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510(k) Data Aggregation

    K Number
    K022305
    Date Cleared
    2002-08-08

    (23 days)

    Product Code
    Regulation Number
    880.6250
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MULTIPLE LABELS, POWDER-FREE POLY-VINYL EXAM GLOVES, COLOR: WHITE

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    A patient examination glove is a disposable device intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner.

    Device Description

    POWDER-FREE POLY VINYL EXAM GLOVES, COLOR: WHITE

    AI/ML Overview

    The document describes the acceptance criteria and the study for "POWDER-FREE POLY VINYL EXAM GLOVES, COLOR: WHITE."

    Here's the breakdown of the requested information:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Standard/Test)Reported Device Performance
    ASTM D 5250-00Met or exceeded
    ASTM D 5151-00Met or exceeded
    ASTM D 6124-00Met or exceeded
    ISO 2859Met or exceeded
    Bio BurdenMet or exceeded
    Bio-Compatibility: Dermal SensitizationMet or exceeded
    Bio-Compatibility: Primary Skin IrritationMet or exceeded

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

    The document does not explicitly state the sample sizes used for the specific tests (ASTM D 5250-00, D 5151-00, D 6124-00, ISO 2859, Bio Burden, Dermal Sensitization, Primary Skin Irritation). The data provenance is implied to be from tests performed on the device by Heyuan Hongli Industries, Inc., which is based in China. The submission date is July 11, 2002, suggesting these were retrospective tests conducted on the manufactured gloves.

    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 tests performed are standardized and do not typically involve human experts establishing a "ground truth" in the way a diagnostic AI device would. Instead, these are material and biological safety tests with predefined methodologies and pass/fail criteria.

    4. Adjudication Method for the Test Set

    This information is not applicable as the tests are standardized and have objective pass/fail criteria. There isn't an adjudication process involving multiple human reviewers to determine a "ground truth" for these types of tests.

    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

    An MRMC comparative effectiveness study was not done. This device is a medical glove, not an AI-powered diagnostic tool. Therefore, the concept of human readers improving with or without AI assistance is not relevant to this device.

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

    This is not applicable. The device is a physical product (medical glove), not an algorithm or AI.

    7. The Type of Ground Truth Used

    The "ground truth" for this device's performance is established by objective measurements and assessments based on the specified ASTM and ISO standards, as well as bio-compatibility tests. These standards define the acceptable physical properties (e.g., strength, dimensions), absence of holes, and biological safety (e.g., absence of skin irritation, allowable bioburden). There is no "expert consensus," "pathology," or "outcomes data" ground truth in the context of this device's testing.

    8. The Sample Size for the Training Set

    This information is not applicable. The device is a physical product and does not involve a training set as a machine learning model would. Production quality control would involve sampling from manufacturing batches, but this is distinct from "training data."

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

    This information is not applicable as there is no "training set" for a medical glove in the context of AI/algorithm development.

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