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510(k) Data Aggregation

    K Number
    K160041
    Manufacturer
    Date Cleared
    2016-03-07

    (59 days)

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

    Cobbra RF Tissue Dissector

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

    The Cobbra RF Tissue Dissector is intended for use by a physician familiar with resection, incision, and hemostasis in soft tissue surgical procedures. The types of surgery intended are: General surgery, Laparoscopic procedures, Endoscopic procedures, Open abdominal, Orthopedic coagulation, Thorascopic coagulation, Neurosurgical coagulation Gynecological coagulation, (except for use in female sterilization), Ear, Nose, Throat coagulation.

    Device Description

    The Cobbra™ RF Tissue Dissector is a single-use, sterile, monopolar electrosurgical instrument intended for use exclusively with the elliquence Surgi-Max® Plus radiofrequency generator (510(k) K100390). The basic design of the device is a plastic handpiece, a partially-insulated electrode with an uninsulated, active edge, and a cable and plug. The electrical power operating at radio frequency (RF) is transferred to tissue at the surgical site via the active edge of the Cobbra™ RF Tissue Dissector's electrode. The time-varying voltage produced by RF electrical power source yields a predetermined electrosurgical effect, such as tissue cutting or coagulation.

    The Cobbra™ RF Tissue Dissector is classified as a sterile, surgically-invasive, active device with an intended patient contact period of

    AI/ML Overview

    The provided document does not contain information regarding detailed acceptance criteria, the specific study that proves the device meets those criteria, or the detailed aspects of a study typically associated with AI/ML-driven devices. This document is a 510(k) premarket notification for a medical device called the "Cobbra RF Tissue Dissector," which is an electrosurgical cutting and coagulation device.

    The document focuses on demonstrating substantial equivalence to predicate devices based on:

    • Intended use
    • Technology/principle of operation
    • Materials
    • Performance (through non-clinical bench testing)

    Here's a breakdown of what is available in the document related to performance and testing, and what is not:

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document mentions "Various performance tests including mechanical testing, thermal damage measurements, and simulated use tests" were conducted. However, it does not provide a table with specific acceptance criteria (e.g., maximum allowed thermal damage, specific mechanical strength thresholds) or the reported device performance against these criteria.

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

    This information is not provided. The testing described is "non-clinical bench testing," which typically involves laboratory conditions rather than human data. There is no mention of "test sets" in the context of patient data, nor country of origin or retrospective/prospective nature.

    3. Number of Experts Used to Establish Ground Truth and Qualifications:

    This information is not applicable and therefore not provided. The device is not an AI/ML diagnostic tool that relies on expert interpretation for ground truth.

    4. Adjudication Method:

    This information is not applicable and therefore not provided.

    5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study:

    No MRMC study was conducted or reported. The device is an electrosurgical tool, and its effectiveness is not assessed through comparative human reader studies.

    6. Standalone (Algorithm only) Performance:

    This is not applicable as the device is a physical electrosurgical instrument, not a software algorithm.

    7. Type of Ground Truth Used:

    The concept of "ground truth" as typically used in AI/ML validation (e.g., pathology, outcomes data) is not applicable here. The performance is assessed through engineering and biological safety tests. For instance, "thermal damage measurements" would have a physical ground truth related to tissue effects.

    8. Sample Size for the Training Set:

    This is not applicable as the device is not an AI/ML algorithm that is trained on a dataset.

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

    This is not applicable.


    Summary of available information related to performance and testing:

    • Acceptance Criteria & Reported Performance: Not explicitly detailed in a table. The document states that "Various performance tests including mechanical testing, thermal damage measurements, and simulated use tests" were performed, along with biocompatibility, electrical safety, EMC, shelf-life, and sterility testing. These tests implicitly have acceptance criteria (e.g., passing results for biocompatibility, meeting electrical safety standards), but the specifics are not enumerated.
    • Study Type: Non-clinical bench testing.
    • Clinical Testing: The document explicitly states: "This premarket submission did not rely on the assessment of clinical performance data to demonstrate substantial equivalence."
    • Testing Categories:
      • Mechanical testing
      • Thermal damage measurements
      • Simulated use tests
      • Biocompatibility (in accordance with ISO 10993-1)
      • Electrical safety and electromagnetic compatibility (in accordance with IEC 60601-1, IEC 60601-1-2, and IEC 60601-2-2)
      • Shelf-life determination
      • Sterility validation

    The document establishes that the device is "as safe and effective as the predicate devices" based on these non-clinical tests and comparisons of intended use, technological characteristics, and materials.

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