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510(k) Data Aggregation

    K Number
    K133840
    Date Cleared
    2014-07-29

    (223 days)

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

    K130340

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

    KangLi® locking plate system is intended for adult patients as indicated for fixation of fractures of tibia.

    Device Description

    KangLi® locking plate system contains locking plates with various specifications, metal bone and locking screws with various specifications, and various specific instruments. The bone plates are used for fixation of bones. The screws are used for fix the plates on the bones and the instruments are used for completing the surgery. The bone plates are manufactured from unalloyed titanium that conforms to ASTM F67. The metal bone and locking screws are made of Ti6AI4V ELI that meets to ASTM F136. The materials of titanium and Ti6AI4V ELI are widely used in the industry with well-known biocompatibility. No new materials are used in the development of this implant.

    AI/ML Overview

    The provided text describes the 510(k) submission for the KangLi® Locking Plate System, a medical device for bone fixation. However, it does not contain information about acceptance criteria and a study proving the device meets those criteria in the context of an AI/ML device.

    The document is a traditional 510(k) summary for a physical medical device (locking plates and screws), not a software or AI/ML device. Therefore, the questions related to AI/ML device evaluation (like sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, or standalone algorithm performance) are not applicable to this submission.

    Instead, this submission focuses on bench testing to demonstrate Substantial Equivalence (SE) to a predicate device. The "acceptance criteria" here are the performance requirements outlined in the referenced ASTM standards.

    Here's a breakdown of the information that can be extracted from the provided text, modified to fit the context of device performance, and an explanation of why other requested information is not present:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Acceptance Criteria (Standard Reference)Reported Device Performance (Compliance)
    ASTM F 382-99 (Reapproved 2008): Standard Specification and Test Method for Metallic Bone PlatesThe proposed device complies with and meets all design specifications. Verified through bench tests.
    - Static four point bendingTest results demonstrated compliance.
    - Dynamic four point bendingTest results demonstrated compliance.
    ASTM F 543-07: Standard Specification and Test Methods for Metallic Medical Bone ScrewsThe proposed device complies with and meets all design specifications. Verified through bench tests.
    - Torsional propertiesTest results demonstrated compliance.
    - Driving torqueTest results demonstrated compliance.
    - Pull out testTest results demonstrated compliance.

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

    • Sample Size: Not explicitly stated. For bench testing of physical orthopedic implants, sample sizes are typically determined by relevant ISO/ASTM standards or internal company protocols to ensure statistical significance for mechanical properties. These are usually small numbers (e.g., 5-10 samples per test arm) rather than large datasets.
    • Data Provenance: Not applicable in the context of "country of origin of data" or "retrospective/prospective" as this refers to mechanical bench testing, not clinical or image data. The testing was conducted by Suzhou Kangli Orthopaedics Instrument Co., Ltd., which is based in China.

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

    • Not applicable. "Ground truth" in this context refers to the measured physical properties of the device meeting the specified ASTM standards. This is determined by engineering measurements and quality control processes, not expert clinical interpretation.

    4. Adjudication method for the test set:

    • Not applicable. Mechanical testing involves objective measurements against predefined thresholds, not subjective adjudication.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done:

    • No. This type of study is for evaluating the diagnostic performance of a device (often AI/ML systems) with human readers. The KangLi® Locking Plate System is a physical implant, not a diagnostic tool.

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

    • No. This relates to AI/ML algorithms. The KangLi® system is a physical implant. Its performance is inherent in its mechanical properties.

    7. The type of ground truth used:

    • Engineering/Mechanical Specifications: The "ground truth" for this device's performance is adherence to the mechanical performance specifications defined by the ASTM standards (F 382-99 and F 543-07). This includes properties like static and dynamic bending strength for plates, and torsional properties, driving torque, and pull-out strength for screws.

    8. The sample size for the training set:

    • Not applicable. There is no "training set" in the context of a physical medical device being evaluated through bench testing. The design of the device is based on engineering principles and knowledge of materials, not machine learning algorithms.

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

    • Not applicable, as there is no training set.

    In summary: The provided text details the non-clinical bench testing conducted to demonstrate that the KangLi® Locking Plate System structurally performs in accordance with established ASTM standards for metallic bone plates and screws. This type of regulatory submission focuses on mechanical and material properties to prove "Substantial Equivalence" to a previously approved device, not on diagnostic accuracy or AI/ML performance. Therefore, most of the questions are not relevant to this specific document.

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