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510(k) Data Aggregation

    K Number
    K070017
    Date Cleared
    2007-01-31

    (28 days)

    Product Code
    Regulation Number
    862.1345
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    PTS PANELS METABOLIC CHEMISTRY PANEL TEST STRIPS

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

    PTS PANELS Metabolic Chemistry Panel Test Strips are intended to be used by medical professionals and individuals in the home to measure glucose, high density lipoprotein cholesterol and triglycerides in fingerstick whole blood. Glucose measurements are used in the management of carbohydrate metabolism disorders. Cholesterol measurements are used in the diagnosis and treatment of disorders involving excess cholesterol in the blood and lipid and lipoprotein metabolism disorders. Lipoprotein measurements are used in the diagnosis and treatment of lipid disorders (such as diabetes mellitus), atherosclerosis, and various liver and renal diseases. Triglycerides measurements are used in the diagnosis and treatment of patients with diabetes mellitus, nephrosis, liver obstruction, other diseases involving lipid metabolism. or various endocrine disorders.

    Device Description

    Dry chemistry test strip for use with PTS reflectance photometer. Single test strip with three tests.

    AI/ML Overview

    The provided text does not contain detailed acceptance criteria or a study that explicitly demonstrates the device meets such criteria. It primarily focuses on the 510(k) summary for a modified medical device, comparing it to predicate devices. The document states "Similarities Between Predicate and Modified Device" and "Differences Between Predicate and Modified Device," but these refer to the device's characteristics and intended use, not performance metrics against acceptance criteria.

    The submission is for a device modification, and the FDA has determined it to be "substantially equivalent" to legally marketed predicate devices, which implies that its performance is considered acceptable based on the already approved predicates. However, the specific performance data or acceptance criteria used for this determination are not detailed in the provided sections.

    Therefore, I cannot populate the table or answer the specific questions about acceptance criteria, study details, sample sizes, ground truth, or expert involvement as this information is not present in the provided text.

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