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510(k) Data Aggregation

    K Number
    K031042
    Date Cleared
    2003-11-03

    (216 days)

    Product Code
    Regulation Number
    864.7470
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The ATAC Hemoglobin A1C Reagent Kit is intended for use with the ATAC 8000 Random Access Chemistry System as a system for the quantitative determination of Hemoglobin A1C results are used to assess the level of control of a patient's diabetes.

    This reagent is intended to be used by trained personnel in a professional setting and is not intended for home use.

    Device Description

    The ATAC HemoglobinAlC Reagent Kit is intended for the quantitative determination of HemoglobinA1C in whole blood. HemoglobinA1Cresults are used in monitoring glycemic control in diabetic patients. The assay determines total hemoglobin and umole A1C. These values are then used in the calculation of %Hemoglobin A1C reagent is substantially equivalent to the Bayer HemoglobinA1C reagent, Bayer product no. T01-3639-01, cuttently marketed by Bayer Corporation, Tarrytown, New York.

    AI/ML Overview

    The provided text describes the ATAC HemoglobinA1C Reagent Kit and studies performed to demonstrate its effectiveness. Here's an analysis based on your requested information:

    1. Table of Acceptance Criteria and Reported Device Performance

    The text doesn't explicitly state "acceptance criteria" for precision or method comparison in a pass/fail format. Instead, it presents the results of these studies. The "acceptance criteria" are implied by the performance statistics themselves, specifically that the results fall within generally accepted ranges for such assays or are comparable to the predicate device.

    Study TypeAcceptance Criteria (Implied)Reported Device Performance
    Precision%CV values within acceptable limits for HbA1c assays.Control 1: %CV (Within Run) = 3.38%, %CV (Total) = 4.74%
    Control 2: %CV (Within Run) = 2.46%, %CV (Total) = 3.08%
    Patient: %CV (Within Run) = 2.60%, %CV (Total) = 4.66%
    Method ComparisonStrong linear correlation and agreement with a comparative method (TOSOH HPLC). Slope close to 1, intercept close to 0.ATAC 8000 = 0.6367 + 0.9722 x Comparative Method
    Calibration StabilityTotal imprecision of %HemoglobinA1C recoveries over claimed period < 5%.Less than 5% total imprecision over 12 days.
    On-board StabilityTotal imprecision of %HemoglobinA1C recoveries over claimed period < 5%.Less than 5% total imprecision over 10 days.

    2. Sample Size Used for the Test Set and Data Provenance

    • Precision Study:

      • Control 1: n = 32
      • Control 2: n = 31
      • Patient Sample: n = 31
      • Data Provenance: Not explicitly stated, but likely from a laboratory setting as part of a validation study. The patient sample is described as "pooled patient sample," suggesting it's from clinical samples.
    • Method Comparison Study:

      • Sample Size: Not explicitly stated in the provided text. It mentions comparing "Whole blood samples collected from patients."
      • Data Provenance: "Whole blood samples collected from patients." This indicates prospective clinical samples. Country of origin is not specified.

    3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

    This information is not applicable to this type of device. The ATAC HemoglobinA1C Reagent is a laboratory diagnostic assay, and its performance is evaluated against established analytical methods (like TOSOH HPLC for method comparison) and controls, not subjective expert assessment of images or clinical opinions.

    4. Adjudication Method for the Test Set

    This information is not applicable. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among multiple human readers when establishing ground truth, typically in image-based diagnostic or clinical assessment studies. This device's performance is measured by quantitative analytical results.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

    No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study typically involves human readers assessing cases with and without AI assistance, which is irrelevant for a quantitative diagnostic reagent.

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

    Yes, the studies described are standalone performance evaluations of the ATAC HemoglobinA1C Reagent Kit on the ATAC 8000 Random Access Chemistry System. This device is an automated in vitro diagnostic (IVD) assay; its performance is inherently "standalone" in that it produces a quantitative result without direct human interpretation of, for example, an image, which would then be compared to a human's interpretation. The "algorithm" here refers to the chemical reactions and photometric measurements performed by the system.

    7. The Type of Ground Truth Used

    • For Precision: The ground truth is the inherent stability and reproducibility of the assay when run repeatedly on stable samples (controls and pooled patient sample).
    • For Method Comparison: The ground truth is established by a comparative method, specifically the TOSOH HPLC method, which is a widely accepted and established reference method for HbA1c determination.
    • For Linearity, Calibration Stability, and On-board Stability: Ground truth is established by the expected behavior of known calibrators and controls over time and across concentration ranges.

    8. The Sample Size for the Training Set

    This information is not provided and is not applicable in the context of this device. The ATAC HemoglobinA1C Reagent Kit is a chemical assay, not a machine learning algorithm that requires a "training set" in the conventional sense. The "training" for such a system involves calibrating the instrument with known standards and optimizing the reagent formulation and assay parameters based on extensive R&D and analytical validation. The document does not describe a machine learning component that would have a distinct training set.

    9. How the Ground Truth for the Training Set was Established

    As noted above, the concept of a "training set" and associated "ground truth" establishment in the machine learning sense is not applicable to this medical device. The 'ground truth' for developing such a reagent would stem from comprehensive chemical and analytical validation, using reference materials, established laboratory practices, and comparisons to recognized analytical methods during the research and development phase.

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