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510(k) Data Aggregation

    K Number
    K161827
    Date Cleared
    2016-12-08

    (156 days)

    Product Code
    Regulation Number
    870.1220
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Reprocessed Response Diagnostic Electrophysiology Catheters can be used in the evaluation of a variety of cardiac arrhythmias from endocardial and intravascular sites.

    Device Description

    The Reprocessed Response Diagnostic Electrophysiology Catheters are manufactured in various fixed curves and electrode spacing for electrophysiological mapping for the evaluation of a variety of cardiac arrhythmias from endocardial and intravascular sites.

    AI/ML Overview

    The provided text is related to a 510(k) premarket notification for reprocessed diagnostic electrophysiology catheters. This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study to prove acceptance criteria for an AI/ML powered medical device.

    Therefore, the requested information (acceptance criteria, device performance, sample sizes for test/training sets, ground truth establishment, expert qualifications, adjudication methods, MRMC study results, or standalone algorithm performance) is not present in the provided text.

    The document discusses:

    • The device being a reprocessed electrophysiology catheter.
    • Its intended use in evaluating cardiac arrhythmias.
    • Various functional and safety tests performed (biocompatibility, cleaning validation, sterilization validation, visual inspection, dimensional verification, electrical continuity and resistance, simulated use, mechanical characteristics, electrical safety testing, packaging validation).
    • The conclusion that the reprocessed catheters are as safe and effective as the predicate devices.

    However, these are not the detailed acceptance criteria and study results typically found for AI/ML device performance.

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