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510(k) Data Aggregation

    K Number
    K152691
    Date Cleared
    2016-02-25

    (157 days)

    Product Code
    Regulation Number
    872.3275
    Panel
    Dental
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    EDS Universal Cement

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use
    • Final cementation of ceramic, composite, or metal inlays, onlays, crowns, bridges, posts, and screws.
    • Final cementation of ceramic, composite, or metal restorations on implant abutments.
    • Permament cementation of ceramic or composite veneers.
    Device Description

    EDS Universal Cement is an automix, dual-curing, self-adhesive resin cement. This multi-purpose device can be used to affix a variety of ceramic, composite, or metal restorations without the aid of an etchant or bonding agent. The device is comprised of two pastes (base and catalyst) that contain dimethacrylate resins, inorqanic filler particles (60% by wt), and a photoinitiator system. The mixing ratio is roughly 1 part base to 1 part catalyst. The device is packaged in a 5 mL dualbarreled syringe and comes in three shades: translucent (white), opaque (white), and A2 (tooth colored). EDS Universal Cement provides a bond between tooth surfaces (dentin and enamel) and ceramic, composite, and metal restorations. The device provides radiopacity and is resistant to mechanical stress and water damage. EDS Universal Cement is provided non-sterile and has a shelf-life of two years.

    AI/ML Overview

    The provided document is a 510(k) premarket notification for a dental cement (EDS Universal Cement). It does not describe an AI/ML powered device, nor does it contain information about acceptance criteria or a study proving the device meets said criteria in the context of AI/ML performance metrics.

    However, based on the document, I can extract information related to product testing and equivalence to predicate devices, which serves a similar purpose to acceptance criteria and studies in regulatory submissions for traditional medical devices.

    Here's an interpretation of the request using the available information for a non-AI/ML device:

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

    The document does not explicitly state "acceptance criteria" with numerical thresholds for performance. Instead, it relies on demonstrating equivalence to a legally marketed predicate device (Unicem HM). The performance is reported through a series of tests against this predicate.

    Test CategoryAcceptance Criteria (Implied by equivalence)Reported Device Performance (EDS Universal Cement)
    BiocompatibilityEquivalent to predicate (Unicem HM) in terms of safety. Confirmed by ISO standards.Passed Cytotoxicity (ISO 10993-5), Sensitization (ISO 10993-10), Implantation (ISO 10993-6), and Genotoxicity (ISO 10993-3) testing, demonstrating safety equivalence.
    Physical Properties / AdhesionEquivalent to predicate (Unicem HM) in performance, particularly comparative shear bond strength to various dental surfaces.Demonstrated performance equivalence to Unicem HM through comparative shear bond strength testing on dentin, enamel, zirconia, and lithium disilicate surfaces. (Specific numerical values/statistical comparison are not provided in this summary but were likely in the full submission).
    Fluoride Release(Not explicitly compared to predicate, but assessed as a characteristic)No fluoride was released over a 7-day period when immersed in distilled water.

    2. Sample size used for the test set and the data provenance

    The document does not specify the exact sample sizes for the individual tests (e.g., number of samples for shear bond strength, number of animals for in vivo tests). It generally refers to "samples of the subject and predicate devices."

    The data provenance is not explicitly stated in terms of country of origin. The study types (biocompatibility, physical properties, adhesion) are all non-clinical in vitro or in vivo (animal) studies, not human clinical studies. Therefore, it is retrospective if the tests were performed on pre-existing batches or prospective if the tests were designed specifically for this submission. The summary does not provide this detail.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This concept is not applicable here as these are laboratory-based non-clinical tests for a dental cement, not diagnostic or AI performance evaluation studies requiring expert ground truth. The "ground truth" for these tests would be the established scientific methods and measurements.

    4. Adjudication method for the test set

    Not applicable for non-clinical laboratory tests. The results are typically objectively measured according to standardized protocols (e.g., ISO standards for biocompatibility, universal testing machine for shear bond strength).

    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

    Not applicable. This is a dental cement, not an AI-powered diagnostic device.

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

    Not applicable. This is a dental cement, not an AI-powered device.

    7. The type of ground truth used

    For biocompatibility tests, the ground truth is established by ISO (International Organization for Standardization) standards (e.g., ISO 10993 series), which define acceptable biological responses.

    For physical properties and adhesion tests, the "ground truth" is measured physical and material properties derived from standardized laboratory testing methods (e.g., shear bond strength in MPa). The comparison is against the predicate device's performance under similar testing conditions.

    8. The sample size for the training set

    Not applicable. This is a traditional medical device, not an AI/ML system requiring a training set.

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

    Not applicable. This is a traditional medical device, not an AI/ML system.

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