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510(k) Data Aggregation

    K Number
    K241621
    Manufacturer
    Date Cleared
    2024-08-02

    (58 days)

    Product Code
    Regulation Number
    878.4400
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K223039, K231212

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

    The Da Vinci Monopolar and Bipolar Adapters are intended for connecting monopolar or bipolar electrosurgical instruments to an electrosurgical generator to provide transmission of high frequency energy from the electrosurgical generator to the surgical instrument.

    Device Description

    The Da Vinci Monopolar and Bipolar Adapters are an accessory for the Da Vinci E-200 Electrosurgical Generator (K223039, K231212). The Da Vinci Monopolar and Bipolar Adapters (referred to herein as "Adapters") are non-sterile. They are designed to enable the use of certain, third-party electrosurgical instruments with specific monopolar and bipolar plug formats (refer to with the E-200 Electrosurgical Generator). This enables the transmission of high-frequency energy from the electrosurgical generator to the surgical instrument.

    AI/ML Overview

    The provided text is a 510(k) summary for the Da Vinci Monopolar and Bipolar Adapters. It describes the device, its intended use, and the studies conducted to demonstrate its substantial equivalence to a predicate device. However, it does not contain the specific details required to answer all parts of your request regarding the acceptance criteria and the study proving the device meets those criteria for an AI/ML-based medical device.

    The Da Vinci Monopolar and Bipolar Adapters are described as an accessory for an electrosurgical generator, designed to connect instruments to the generator for transmission of high-frequency energy. This is a hardware device, not an AI/ML software device for diagnostic or prognostic purposes. Therefore, the types of studies and acceptance criteria you've outlined (e.g., MRMC studies, ground truth establishment, training sets, AI assistance metrics) are not applicable to this device.

    The performance data mentioned are typical for hardware accessories:

    • Design Verification (Bench Testing): Covered hardware requirements, reliability, EMC and Electrical Safety, and Packaging and Labeling.
    • Design Validation: Simulated clinical use with a cadaver model.
    • Human Factor Evaluation: Assessed safety and effectiveness for intended users and use environments.
    • Transit Testing: Evaluated packaging.

    Since your request is tailored for an AI/ML medical device, and the provided document is for a hardware accessory, I cannot extract the information you're asking for directly from this text. The acceptance criteria for this device would be based on the successful completion of the described engineering and usability tests, demonstrating functional performance, electrical safety, and mechanical integrity, rather than diagnostic accuracy or reader improvement metrics.

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