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510(k) Data Aggregation

    K Number
    K981771
    Date Cleared
    1998-06-12

    (24 days)

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

    Immunoassay for the qualitative detection of opiates in human urine to assist in screening of drug of abuse samples and/or diagnosis of clinical symptoms associated with the use of drugs

    Device Description

    AccuSign MOP, BioSign MOP, and STATUS DS MOP

    AI/ML Overview

    The document provided does not contain the detailed information necessary to fully answer all aspects of the request regarding acceptance criteria and a study proving device performance. The document is an FDA 510(k) clearance letter for three opiate detection devices (AccuSign MOP, BioSign MOP, and STATUS DS MOP), indicating substantial equivalence to a predicate device. It defines the intended use but does not include specific performance study data, acceptance criteria, sample sizes, ground truth establishment, or expert details typical of a detailed performance study report.

    Therefore, many of the requested fields cannot be populated from the provided text.

    Here's what can be extracted and what is missing:

    1. Table of acceptance criteria and the reported device performance:

    This information is not present in the provided document. An FDA 510(k) clearance letter acknowledges the submission and clearance but typically does not include the detailed performance data or acceptance criteria that were part of the submission.

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

    This information is not present in the provided document.

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

    This information is not present in the provided document.

    4. Adjudication method for the test set:

    This information is not present in the provided document.

    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 is an in-vitro diagnostic device (immunoassay for opiate detection). The concept of "human readers improve with AI vs without AI assistance" is not applicable to this type of device. There's no indication of AI involvement or a human interpretive component in the context of MRMC for this device.

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

    This is an in-vitro diagnostic device. Its performance is inherently "standalone" in terms of its ability to detect opiates in urine, as it's an immunoassay. The device itself performs the detection. However, the term "standalone" as used in the context of "algorithm only" or "without human-in-the-loop" typically refers to AI/ML models. While the device operates without continuous human input for each test result, it's not a software algorithm in the AI/ML sense. Performance data for such a device would typically focus on sensitivity, specificity, accuracy, precision, etc., rather than algorithm-only performance. The specifics of these metrics are not provided in the document.

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

    For an immunoassay detecting opiates, the ground truth would typically be established by a reference method for drug detection (e.g., Gas Chromatography-Mass Spectrometry (GC/MS) or Liquid Chromatography-Mass Spectrometry (LC-MS)) on the same urine samples. However, the specific method used for ground truth is not mentioned in the document.

    8. The sample size for the training set:

    This information is not present in the provided document. For 510(k) submissions of IVD kits, the concept of a "training set" in the machine learning sense is generally not applicable as these are typically chemical/biological assays, not AI algorithms. Performance is evaluated on clinical samples.

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

    This information is not present in the provided document. As mentioned above, the concept of a "training set" in this context is not directly applicable.


    Summary of what is known from the document:

    • Device Name: AccuSign MOP, BioSign MOP, and STATUS DS MOP
    • Regulatory Class: II
    • Product Code: DJG
    • Indications For Use: Immunoassay for the qualitative detection of opiates in human urine to assist in screening of drug of abuse samples and/or diagnosis of clinical symptoms associated with the use of drugs.
    • K981771: The 510(k) number for this clearance.
    • Clearance Date: June 12, 1998
    • Use Type: Professional use and Prescription Use.

    To obtain the detailed performance study information, one would typically need to review the original 510(k) submission (K981771) itself, which would contain the test reports and data that led to the substantial equivalence determination. The FDA clearance letter only states that the device was found substantially equivalent, implying that the submitted data met the required criteria.

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