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510(k) Data Aggregation

    K Number
    K120469
    Device Name
    ERISMA-LP
    Manufacturer
    Date Cleared
    2012-08-13

    (179 days)

    Product Code
    Regulation Number
    888.3070
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K052131,K030840,K001272

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

    When used as a pedicle screw fixation system of the non-cervical posterior spine in skeletally mature patients using allograft and/or autograft, the Erisma™ Spinal System is indicated as an adjunct to fusion for one or more of the following:

    • Degenerative disc disease( Discogenic pain with degeneration of the disc confirmed . by history and radiographic studies)
    • . Degenerative spondylolisthesis with objective evidence of neurologic impairment.
    • Severe spondylolisthesis (Grades 3 and 4) of the fifth lumbar-first sacral (LS-S1) ◆ vertebral joint
    • Fracture.
    • Dislocation, ●
    • . Scoliosis.
    • Kyphosis, .
    • Spinal tumor.
    • Failed previous fusion (pseudarthrosis). .
    Device Description

    The Erisma™ LP instrumentation is designed for the surgical treatment of spinal pathologies. The treatment consists of the fusion of two or several vertebrae in order to restore spinal stability, with or without any other endocanalar concomitant surgical procedure.

    AI/ML Overview

    The provided document, K120469, is a 510(k) summary for a medical device called CLARIANCE Erisma-LP, a Noncervical Pedicle Spine System. This type of device is a physical medical implant, meaning its performance is primarily evaluated through non-clinical testing (e.g., mechanical, material, and biocompatibility testing) rather than clinical studies involving human patients for effectiveness claims in the way a diagnostic algorithm or a drug would be.

    Therefore, the requested information regarding acceptance criteria and studies that prove the device meets those criteria will be focused on the non-clinical testing performed rather than traditional clinical comparative effectiveness studies or standalone algorithm performance.

    Here's the breakdown based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly state quantitative "acceptance criteria" for performance in the typical sense of metrics like sensitivity, specificity, or AUC, as these would apply to diagnostic or AI-driven devices. Instead, the "acceptance criteria" for a spinal implant are adherence to recognized industry standards for mechanical and material performance.

    Acceptance Criterion (Standard Adherence)Reported Device Performance
    ASTM F1717 - 01Conforms to the standard, indicating validated design
    ASTM F1717 - 09Conforms to the standard, indicating validated design
    ASTM F1798 - 97 (Reapproved 2008)Conforms to the standard, indicating validated design
    ISO 14971 (Risk Management)Rigorous application of the standard, eliminating or mitigating known health hazards

    The "reported device performance" is a statement of conformance to these standards, implying that the device successfully met the test requirements outlined within them for aspects like static and fatigue properties of spinal implant constructs and interconnection mechanisms.

    2. Sample Size Used for the Test Set and Data Provenance

    • Sample Size for Test Set: Not applicable in the context of clinical data for performance evaluation. Non-clinical testing involves specific numbers of physical test specimens (implants, constructs) as defined by the ASTM standards, but these details are not provided in this summary.
    • Data Provenance (country of origin, retrospective/prospective): Not applicable, as this device's substantial equivalence was determined based on non-clinical testing against standards and comparison to predicate devices, not clinical data collection.

    3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

    • Number of Experts: Not applicable. Ground truth for non-clinical testing refers to the established standards themselves, which are developed by expert committees within organizations like ASTM. The specific number and qualifications of individuals involved in the testing itself are not detailed here.

    4. Adjudication Method for the Test Set

    • Adjudication Method: Not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies to resolve discrepancies in expert interpretations (e.g., image readings). For non-clinical device testing, results are objective measurements against predetermined physical criteria within the standards.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    • Was an MRMC study done? No. MRMC studies are typically performed for diagnostic devices (especially those involving image interpretation by multiple readers) to assess the impact of software or AI on human performance. This device is a physical implant.
    • Effect size of human readers improve with AI vs without AI assistance: Not applicable.

    6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

    • Was a standalone study done? No. This concept applies to diagnostic algorithms or AI systems, not physical implants. The "performance" of the Erisma-LP device is its mechanical integrity and biocompatibility, as demonstrated through non-clinical laboratory tests.

    7. Type of Ground Truth Used

    • Type of Ground Truth: The "ground truth" for this device's performance evaluation lies in the established performance criteria and test methodologies within recognized industry standards (ASTM F1717-01, ASTM F1717-09, ASTM F1798-97) and the principles of risk management (ISO 14971). For a physical implant, demonstrating conformance to these standards is how "ground truth" of safety and basic effectiveness (e.g., mechanical stability) is established for 510(k) clearance.

    8. Sample Size for the Training Set

    • Sample Size for Training Set: Not applicable. This device is not an AI algorithm, so there is no "training set."

    9. How the Ground Truth for the Training Set was Established

    • How Ground Truth for Training Set was Established: Not applicable. As there is no training set for an AI algorithm, this question does not apply.
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