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510(k) Data Aggregation

    K Number
    K080744

    Validate with FDA (Live)

    Date Cleared
    2008-07-17

    (122 days)

    Product Code
    Regulation Number
    872.3640
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The HG II Fixture System is indicated for use in partially or fully edentulous mandibles and maxillae, in support of single or multiple-unit restorations including; cemented retained, screw retained, or overdenture restorations, and terminal or intermediate abutment support for fixed bridgework. The HG II Fixture System is for single and two stage surgical procedures. It is not for immediate load.

    Device Description

    The HG II Fixture System is a dental implant made of titanium metal intended to be surgically placed in the bone of the upper or lower jaw arches.

    AI/ML Overview

    The provided document describes a 510(k) premarket notification for the "HG II Fixture System," a dental implant device, and focuses on demonstrating its substantial equivalence to existing predicate devices.

    This type of submission does not involve clinical studies with acceptance criteria, human readers, or ground truth establishment in the way requested for software algorithms or diagnostic devices. Instead, substantial equivalence is established by comparing the new device's material, design, function, intended use, and performance characteristics to legally marketed predicate devices.

    Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, expert involvement, and ground truth is not applicable to this 510(k) submission.

    Here's an explanation based on the document:

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

    • Not Applicable. The document does not describe specific numerical acceptance criteria (e.g., sensitivity, specificity, accuracy) or quantitative performance metrics from a study that would typically be presented in such a table. The evaluation is based on demonstrating similarity to predicate devices rather than meeting a pre-defined performance threshold against a "ground truth."
    • The document states: "The HG II Fixture System has been subjected to safety, performance, and product validations prior to release. Safety tests including biocompatibility have been performed to ensure the devices comply with the applicable International and US regulations." However, the specific results or acceptance criteria for these internal validations are not detailed in this 510(k) summary.

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

    • Not Applicable. No "test set" in the context of an algorithm or diagnostic study is mentioned. This filing is about a medical device (dental implant).

    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):

    • Not Applicable. No ground truth establishment by experts for a test set is part of this type of submission.

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

    • Not Applicable. No adjudication method for a test set is relevant to this submission.

    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 hardware medical device (dental implant), not an AI-assisted diagnostic tool. Therefore, MRMC studies are not relevant.

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

    • Not Applicable. This is a hardware medical device, not an algorithm.

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

    • Not Applicable. No "ground truth" as typically defined for diagnostic or AI devices is used in this 510(k) submission. The evaluation relies on demonstrating equivalence to predicate devices through comparisons of material properties, design, intended use, and safety testing (biocompatibility).

    8. The sample size for the training set:

    • Not Applicable. No training set, as typically understood for machine learning or AI models, is used for this device.

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

    • Not Applicable. No training set or associated ground truth establishment is relevant to this 510(k) submission.

    In summary, this 510(k) document demonstrates substantial equivalence by:

    • Comparing the device's material, indication for use, design, and technological characteristics to predicate devices.
    • Stating that safety tests, including biocompatibility, were performed. (The specific results of these tests are not provided in this public summary, but would have been part of the full 510(k) submission.)
    • Concluding that based on this information, the device is safe, effective, and substantially equivalent.
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