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510(k) Data Aggregation

    K Number
    K232341
    Date Cleared
    2023-10-10

    (67 days)

    Product Code
    Regulation Number
    888.3070
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K181119, K173487, K0822236, K010515, K130291, K133350

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

    The CarboClear® Pedicle Screw System is intended to provide rigid immobilization of lumbar and/or sacral segments as an adjunct to fusion in patients with degenerative disc disease (DDD) at one level from L2 to S1, with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. Patients should be skeletally mature and have at least six months of non-operative treatment. The CarboClear® Pedicle Screw System is intended to be used with an intervertebral body fusion device implanted at the same spinal level with autogenous and/ or allogenic bone graft comprised of cancellous and/or corticocancellous bone graff.

    Device Description

    The CarboClear® Pedicle Screw System is composed of implants in various dimensions, used to build a spinal construct; and of a set of instruments, intended to assist in the insertion and placement of the implants. The CarboClear® implants include pedicle screws, rods and locking elements. The implants are made of carbon fiber-reinforced polyetheretherketone (CFR-PEEK). The threaded portion of the pedicle screws is encased within a thin titanium shell. The implants include tantalum markers. The implants are supplied sterile, and are intended for single use.

    AI/ML Overview

    The provided text describes the CarboClear® Pedicle Screw System, a medical device for spinal stabilization, and its 510(k) submission to the FDA. The submission focuses on demonstrating substantial equivalence to existing predicate devices rather than proving the device meets specific acceptance criteria through a standalone study with a defined test set, ground truth, and expert adjudication as might be seen for AI/ML devices. Therefore, much of the requested information regarding acceptance criteria and study methodology for proving device performance through such studies is not available in this document.

    However, based on the provided text, here's what can be extracted regarding performance and substantiation:

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

    The document does not explicitly state quantitative acceptance criteria for device performance in a table format. Instead, it relies on demonstrating substantial equivalence to predicate devices through various tests.

    Acceptance Criteria (Implied by Substantial Equivalence to Predicates)Reported Device Performance
    Mechanical performance comparable to predicate devices in static and dynamic tests.Performance testing (per ASTM F1717, F1798, F2193, F543, fatigue lateral bending-axial rotation, rod creep tests): "The test results were found to be comparable to those of predicate devices, as applicable, demonstrating substantially equivalent mechanical performance of the subject system."
    Clinical performance comparable to predicate devices for the specified indications for use.Clinical data: "Clinical data for the CarboClear® Pedicle Screw System was presented for the target population specified in the indications for use statement, and supports the substantially equivalent performance of the subject system."

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

    The document does not specify a "test set" in the context of an AI/ML algorithm evaluation. Instead, it refers to "Performance data" and "Clinical data."

    • Performance Data (Mechanical Testing): The sample size for mechanical tests (e.g., number of screws, rods tested) is not provided. The data provenance is laboratory testing conducted according to ASTM standards. Country of origin not specified, but the applicant is based in Israel.
    • Clinical Data: The sample size for clinical data (e.g., number of patients) is not provided. The provenance (country of origin, retrospective/prospective) is also not specified.

    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 applicable to the type of submission described. The document does not describe a study involving expert-established ground truth for a test set, as would be relevant for an AI/ML device.

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

    This information is not applicable. There is no mention of an adjudication method as it relates to expert review of a test set.

    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

    A multi-reader multi-case (MRMC) comparative effectiveness study is not mentioned. The device is a physical pedicle screw system, not an AI/ML-driven diagnostic or assistive tool for human readers.

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

    This information is not applicable. The device is a physical implant, not an algorithm.

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

    For the mechanical performance, the "ground truth" is established by adherence to recognized ASTM standards and comparison to predicate device performance. For clinical performance, the "ground truth" would likely be patient outcomes, but the specific type of clinical ground truth (e.g., imaging follow-up, functional scores, fusion rates) is not detailed.

    8. The sample size for the training set

    This information is not applicable. The device is not an AI/ML model that requires a training set.

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

    This information is not applicable. The device is not an AI/ML model that requires a training set with established ground truth.

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    K Number
    K180433
    Device Name
    ENNOVATE®
    Date Cleared
    2018-04-26

    (65 days)

    Product Code
    Regulation Number
    888.3070
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K130291, K062085, K071945

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

    The ENNOVATE Spinal System is intended for anterior/anterolateral and posterior, non-cervical pedicle and non-pedicle fixation. Fixation is limited to skeletally mature patients and is intended to be used as an adjunct to fusion using autograff or allograft. The ENNOVATE System can be used in both an Open and Minimally Invasive Surgery (MIS). The device is indicated for treatment of the following acute and chronic instabilities or deformities.

    1. Degenerative disc disease (defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies).
    2. Spondylolisthesis,
    3. Trauma (i.e., fracture or dislocation)
    4. Spinal Stenosis.
    5. Deformities or Curvatures (i.e., scoliosis, kyphosis, and/or lordosis),
    6. Tumor.
    7. Pseudoarthrosis, and
    8. Failed previous fusion
    Device Description

    The ENNOVATE Spinal System is an implant system used to correct spinal deformity and facilitate the biological process of spinal fusion. This system is intended for posterior use in the thoracic, lumbar and sacral areas of the spine. This submission includes modified polyaxial screws, additional multiaxial-cross-connectors, offset connectors and additional components in sterile version. All implant components are top loading and top tightening. The implants in this system are manufactured from titanium alloy (Ti-6Al-4V), conforming to ISO 5832-3.
    The ENNOVATE Spinal System is a spinal rod and screw system. This system's polyaxial screws can be locked into a wide range of configurations, therefore allowing each construct to be formed to the needs of an individual patient. Rods of this system are shaped intraoperatively to correct or maintain proper spinal curvature.

    AI/ML Overview

    This document is a 510(k) premarket notification for a medical device (ENNOVATE® Spinal System) and as such, it describes the equivalence of the device to existing predicate devices, rather than establishing acceptance criteria and proving the device meets them through a performance study against a defined ground truth.

    Therefore, the requested information regarding acceptance criteria, device performance, sample sizes for test and training sets, expert consensus, adjudication methods, MRMC studies, and standalone algorithm performance, is not present in this document.

    The document focuses on demonstrating substantial equivalence through:

    • Indications for Use: Listing the conditions the device is intended to treat, which are the same as the predicate devices.
    • Technological Characteristics: Stating that the components, materials (titanium alloy, medical grade silicone, stainless steel, titanium alloy, PEEK), and configurations are similar to predicate and reference devices.
    • Performance Data: Citing various ASTM standards (F1717-15, F2193-14, F1798-13, F543-13/17) for mechanical testing (dynamic/static compression, torsion, flexion bending, pull-out strength, driving torque). These tests confirm the physical properties and mechanical performance are comparable to the predicate, not that the device meets clinical acceptance criteria.

    In summary, this document does not contain the information required to populate the requested table or answer the specific questions about clinical performance studies, AI algorithms, or human-in-the-loop improvements, because it is a 510(k) submission focused on substantial equivalence, not a clinical trial report proving a device meets specific clinical performance acceptance criteria.

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