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510(k) Data Aggregation

    K Number
    K173323
    Date Cleared
    2018-03-08

    (139 days)

    Product Code
    Regulation Number
    878.4300
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K091987

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

    The AnastoClip GC is intended for use in the creation of everting anastomoses in blood vessels and other small tubular structures when tissue penetration is desired. The Applier is also intended for approximation of durotomies following open craniotomy and open spinal laminectomy procedures.

    Device Description

    AnastoClip GC Closure System is designed to create everting anastomoses of tissue. It includes the applier, clip remover, and atraumatic forceps. The AnastoClip GC applier consists of a rotating shaft and an integral cartridge containing titanium clips. As the levers of the applier are squeezed together, the clip is closed around the everted tissue edges. As the levers are released, a new clip is automatically loaded into the clip applier jaws. It is recommended, with each procedure, to use the atraumatic everting forceps to aid in the everting of the tissue edges. It is also recommended, with each procedure, to use the AnastoClip Remover for the removal of any AnastoClip GC clips when needed.

    AI/ML Overview

    The provided text describes the AnastoClip GC Closure System, a medical device. Based on the information presented, here's a breakdown of the acceptance criteria and the study that proves the device meets them:

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

    The document does not explicitly state quantitative "acceptance criteria" in a table format with corresponding "reported device performance" values for a specific study. Instead, it describes a preclinical study that aimed to demonstrate safety and substantial equivalence to a predicate device for an expanded indication. The "acceptance criteria" can be inferred from the successful outcomes of this study.

    Here's an inferred table based on the preclinical study's reported findings:

    Acceptance Criteria (Inferred from successful study outcomes)Reported Device Performance (AnastoClip GC)
    Absence of CSF leaks at cranial and spinal dural sitesNo CSF leaks observed at both cranial and spinal dural sites after application.
    No clinically significant changes in body weight, body condition score, or clinical pathology parametersNo clinically significant changes in body weight, body condition score, or clinical pathology parameters in any animal over the course of the study.
    Absence of adverse responses (inflammation, infection) in CSF samplesNo CSF sample exhibited any indication of adverse responses such as inflammation or infection.
    Absence of hydrocephalus or other abnormalities via CT scanNo signs of hydrocephalus or other abnormalities noted from the CT scan evaluations.
    Comparable histopathologic findings (minimal fibrosis, vascularization, hemorrhage, no necrosis, infection, or foreign body reaction) compared to predicateHistologic findings were comparable to the predicate device (AnastoClip AC), with minimal fibrosis and vascularization, minimal hemorrhage, and no implant-associated necrosis, infection or foreign body reaction.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Test Set Sample Size: 6 porcine models.
    • Data Provenance: The study was a "Pre-clinical GLP safety evaluation" performed in porcine models. The country of origin is not specified, but it's a prospective animal study.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    The document does not specify the number of experts or their qualifications for establishing ground truth. It states that a "comprehensive necropsy was performed" and "histomorphologic evaluation" of cranial and spinal implant sites was conducted. These evaluations would typically be done by veterinary pathologists, but their number and specific qualifications are not detailed.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    The document does not provide details on any adjudication method for the test set. It simply states that a "comprehensive necropsy" and "histomorphologic evaluation" were performed.

    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

    The document describes a preclinical animal study for a medical device (surgical clip system), not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance was not performed and is not applicable.

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

    This question is not applicable as the device is a physical surgical closure system, not an algorithm or AI system.

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

    The ground truth for the preclinical study was established through a combination of:

    • Direct observation: Absence of CSF leaks.
    • Clinical observation: Body weight, body condition score, clinical pathology parameters in animals.
    • Laboratory analysis: CSF sample analysis (for inflammation/infection).
    • Imaging: CT scan evaluations (for hydrocephalus/abnormalities).
    • Pathology/Histomorphology: Microscopic evaluation of cranial and spinal implant sites.

    8. The sample size for the training set

    This question is not applicable as the device is a physical medical device and does not involve AI or machine learning that requires a training set.

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

    This question is not applicable as the device is a physical medical device and does not involve AI or machine learning that requires a training set.

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