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510(k) Data Aggregation

    K Number
    K971526
    Date Cleared
    1997-05-21

    (23 days)

    Product Code
    Regulation Number
    862.1475
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    This in vitro diagnostic product is intended for the quantitative determination of HDL cholesterol in human serum.

    Numerous studies have shown an inverse relationship between serum HDL cholesterol and the risk of coronary heart disease. HDL cholesterol also has an important role in the pathogenesis of atherosclerosis.

    Device Description

    An aliquot of serum is added to the first reagent which contains a mixture of polymers and polyanions that bind to the surface of low-density lipoproteins (LDL), very low-density lipoproteins (VLDL) and chylomicrons. These complexed lipoproteins are stabilized, even in the presence of detergent, which is added as part of the second reagent, together with cholesterol enzymes. HDL particles are not stabilized by the polymers and polyanions and become solubilized by the detergent. As a result, only the HDL cholesterol is subject to measurement.

    AI/ML Overview

    The ACE™ HDL-C Reagent is intended for the quantitative determination of HDL cholesterol in human serum. The study provided focuses on establishing substantial equivalence to a predicate device (N-geneous™ HDL Cholesterol Reagent) and to a CDC reference method, rather than specifically defining explicit acceptance criteria in a regulatory sense for a single-arm study. The performance assessment compares key metrics to both the predicate device and the CDC reference method.

    Here's the breakdown of the information requested based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The provided document doesn't explicitly state "acceptance criteria" in a pass/fail format with specific thresholds. Instead, it presents performance summaries for comparison against a predicate device and a reference method, with the implicit acceptance being that the proposed device performs comparably. The document states that "Based on these data, the Schiapparelli Biosystems ACE™ HDL-C reagent is substantially equivalent to the Centers for Disease Control Reference Method and the predicate device, the Genzyme N-geneous HDL Cholesterol Reagent."

    ParameterImplied "Acceptance Criteria" (from Predicate/CDC)Proposed Device Performance (ACE™ HDL-C Reagent)
    Assay RangePredicate: 2 mg/dL to 200 mg/dL2 mg/dL to 100 mg/dL
    Precision
    Within Run (% CV)Predicate: < 1.5 %CV< 2.7 % CV
    Between Run (% CV)Predicate: < 3.8 %CV< 4.6 %CV
    Correlation vs. CDC Ref
    SlopeCDC Ref: 1.011.014
    InterceptCDC Ref: -3.390.13
    rCDC Ref: 0.960.986
    Correlation vs. Phosphotungstic Acid Ppt
    SlopePredicate: 0.81N/A (Proposed vs. Dextran Sulfate Ppt)
    InterceptPredicate: 7.82N/A (Proposed vs. Dextran Sulfate Ppt)
    rPredicate: 0.96N/A (Proposed vs. Dextran Sulfate Ppt)
    Correlation vs. Dextran Sulfate Ppt (Proposed only)N/A (This is a comparison method for the proposed device)
    SlopeN/A0.991
    InterceptN/A0.55
    rN/A0.976

    Note: The document directly compares the proposed device to the CDC reference method for slope, intercept, and r. For other correlation, the proposed device is compared against Dextran Sulfate Ppt, while the predicate is compared against Phosphotungstic Acid Ppt. The implied acceptance is that these values should be "comparable" to demonstrate substantial equivalence.

    2. Sample size used for the test set and the data provenance

    The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective nature of the data). It only provides performance summary data (e.g., precision values, correlation statistics).

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This information is not applicable and not provided in the document. The study involves laboratory-based measurements of HDL cholesterol rather than expert interpretation of medical images or other subjective data. Ground truth is established by a reference laboratory method (CDC Reference Method) or comparative chemical precipitation methods.

    4. Adjudication method for the test set

    This information is not applicable and not provided in the document. Adjudication methods are typically relevant for studies involving human interpretation or subjective assessments, which is not the case for this chemical assay.

    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 in the document. This is a submission for a diagnostic reagent for an automated assay, not an AI-assisted diagnostic tool that involves human readers.

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

    Yes, a standalone performance assessment was done for the ACE™ HDL-C Reagent, as evidenced by the "Performance Assessment" section. This section details the reagent's assay range, precision (within-run and between-run), and correlation against reference methods. There is no human-in-the-loop component for the direct measurement by this reagent.

    7. The type of ground truth used

    The ground truth for the performance assessment was established using a CDC Reference Method for cholesterol determination and chemical precipitation methods (specifically Dextran Sulfate Ppt for the proposed device and Phosphotungstic Acid Ppt for the predicate device within the correlation studies).

    8. The sample size for the training set

    The document does not mention a "training set" in the context of machine learning or algorithm development. This is a diagnostic reagent, and its performance is evaluated through analytical validation, not a machine learning training process.

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

    Not applicable, as there is no "training set" in the context of this device's development as described in the provided summary.

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