Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K233593
    Date Cleared
    2024-02-06

    (90 days)

    Product Code
    Regulation Number
    888.3070
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The MAGEC Spinal Bracing and Distraction System is indicated for skeletally immature patients with severe progressive spinal deformities (e.g., Cobb angle of 30 degrees or more; thoracic spine height less than 22 cm) secondary to early-onset scoliosis associated with or at risk of Thoracic Insufficiency Syndrome(TIS). TIS is defined as the inability of the thorax to support normal respiration or lung growth.

    Device Description

    The subject MAGEC Spinal Bracing and Distraction System has an identical design and principle of operation to the predicate design iterations cleared in the predicate Magec System (K201543, K161751, K140613). The subject system includes sterile single use MAGEC rods manufactured from Ti-6Al-4V, conforming to ASTM F136, along with various accessories including a sterile Rod Template and Manual Distractor, a non-sterile Wand Magnet Locator, and is compatible with a hand held External Remote Controller (ERC) 1 or 2. The MAGEC rod can be surgically implanted using appropriate NuVasive Reline 4.5-5.0 (Reline Small Stature or RSS) or Armada fixation components (i.e., pedicle screws, hooks and/or connectors). The titanium MAGEC rod includes an actuator portion that holds a small internal magnet. The magnet in the actuator can be turned non- invasively by use of the ERC, which is electrically powered. The hand-held non-invasive ERC is placed over the patient's spine and then manually activated, which causes the implanted magnet to rotate and either distract or retract the rod. Periodic distraction of the rod is performed to lengthen the spine and to provide adequate bracing during growth to minimize the progression of scoliosis. Once the physician determines that the implant has achieved its intended use and is no longer required, the implant is explanted.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the MAGEC Spinal Bracing and Distraction System, focusing on expanding its indications for use. It primarily demonstrates substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria in the typical sense of a diagnostic or AI device.

    However, based on the information provided, we can infer "acceptance criteria" from the measured clinical outcomes that are presented to support the expanded indication. The device's performance is demonstrated through a retrospective registry study comparing clinical and radiographic data.

    Here's a breakdown of the requested information:

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

    The document doesn't explicitly state "acceptance criteria" with numerical thresholds as one might find for a new, novel device. Instead, the study aims to show that the performance of the MAGEC System in older skeletally immature patients (subject group) is comparable to its established performance in younger patients (predicate group). Therefore, the "acceptance criteria" are implicitly that the clinical outcomes in the subject group should not be worse than those in the predicate group, supporting substantial equivalence.

    Acceptance Criteria (Inferred from comparison)Reported Device Performance (Subject Group 2: Age ≥10 years)Reported Device Performance (Predicate Group 1: Age <10 years)
    Major curve Cobb angle, Δ, mean (not worse)25.0%26.5%
    Thoracic height (T1-T12), Δ, mean (not worse)15.5%15.1%
    Spinal height (T1-S1), Δ mean (not worse)15.3%15.3%
    Device-related adverse events (not worse)8.1%35.3%

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

    • Sample Size (Test Set):
      • Group 1 (Predicate: Age <10 years): N=1,080 patients
      • Group 2 (Subject: Age ≥10 years): N=172 patients
      • Group B (Subject/Literature: Age ≥10 years): N=57 patients
    • Data Provenance: Retrospective registry study. The country of origin is not specified in the provided text.

    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)

    The document does not mention the use of experts to establish ground truth for the test set in the context of image interpretation or diagnostic accuracy. This is a spinal bracing and distraction system, and the "ground truth" for its effectiveness is based on clinical and radiographic measurements taken during the treatment process within the registry.

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

    Not applicable. The study is a retrospective registry study tracking clinical and radiographic outcomes, not an adjudication process for diagnostic accuracy.

    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 medical device for spinal treatment, not an AI-assisted diagnostic device that would involve human readers.

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

    Not applicable. This is a physical medical device (spinal bracing and distraction system), not an algorithm or AI system.

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

    The "ground truth" for the device's effectiveness is based on clinical and radiographic outcomes data (e.g., changes in Cobb angle, thoracic height, spinal height, and incidence of device-related adverse events) collected from patients treated with the MAGEC System.

    8. The sample size for the training set

    Not applicable. This is a study of a physical medical device, not a machine learning model, so there is no training set in the AI sense.

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

    Not applicable, as there is no training set for an AI model. For the clinical study, the "ground truth" (i.e., the collected patient data and outcomes) was established through existing medical records and measurements from the retrospective registry study.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1