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510(k) Data Aggregation

    K Number
    K961911
    Date Cleared
    1996-06-28

    (42 days)

    Product Code
    Regulation Number
    862.1155
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The DSL I-hCG ELISA assay is intended for the quantitative determination of I-hCG in human serum. It is intended for in vitro diagnostic use by professional laboratory personnel as an aid in the detection of pregnancy.

    Device Description

    The ELISA format is a non-competitive assay in which the analyte to be measured is "sandwiched" between two antibodies. The first antibody is immobilized to the inside wall of the microtitration well, the other antibody is conjugated to the enzyme horseradish peroxidase for detection. The analyte present is bound by both the antibodies to form a "sandwiched" complex. Unbound materials are removed by washing the wells. The resultant is analyzed in a spectrophotometer for absorbance. The amount of bound hCG is directly proportional to the concentration of the hCG present in the sample.

    AI/ML Overview

    Here's an analysis of the provided text based on your request, focusing on the acceptance criteria and study details for the DSL 10-8300 I-hCG ELISA Kit:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance CriteriaReported Device Performance
    Substantial Equivalence to DSL I-hCG IRMALinear regression analysis of patient sample comparison: Y = 0.92(X) + 16.5
    Correlation coefficient (r) = 0.98

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

    • Sample Size for Test Set: 54 patient samples.
    • Data Provenance: Not explicitly stated, but the context implies these are real human serum samples. There is no information on the country of origin or whether the data was retrospective or prospective. "Samples were chosen based on expected hCG levels so that samples with low, intermediate and high levels would be evaluated," which suggests a deliberate selection akin to a prospective design for comparison, but the origin details are missing.

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

    This information is not provided in the document. The "ground truth" for the comparison study appears to be the results generated by the predicate device, the DSL I-hCG IRMA, rather than an independent expert assessment.

    4. Adjudication Method for the Test Set

    This information is not applicable/not provided. The study design is a comparison of two assays' numerical outputs (quantitative measurements), not a diagnostic interpretation that would typically require adjudication. The DSL I-hCG IRMA served as the reference for comparison.

    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 not applicable. The device is an ELISA kit for quantitative measurement of hCG in human serum, not an AI-powered diagnostic system that assists human readers. Therefore, an MRMC study and effects on human reader performance are outside the scope of this device.

    6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

    This is not applicable. This is an immunoassay kit, not an algorithm. The device itself performs the quantitative measurement.

    7. The Type of Ground Truth Used

    The "ground truth" for the comparative performance study was the results obtained from the DSL I-hCG IRMA, which is the predicate device. This is a form of reference standard comparison against an established method.

    8. The Sample Size for the Training Set

    This information is not provided and is likely not relevant in the context of an immunoassay kit. Immunoassay kits are developed and validated through a series of analytical studies (e.g., precision, accuracy, linearity, interferences) and then clinical comparison studies. They do not typically involve "training sets" in the same way machine learning algorithms do.

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

    This information is not provided/not applicable for the reasons stated above (it's an immunoassay, not an AI algorithm).

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