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510(k) Data Aggregation

    Why did this record match?
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Fixion™ Interlocking Intramedullary Nail is intended for use in fixation of various types of fractures, including diaphyseal fractures and short distal or proximal fragments in the long bones.

    Device Description

    The Fixion Interlocking Intramedullary Nailing System consist of the following main components: 1. The Nail Implant is an expandable non-slotted stainless steel cylindrical tube, with a cap protected, female threaded proximal end with holes for interlocking screws to lock the nail in the bone. The Nail Implant may also have both proximal and distal ends with holes for interlocking screws. 2. The Instrument Set consists of a few accessories used during insertion and removal (if required) of the Nail Implant. 3. The Inflation Device is a single-use, manual, plastic pump to be filled with sterile inflation liquid. Once the nail is positioned within the medullary canal, rotation of the pump handle allows for nail diameter increase to its intended diameter under x-ray and controlled pressure. Interlocking screws may be used to lock the nail inside the bone.

    AI/ML Overview

    The provided text K013449 describes the Fixion Interlocking Intramedullary Nailing System. However, this document does not contain information about acceptance criteria or a study proving device performance in the context of diagnostic accuracy, which is typically associated with AI/ML devices.

    Instead, the document focuses on:

    • Materials and Mechanical Performance for a physical medical device (an intramedullary nail).
    • Substantial equivalence to a predicate device.
    • Intended use and system description.

    Therefore, I cannot provide the requested information in the format of a diagnostic performance study, as the provided input does not pertain to such a device or study.

    Here's a breakdown of why each requested point cannot be addressed with the provided text:

    1. A table of acceptance criteria and the reported device performance: The document states the device meets ASTM F138 (material spec), ASTM F565 (care/handling), and ASTM F1264-99 (4-point bending mechanical testing). These are standards the device adheres to, not specific performance metrics or acceptance criteria as would be defined for a diagnostic AI model (e.g., sensitivity, specificity, AUC). There are no reported numerical performance metrics from a study in this context.
    2. Sample sized used for the test set and the data provenance: Not applicable. This document describes a physical implant, not a diagnostic algorithm.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical implant's mechanical properties is established through material testing and engineering standards, not expert clinical review of data.
    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
    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 not an AI/ML diagnostic device.
    6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable.
    7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): For a physical device, the "ground truth" would be adherence to material specifications (ASTM F138) and mechanical performance standards (ASTM F1264-99).
    8. The sample size for the training set: Not applicable. This device does not use a training set in the context of AI/ML.
    9. How the ground truth for the training set was established: Not applicable.

    In summary, the provided document describes a traditional medical device (an intramedullary nailing system) and its compliance with established material and mechanical testing standards, not an AI/ML-driven diagnostic device with associated performance studies.

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