electrosurgical unit. It confirms that the device is substantially equivalent to a previously marketed device. However, it does not contain the detailed information needed to answer your request about acceptance criteria and study data.

    Here's a breakdown of why and what kind of information is missing:

    Why the requested information is not present in this document:

    • This is a clearance letter, not a study report. The FDA 510(k) clearance letter primarily states that a device is substantially equivalent to a predicate device and can be marketed. It does not typically include the specifics of performance studies, acceptance criteria, or detailed ground truth methodologies.
    • The device is an Electrosurgical Unit. For this type of device, the "performance" is often related to electrical safety, power output accuracy, tissue effect (cutting/coagulation effectiveness), and biocompatibility, rather than diagnostic accuracy metrics like sensitivity, specificity, or AUC, which are common for AI/ML-driven diagnostic devices.
    • The clearance date is June 24, 1998. AI/ML-driven medical device evaluations, with their specific metrics and study designs, were not common or required in 1998 in the way they are today.

    Therefore, I cannot provide the requested information from this document. It does not describe a study involving algorithms, test sets, experts, or ground truth for diagnostic performance.

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