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510(k) Data Aggregation

    K Number
    K983709
    Date Cleared
    1998-10-28

    (7 days)

    Product Code
    Regulation Number
    862.3280
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The SYNCHRON® Systems DAT Low and High Urine Controls 1, in conjunction with SYNCHRON Reagents, are intended for use on SYNCHRON Systems for monitoring the quality control for Amphetamines, Cocaine Metabolite, Opiate 2000 ng, and Phencyclidine in the clinical laboratory.

    Device Description

    The SYNCHRON® Systems DAT Low and High Urine Controls 1 are used for monitoring the quality control for Amphetamines, Cocaine Metabolite, Opiate 2000 ng, and Phencyclidine reagents in the clinical laboratory.

    AI/ML Overview

    This document describes the SYNCHRON® Systems DAT Low and High Urine Controls 1 by Beckman Coulter, Inc. as a quality control material for specific drugs of abuse in urine.

    Here's an analysis of the provided text in relation to your questions:

    1. A table of acceptance criteria and the reported device performance

    The document does not explicitly state quantitative acceptance criteria or detailed performance metrics. Instead, it refers to a "Summary of Performance Data" that claims:

    Acceptance CriteriaReported Device Performance
    Substantial Equivalence to predicate toxicology controls"supports a finding of substantial equivalence to toxicology controls already in commercial distribution."
    Stability"Stress stability studies of the DAT Low and High Urine Controls 1 support the Beckman stability claim of 18 months."

    2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    The document does not provide details on the sample size used for the test set, data provenance (country of origin), or whether the study was retrospective or prospective. It only mentions "Stress stability studies."

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    This information is not provided in the document. The device is a control material for laboratory tests, so the "ground truth" would generally be established by the known concentration of analytes in the control material itself, rather than expert interpretation of a diagnostic image or clinical case.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    This information is not applicable and not provided. Adjudication methods are typically used in studies involving human interpretation or subjective assessments, which is not the case for a quality control material.

    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 information is not applicable and not provided. The device is not an AI-assisted diagnostic tool or an imaging device, so an MRMC study is not relevant.

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

    This information is not applicable and not provided. The device is a chemical control material for laboratory instruments, not an algorithm.

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

    For a quality control material, the "ground truth" for the performance of the device itself would be the known, manufactured concentrations of the target analytes (Amphetamines, Cocaine Metabolite, Opiate 2000 ng, Phencyclidine) within the Low and High Urine Controls. The document doesn't explicitly state how these concentrations were verified, but it's an inherent part of manufacturing such controls.

    8. The sample size for the training set

    This information is not applicable and not provided. As a quality control material, there is no "training set" in the context of machine learning or AI.

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

    This information is not applicable and not provided.

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