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510(k) Data Aggregation

    K Number
    K010646
    Manufacturer
    Date Cleared
    2001-03-30

    (25 days)

    Product Code
    Regulation Number
    N/A
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use
    Device Description
    AI/ML Overview
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    K Number
    K994234
    Manufacturer
    Date Cleared
    1999-12-30

    (14 days)

    Product Code
    Regulation Number
    862.3650
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    A home drug screening, and if needed, confirmation service. This kit provides a preliminary result for the detection/presence of the following drugs of abuse in urine: Opiates

    Device Description

    Immunoassay for the qualitative detection of Opiates in urine

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and the study details for the At Home Drug Test (Model 9083), based on the provided CPT code K994234:

    Acceptance Criteria and Reported Device Performance

    The provided document does not explicitly state pre-defined acceptance criteria (e.g., "must achieve X% accuracy"). Instead, it compares the device's performance to predicate devices and asserts substantial equivalence based on the observed correlation and accuracy. The primary performance metrics reported are correlation and overall accuracy.

    Acceptance Criteria (Implied)Reported Device Performance (Opiates)
    High correlation with GC/MS and predicate immunoassay>98% correlation with Behring EMIT II and GC/MS methodology
    High overall accuracy for professional users>97% overall accuracy
    High overall accuracy for lay users97.3% (918/943) for Opiates

    Study Details

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

    • Clinical Sample Correlation Study: The exact sample size is not explicitly stated, but it refers to "clinical specimens." The provenance is also not specified beyond "clinical specimens."
    • Blind Labeled Spiked Study: No sample size is given.
    • Professional User Study: No explicit sample size is given, but it states "excellent overall accuracy (>97%) in the hands of professional users."
    • Consumer Study: The overall consumer study involved 4557/4715 correct readings. For opiates specifically, the test set size was 943 (918 correct readings). The provenance is not specified other than "consumer study." All studies appear to be prospective to evaluate the device's performance.

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

    • Clinical Sample Correlation Study: The ground truth was established by two methodologies:
      • Behring EMIT II: This is another immunoassay, likely read by laboratory professionals.
      • GC/MS methodology: This is a gold standard laboratory confirmation method, performed by trained laboratory technicians/analysts. The number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience") are not detailed.
    • Professional User Study & Consumer Study: The "ground truth" for evaluating the At Home Drug Test's performance was the GC/MS methodology. The number and qualifications of experts involved in running the GC/MS are not specified beyond being standard laboratory practice.

    4. Adjudication method for the test set:

    The document does not describe a formal adjudication method (e.g., 2+1, 3+1). For the clinical correlation study, the comparison was made against established laboratory methods (Behring EMIT II and GC/MS). For the professional and consumer studies, the At Home Drug Test's results were compared against GC/MS results. It implies a direct comparison rather than an adjudication process requiring multiple readers for the device itself.

    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 device is an in vitro diagnostic immunoassay for drug detection, not an AI-powered diagnostic imaging device. Therefore, an MRMC comparative effectiveness study to assess the impact of AI assistance on human readers was not performed and is not applicable. The device provides a direct qualitative result (positive/negative) via visual color change, which is then interpreted by the user.

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

    The device itself is a standalone test in the sense that it produces a result without human interpretation of complex data (like an algorithm analyzing an image). However, it is an "At Home Drug Test," meaning it relies on a human user to perform the test and visually interpret the result. Therefore, studies were done for both professional users and lay users, indicating that the "human-in-the-loop" aspect is crucial, especially for the home-use context. The device's performance is its standalone performance in a qualitative sense, but the interpretation step is performed by a human.

    7. The type of ground truth used:

    The primary ground truth used for establishing the performance characteristics was GC/MS (Gas Chromatography/Mass Spectrometry) methodology. This is a highly accurate and widely accepted laboratory confirmation method for drug presence and concentration. In some instances, another predicate immunoassay (Behring EMIT II) was also used for correlation.

    8. The sample size for the training set:

    The document does not explicitly mention a "training set" or "validation set" in the context of machine learning or algorithm development. This device is an immunoassay, not an AI/ML-based device. The studies described are performance evaluation studies, not algorithm training or validation studies.

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

    As noted above, there's no mention of a "training set" because this device does not use an AI/ML algorithm that requires training. The "ground truth" for the performance evaluation studies was established using GC/MS methodology, as described in point 7.

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