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510(k) Data Aggregation

    K Number
    K952244
    Date Cleared
    1996-08-05

    (451 days)

    Product Code
    Regulation Number
    880.2800
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Sterilier CROSS-CHECKS EO gas process indicator monitoring strips are a yellow to brown chemical indicator strip that changes color during Ethylenc Oxide (EO) processing. They indicate that the item has been processed in Ethylene Oxide.

    Device Description

    SteriTec CROSS-CHECKS EO process indicators are a pale yellow to brown chemical indicator strip that changes color during ethylene oxide processing.

    AI/ML Overview

    The provided text describes a 510(k) application for a chemical process indicator and includes limited information about performance criteria and study details. Based on the available text, here's an attempt to answer the questions, highlighting what is present and what is missing.

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

    Acceptance Criteria (Implied)Reported Device Performance
    Changes color during ethylene oxide processing."a pale yellow to brown chemical indicator strip that changes color during ethylene oxide processing."
    Indicates that the item has been processed in Ethylene Oxide."They indicate that the item has been processed in Ethylene Oxide."
    Performs safely and effectively."performed in a safe and effective manner"
    Equivalent to the predicate device (Surgicot 20 EO Gas Indicator)."performed...equivalently to the Surgicot 20 predicate device."

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

    • Sample Size for Test Set: Not specified. The document states "Laboratory tests were performed" but does not give a number of indicators tested.
    • Data Provenance: Not explicitly stated, but the tests were performed by "an independent testing laboratory." The location of this laboratory and whether the data is retrospective or prospective is not mentioned.

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

    This information is not provided. For a chemical indicator, ground truth would likely be established by exposure to EO gas under controlled conditions, not by expert interpretation.

    4. Adjudication method for the test set

    Not applicable/Not specified. Given the nature of a chemical indicator, "adjudication" in the sense of human interpretation of complex outputs is not relevant. The "ground truth" for whether the indicator changed color would be directly observable.

    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

    Not applicable. This device is a chemical process indicator, not an AI-assisted diagnostic tool for human readers. Therefore, an MRMC study and AI assistance are not relevant.

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

    This concept is not directly applicable. The device itself is a "standalone" chemical indicator that changes color. There is no algorithm or human-in-the-loop interaction described beyond the observation of the color change. The "laboratory tests" inherently represent the standalone performance of the indicator.

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

    The ground truth for this type of device would be whether the indicator was actually exposed to ethylene oxide gas under conditions that should trigger a color change, and conversely, whether it remained unchanged when not exposed. This would be established by controlled laboratory exposure to EO (or lack thereof) rather than expert consensus or pathology.

    8. The sample size for the training set

    Not applicable. Chemical process indicators typically do not involve "training sets" in the machine learning sense. Their performance is based on chemical reactions.

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

    Not applicable (see point 8).

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