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510(k) Data Aggregation

    K Number
    K100341
    Date Cleared
    2010-05-04

    (88 days)

    Product Code
    Regulation Number
    864.5220
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    SpermCheck® Fertility is a qualitative test that detects sperm concentration at or above 20,000,000 sperm/mL. The test is intended for use as an aid in the determination of a man's fertility status. For in vitro, over the counter home use.

    Device Description

    SpermCheck® Fertility is an immunochromatographic test for the rapid, qualitative detection of sperm concentration.

    AI/ML Overview

    The provided text describes the 510(k) summary for the SpermCheck® Fertility device. Here's a breakdown of the requested information based on the text:

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

    The document does not explicitly state "acceptance criteria" with specific numerical thresholds that the device had to meet and then report its performance against them. Instead, it focuses on substantial equivalence to existing devices. The key performance characteristic mentioned is its ability to detect sperm concentration at or above 20,000,000 sperm/mL.

    Performance MetricReported Device Performance
    Qualitative detection of sperm concentrationDetects sperm concentration at or above 20,000,000 sperm/mL.
    Equivalence to microscopic analysisSubstantially equivalent to standard microscopic analysis (counting by Hemacytometer) based on WHO guidelines.
    Equivalence to other rapid testsSubstantially equivalent to K073039, SpermCheck® Vasectomy Test; K041039, Fertell Male Fertility Test; and K011679, FertilMARQ™ Home Diagnostic Screening Test.

    2. Sample size 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 or the data provenance (country of origin, retrospective/prospective).

    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)

    The document does not provide details on the number of experts or their qualifications used to establish ground truth for a test set. It mentions "standard microscopic analysis (counting by Hemacytometer) based on WHO guidelines" as a comparator, which implies expert analysis, but specifics are missing.

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

    The document does not provide details on any adjudication method used for a test set.

    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 section is not applicable as the device described is a qualitative home-use immunochromatographic test, not an AI-based system assisting human readers. It's a standalone diagnostic.

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

    Yes, a standalone performance was done. The SpermCheck® Fertility is an "immunochromatographic test for the rapid, qualitative detection of sperm concentration" intended for "over the counter home use." This inherently means it operates as a standalone device without a human-in-the-loop performance aspect beyond the user interpreting the visual result of the test. The primary comparative study mentioned is against "standard microscopic analysis (counting by Hemacytometer)."

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

    The ground truth for comparison appears to be the "standard microscopic analysis (counting by Hemacytometer) based on WHO guidelines." This implicitly relies on expert interpretation and established laboratory procedures, which can be considered a form of "expert consensus" or established "diagnostic standard."

    8. The sample size for the training set

    The document does not provide details on the sample size for a training set. As an immunochromatographic test, it's unlikely to have a "training set" in the machine learning sense. The development would involve analytical validation and clinical testing, but not a separate training phase for an algorithm.

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

    The document does not provide details on a training set or how its ground truth was established, as it's not an AI/machine learning device.

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