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510(k) Data Aggregation

    K Number
    K113364
    Date Cleared
    2012-02-29

    (106 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    2.7MM LCP ULNA OSTEOTOMY SYSTEM

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

    The 2.7mm LCP Ulna Osteotomy System is indicated for fixation of fractures, osteotomies, nonunions, replantations, and fusions of small bones and small bone fragments, including osteopenic bone in the ulna. The 2.7mm LCP Ulna Osteotomy System is indicated for use in both adults and adolescents (12-21 years) in which growth plates have fused or in which growth plates will not be crossed by screw fixation.

    Device Description

    The 2.7mm LCP Ulna Osteotomy System consists of two plates, 6- hole and 8-hole which will be available in titanium alloy and stainless steel, to be offered sterile and non-sterile. This system also includes instrumentation which supports transverse and oblique osteotomy cuts as well as plate placement and fixation.

    AI/ML Overview

    This document describes the 2.7mm LCP Ulna Osteotomy System and its substantial equivalence to predicate devices, rather than a study with acceptance criteria for a device's performance measured against a specific metric. The provided text is a 510(k) summary for a medical device submitted to the FDA, which focuses on demonstrating substantial equivalence to already legally marketed devices, primarily through design, material, and intended use comparisons, along with bench testing.

    Therefore, many of the requested categories in the prompt are not applicable to the information contained in this 510(k) summary. I will address the applicable parts and indicate when information is not present.

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

    The document does not explicitly state acceptance criteria in terms of numerical performance metrics for a specific clinical or diagnostic outcome as one might find for an AI/ML device or a diagnostic test. Instead, acceptance criteria for this type of submission are typically demonstrating that the device is as safe and effective as the predicate device(s). The "performance" is demonstrated through similarity in design, materials, intended use, and bench testing to confirm mechanical equivalence.

    Aspect of Equivalence/PerformanceAcceptance Criteria (Implicit)Reported Device Performance (as described in the summary)
    Indications for UseSame or similar indications for use as predicate devices."The proposed system has the same indications for use..." Indicated for "fixation of fractures, osteotomies, nonunions, replantations, and fusions of small bones and small bone fragments, including osteopenic bone in the ulna. For use in adults and adolescents (12-21 years) in which growth plates have fused or will not be crossed by screw fixation." (Matches predicate's scope).
    DesignSimilar in design to predicate devices."is similar in design..." Consists of two plates (6-hole and 8-hole) for ulna osteotomy, includes instrumentation for transverse and oblique osteotomy cuts, plate placement, and fixation.
    MaterialsComposed of the same or equivalent materials as predicate devices."is composed of the same materials." Available in titanium alloy and stainless steel (materials commonly used in bone fixation devices and likely matching predicates).
    Fundamental TechnologyIncorporates the same fundamental product technology as predicate devices."incorporates the same fundamental product technology..." (Implied to be internal bone fixation for the ulna using plates and screws).
    Mechanical Strength/IntegrityBending strength and mechanical properties comparable to predicate devices. (Often guided by relevant ASTM or ISO standards for orthopedic implants, though not stated here)."static and dynamic bench testing was performed as well as calculations comparing the bending strength of the subject and predicate devices based on geometric analyses and material characteristics, defined in standard." (The summary does not provide specific numerical results or comparison values from this testing, only that it was performed to support substantial equivalence).

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

    This information is not applicable. The device is a bone fixation system, not an AI/ML or diagnostic device that uses a "test set" of patient data. The primary "testing" mentioned is bench testing (mechanical).

    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. There is no mention of "ground truth" established by experts in the context of a test set, as this is a mechanical fixation device, not a diagnostic or AI system.

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

    This information is not applicable. There is no "test set" of patient data requiring adjudication in this context.

    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

    This information is not applicable. This is a physical medical device (bone plate and screws), not an AI-assisted diagnostic tool.

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

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

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

    This information is not applicable in the typical sense. For mechanical devices, "ground truth" relates to material properties, design specifications, and performance under rigorous bench testing conditions, comparing against established engineering standards and predicate device performance.

    8. The sample size for the training set

    This information is not applicable. There is no "training set" for this type of medical device submission.

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

    This information is not applicable. There is no "training set" or corresponding ground truth establishment in this context.


    Summary of the Study that Proves the Device Meets the Acceptance Criteria (Based on Available Information):

    The "study" proving the device meets the acceptance criteria, in the context of this 510(k) submission, is a demonstration of substantial equivalence to legally marketed predicate devices. This is achieved through:

    • Comparative Analysis: The proposed 2.7mm LCP Ulna Osteotomy System was directly compared to predicate devices (K063049- Modular Mini Fragment LCP System and K073228 - DC Ulnar Shortening System).
    • Design & Intended Use Parity: The submission asserts that the new system has the same indications for use, is similar in design, and incorporates the same fundamental product technology as the predicate devices.
    • Material Equivalence: The device is composed of the same materials (titanium alloy and stainless steel) as the predicate systems, ensuring similar biocompatibility and mechanical properties.
    • Bench Testing: To further support substantial equivalence in terms of mechanical performance, static and dynamic bench testing was performed. This testing, combined with calculations comparing the bending strength based on geometric analyses and material characteristics (defined in standard, likely ASTM or ISO standards for orthopedic implants), aimed to demonstrate that the new device's mechanical properties are comparable to or meet the requirements established by the predicate devices or relevant standards.

    The success of this "study" is the FDA's determination that the device is substantially equivalent to the predicate devices, meaning it is as safe and effective. The 510(k) summary serves as the evidence for this determination, rather than providing detailed results of a clinical trial or performance study against specific acceptance metrics for AI/ML or diagnostic devices.

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