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510(k) Data Aggregation

    K Number
    K030249

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2003-02-14

    (21 days)

    Product Code
    Regulation Number
    888.3060
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Surgical Titanium Mesh System is indicated for use in the thoracolumbar spine (T1-L5) to replace a diseased vertebral body resected or excised for the treatment of tumors, to achieve anterior decompression of the spinal cord and neural tissues, and to restore the height of a collapsed vertebral body.

    The Surgical Titanium Mesh System is also indicated for treating fractures of the thoracic and lumbar spine.

    The Surgical Titanium Mesh System is designed to restore the biomechanical integrity of the anterior, middle, and posterior spinal column even in the absence of fusion for a prolonged period.

    The Surgical Titanium Mesh System is intended for use with supplemental internal fixation. The supplemental internal fixation systems that may be used with the Surgical Titanium Mesh System include DePuy AcroMed titanium plate or rod systems (e.g. Kaneda SR, University Plate, M-2, ISOLA, VSP, Moss Miami, TiMX, Monarch and Profile).

    Device Description

    Not Found

    AI/ML Overview

    The provided text describes the regulatory clearance for the "Surgical Titanium Mesh™ System" as a medical device, focusing on its intended use and general performance data (biomechanical testing). It does NOT contain information about acceptance criteria for device performance, a study to prove it meets those criteria, sample sizes for test sets, data provenance, expert qualifications for ground truth, adjudication methods, MRMC studies, standalone algorithm performance, or how ground truth for training sets was established.

    Therefore, most of the requested information cannot be extracted from the given text.

    Here's what can be extracted based on the provided document:

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

    Acceptance CriteriaReported Device Performance
    Not specified in the documentBiomechanical testing, including static axial compression and dynamic axial compression, were conducted. (Performance results and criteria for success are not detailed.)

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

    • Sample Size for Test Set: Not specified.
    • Data Provenance: Not specified. This document pertains to a 510(k) submission for a medical device and typically such submissions detail testing protocols and results, but this specific excerpt doesn't provide those details.

    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 as this is a physical medical device (implant) and not related to AI or diagnostic image analysis where expert-established ground truth for a test set would be relevant.

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

    • Not applicable for a physical medical device.

    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 physical medical device, not an AI diagnostic tool.

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

    • Not applicable. This is a physical medical device, not an AI algorithm.

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

    • Not applicable. Performance for this device would be based on engineering and biomechanical standards, not a clinical "ground truth" as typically defined for diagnostic AI. The "performance data" mentioned is biomechanical testing.

    8. The sample size for the training set

    • Not applicable. This is a physical medical device, not an AI algorithm.

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

    • Not applicable. This is a physical medical device, not an AI algorithm.
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