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510(k) Data Aggregation

    K Number
    K984512
    Manufacturer
    Date Cleared
    1999-07-12

    (206 days)

    Product Code
    Regulation Number
    878.4460
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    This sterile nitrile powder free surgeon's glove is intended to be worn by operating room personnel to protect a surgical wound from contamination.

    Device Description

    Nitrilon™ Correct Touch® Sterile Nitrile Powder Free Surgeon's Glove

    AI/ML Overview

    This is an FDA 510(k) clearance letter for sterile nitrile powder-free surgical gloves. It does not contain the detailed information required to answer your questions about acceptance criteria, study design, expert qualifications, or ground truth for a medical device. This type of document confirms that a device is "substantially equivalent" to a previously marketed device, without necessarily detailing specific performance studies in the way you've outlined.

    Therefore, I cannot provide the requested information from the provided text.

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    K Number
    K981304
    Manufacturer
    Date Cleared
    1998-06-22

    (73 days)

    Product Code
    Regulation Number
    880.6250
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    A medical giove is worn on the hand of health care and similar personnel to prevent contamination between health care personnel and the patient.

    Device Description

    NITRILON CORRECT-TOUCH POWDERED NITRILE Examination Glove

    AI/ML Overview

    Here's an analysis of the provided text regarding acceptance criteria and study details for the Nitrilon™ Correct-Touch® Powdered Nitrile Examination Gloves:

    Important Note: The provided document is a 510(k) clearance letter from the FDA for medical gloves. This type of document declares substantial equivalence to a previously marketed device, rather than providing a detailed study report with specific performance metrics and acceptance criteria as would be found for a novel AI device or a more complex medical device requiring clinical trial data.

    Therefore, many of the requested sections (e.g., sample size for training/test sets, expert qualifications, MRMC studies, standalone algorithm performance) are not applicable or not explicitly detailed in this document, as the regulatory pathway for examination gloves relies on demonstrating equivalence rather than establishing de novo performance characteristics through such studies.

    However, I will extract what can be inferred or stated as "not applicable" based on the provided text.


    1. Table of Acceptance Criteria and Reported Device Performance

    For examination gloves, the "acceptance criteria" are generally based on recognized standards for physical properties and biocompatibility to ensure they are safe and effective for their intended use and equivalent to existing predicate devices. The document does not explicitly list a table of acceptance criteria or performance metrics specific to the Nitrilon™ Correct-Touch® gloves. Instead, the FDA's clearance implies that the device meets the general controls and equivalence requirements.

    Therefore, for this document, a direct table of acceptance criteria and reported performance cannot be generated. The "performance" being assessed here is predominantly the device's substantial equivalence to a predicate device in terms of materials, intended use, and manufacturing processes, rather than a quantifiable performance metric like sensitivity or specificity.

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

    Not applicable. This document does not describe a "test set" in the context of evaluating an AI algorithm's performance. The review is for a physical medical device (gloves) and relies on substantial equivalence.

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

    Not applicable. "Ground truth" in the context of AI algorithm evaluation is irrelevant here. The FDA's review involves regulatory experts, but they are assessing compliance and equivalence, not establishing a "ground truth" for a dataset.

    4. Adjudication Method for the Test Set

    Not applicable. There is no "test set" in the context of AI algorithm evaluation described.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

    Not applicable. MRMC studies are used for evaluating the impact of AI on human reader performance, typically in diagnostic imaging. This document pertains to examination gloves.

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

    Not applicable. This device is not an algorithm.

    7. The Type of Ground Truth Used

    Not applicable. "Ground truth" is a concept for evaluating algorithms. For medical gloves, the "truth" is established by adherence to recognized standards for materials, manufacturing, and performance (e.g., tensile strength, barrier integrity, biocompatibility), which are demonstrated through testing that is not detailed in this FDA clearance letter.

    8. The Sample Size for the Training Set

    Not applicable. This document is not about an AI algorithm, so there is no training set.

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

    Not applicable. There is no training set mentioned in this document.


    Summary based on the provided document:

    The provided FDA 510(k) clearance letter for Nitrilon™ Correct-Touch® Powdered Nitrile Examination Gloves is for a physical medical device, not an AI algorithm. The regulatory pathway for such devices focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than on proving performance through studies typically associated with AI or novel diagnostic/therapeutic devices (e.g., clinical trials, AI performance metrics, expert adjudication). Therefore, most of the requested information regarding acceptance criteria, study design parameters (sample sizes, experts, ground truth, MRMC studies, standalone performance) is not available or applicable in this specific regulatory document. The FDA's letter confirms that the device meets the general controls provisions of the Federal Food, Drug, and Cosmetic Act and is substantially equivalent to a predicate device.

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    K Number
    K981333
    Manufacturer
    Date Cleared
    1998-06-22

    (70 days)

    Product Code
    Regulation Number
    880.6250
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    A medical glove is worn on the hand of A medical grow similar personnel to prevent contamination between health care personnel and the patient.

    Device Description

    Nitrilon™ Correct-Touch® Nitrile Powder-Trade Name: Free Examination Gloves

    AI/ML Overview

    The provided document is a 510(k) clearance letter from the FDA for a Nitrile Powder-Free Examination Glove. It is not a study report or a technical document detailing acceptance criteria and device performance. Therefore, I cannot extract the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, or ground truth.

    The letter confirms that the device is substantially equivalent to legally marketed predicate devices for its stated indications for use: "A medical glove is worn on the hand of medical or similar personnel to prevent contamination between health care personnel and the patient."

    The document does not contain any of the specific information requested in your prompt regarding:

    1. A table of acceptance criteria and reported device performance.
    2. Sample sizes or data provenance for a test set.
    3. Number or qualifications of experts for ground truth.
    4. Adjudication method.
    5. MRMC comparative effectiveness study results.
    6. Standalone algorithm performance.
    7. Type of ground truth used.
    8. Training set sample size.
    9. How training set ground truth was established.
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