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510(k) Data Aggregation

    K Number
    K071688
    Device Name
    RELIANCE S.E.P.
    Date Cleared
    2007-09-07

    (79 days)

    Product Code
    Regulation Number
    872.3200
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Reliance S.E.P. is a one step self etching primer intended to be used for the preparation of a tooth surface prior to bonding an orthodontic appliance(s) with a light cure adhesive.

    Device Description

    The Reliance S.E.P. is a one step self etching primer contained in a handheld dispenser. Upon manual compression into a light impervious mixing well, enough solution is dispensed to prepare the enamel surface of up to 20 teeth.

    AI/ML Overview

    The provided document describes the Reliance S.E.P. (Self Etching Primer) and its substantial equivalence to a predicate device, 3M Unitek Transbond Plus Self Etching Primer. The primary study conducted to demonstrate this equivalence is a "Shear bond strength testing comparison."

    Here's a breakdown of the requested information based on the provided text:

    Acceptance Criteria and Reported Device Performance

    Acceptance CriteriaReported Device Performance
    Equivalence in Effectiveness (Shear Bond Strength)The Reliance S.E.P. demonstrates equivalence to the legally marketed predicate device (3M Unitek Transbond™ Plus Self Etching Primer) in terms of effectiveness, as shown by shear bond strength testing comparisons.
    Non-toxicityThe device was found to be non-toxic based on an Oral Toxicity Test method.

    Note: The document states that the acceptance criterion for effectiveness is equivalence to the predicate device's effective bond strength, but it does not provide specific numerical thresholds or performance targets for either device's bond strength. It simply states that the Reliance S.E.P. "demonstrate[s] that the applicant device is equivalent to the legally marketed device in terms of effectiveness."


    Study Details

    1. Sample size used for the test set and the data provenance:

      • The document does not specify the sample size used for the shear bond strength testing.
      • The document does not specify the data provenance (e.g., country of origin, retrospective or prospective).
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • This information is not applicable to the type of study conducted. The ground truth for this performance study (shear bond strength testing) would be objective measurements of bond strength, not expert consensus.
    3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

      • Adjudication methods like 2+1 or 3+1 are typically used for studies involving subjective human assessment (e.g., image interpretation). This is a physical/mechanical performance study, so such adjudication is not applicable. The measurements would be objective.
    4. 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, an MRMC comparative effectiveness study was not done. This device is a self-etching primer, not an AI-assisted diagnostic tool.
    5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

      • This question is not applicable. The device is a physical product (self-etching primer), not an algorithm. The "standalone" performance here refers to the device's inherent mechanical properties.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • The ground truth for effectiveness was based on objective mechanical/physical measurements of shear bond strength. For safety, it was an Oral Toxicity Test method.
    7. The sample size for the training set:

      • This information is not applicable. This is a study of a physical medical device, not a machine learning algorithm that requires a "training set."
    8. How the ground truth for the training set was established:

      • This information is not applicable, as there is no "training set" in this context.
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