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510(k) Data Aggregation

    K Number
    K243860
    Manufacturer
    Date Cleared
    2025-01-15

    (30 days)

    Product Code
    Regulation Number
    878.4300
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The AtriClip LAA Exclusion System is indicated for the exclusion of the heart's left atrial appendage, performed under direct visualization and in conjunction with other cardiac surgical procedures.

    Direct visualization, in this context, requires that the surgeon is able to see the heart directly, with or without assistance from a camera, endoscope, etc., or other appropriate viewing technologies.

    Device Description

    The AtriClip PRO-Mini LAA Exclusion System consists of a single use, sterile, self-closing, implantable Clip (AtriClip Mini) preloaded on a Single Use Clip Applier along with a Selection Guide. When closed, the Clip applies uniform pressure over the length of the Clip to ensure consistent, reproducible, and secure exclusion of the left atrial appendage (LAA). The Clip is then deployed and is left as a permanent implant, and excludes the LAA, resulting in electrical isolation of the LAA. The Clip is available in the following lengths to accommodate different sizes of LAA: 35 mm, 40 mm, 45 mm, and 50 mm. The PRO-Mini device is a disposable device with a handle, leftright and up/down articulation knobs, articulation lock, deployment tab, shaft, suture anchors, and end effector containing the AtriClip Mini.

    AI/ML Overview

    This document outlines the FDA's clearance for the AtriClip PRO-Mini LAA Exclusion System (PROM) based on its substantial equivalence to previously cleared predicate devices. The information provided primarily focuses on the device's technical characteristics and the non-clinical bench testing performed to demonstrate this equivalence. It does not describe a study involving algorithms, AI, human readers, or clinical performance metrics that would typically have acceptance criteria like sensitivity, specificity, or AUC when evaluating diagnostic or prognostic devices.

    Therefore, many of the requested sections (2-6, 8-9) are not applicable or cannot be extracted from this document as they pertain to clinical or AI/algorithm-based studies, which are not described here.

    Here's the information that can be extracted or inferred from the provided text, focusing on the device's substantial equivalence through bench testing:

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

    Based on the provided text, the acceptance criteria are generalized as demonstrating "equivalence in performance" and not raising "any new issues of safety." The reported performance is that the device "met the predetermined acceptance criteria." Specific quantitative acceptance criteria are not detailed in this document, nor are specific quantitative performance results.

    Acceptance Criteria (General)Reported Device Performance
    Demonstrated equivalency in performanceMet predetermined acceptance criteria
    Did not raise any new issues of safetyNo new safety or performance issues were raised during testing
    Fundamental design is substantially equivalentDemonstrated substantial equivalence
    Technology is substantially equivalentDemonstrated substantial equivalence
    Function is substantially equivalentDemonstrated substantial equivalence
    Device materials are substantially equivalentDemonstrated substantial equivalence
    Packaging is substantially equivalentDemonstrated substantial equivalence
    Sterilization is substantially equivalentDemonstrated substantial equivalence
    Operating principle is substantially equivalentDemonstrated substantial equivalence
    Intended use / indication for use is equivalentDemonstrated substantial equivalence

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

    This information is not provided in the document. The document refers to "bench testing," which implies laboratory-based tests rather than patient data.

    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)

    This information is not provided as the study is non-clinical bench testing, not a study requiring expert clinical interpretation for ground truth establishment.

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

    This information is not provided as the study is non-clinical bench testing, and adjudication methods are typically used for expert clinical review of cases.

    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

    No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done and is not described in this document. This document pertains to the clearance of a physical medical device (implantable clip system) based on non-clinical bench testing, not an AI or imaging device involving human readers.

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

    Not Applicable. This document describes a physical medical device, not an algorithm or AI system.

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

    For the non-clinical bench testing, "ground truth" would likely be established by engineering specifications, material standards, and validated testing methodologies to measure mechanical properties, reliability, and tissue interaction. The document doesn't explicitly state the methodology for establishing this "ground truth" for each bench test, but it is implied by the nature of such testing.

    8. The sample size for the training set

    Not Applicable. This document describes the clearance of a physical medical device based on non-clinical bench testing, not an AI or algorithm-based device that would require a training set.

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

    Not Applicable. As no training set is described or implied, the establishment of its ground truth is not relevant.

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