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510(k) Data Aggregation

    K Number
    K230067
    Date Cleared
    2023-09-22

    (256 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    New Paradigm Biomedical

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

    The Para-Fix External Fixation System is intended to provide stabilization of open and/or unstable fractures and where tissue injury precludes the use of other fracture treatments such as IM rodding or casting.

    The specific indications for the Para-Fix External Fixation System include:

    · Bone fracture fixation
    · Osteotomy
    · Arthrodesis
    · Correction of deformity
    · Revision procedure where other treatments or devices have been unsuccessful
    · Bone reconstruction procedures

    Device Description

    The New Paradigm Biomedical (NPB) Para-Fix External Fixation System is intended for use in external fixation of various long bone fractures, including tibial, femoral, pelvic, and humeral fractures in adults. The Para-Fix system consists of implants, & instrumentation for external fixation. The system features implants (Schanz Screws) in various diameters (05 – 6mm) and lengths (120 – 300mm) to accommodate different anatomic sizes of patients. Schanz Screws are manufactured from medical grade stainless steel per ASTM F138. Para-Fix frame components include Clamps are available in Combination (pin to rod, rod to rod) or Multi-Pin clamps are manufactured from stainless steel. Ø11mm rods are available in lengths ranging from 65 – 500mm and are manufactured from carbon fiber. The Para-Fix system is provided non-sterile.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the "Para-Fix External Fixation System." This is a medical device for orthopedic use, specifically for stabilizing bone fractures and other orthopedic conditions.

    The document focuses on demonstrating substantial equivalence to existing legally marketed predicate devices, rather than describing a study to prove acceptance criteria for a new AI/software-based medical device. Therefore, much of the requested information regarding "acceptance criteria," "device performance," "sample sizes," "ground truth," "expert readers," and "MRMC studies" is not applicable or present in this specific 510(k) summary.

    Here's how the provided information relates to the request:

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

    • Acceptance Criteria: The primary acceptance criterion for a 510(k) submission like this is substantial equivalence to a predicate device. This is typically demonstrated through a comparison of technological characteristics, intended use, and performance data (often non-clinical in this case).
    • Reported Device Performance: The performance is reported in terms of mechanical testing showing substantial equivalence to the predicate device.
    Acceptance Criteria (Implied for 510(k) Substantial Equivalence)Reported Device Performance
    Mechanical performance similar to predicate device (ASTM F1541-17)"The subject device performed substantially equivalent to the primary predicate device in all full construct test modalities." (This refers to tests like Compression Connector Testing, Static Axial Compression Subassembly Testing, Static Torsion Full Construct Testing, Static Axial Compression Testing, and Fatigue (Multi-Cycle) Axial Compression/Tension Full Construct Testing).
    Intended Use Consistency"The indications for use of the subject device are consistent with those of the primary and secondary predicate external fixation systems."
    Technological Characteristics SimilaritySimilar materials (stainless steel, carbon fiber), similar components (Schanz Screws, clamps, rods), identical principles of operation.

    2. Sample sizes used for the test set and the data provenance

    • Sample Size for Test Set: Not explicitly stated as a number of patients or clinical cases. For mechanical testing, the "sample size" would refer to the number of devices or components tested. This information (e.g., number of replicates for each mechanical test) is not detailed in the summary but would be part of the full test reports.
    • Data Provenance: The mechanical testing was performed by "Element Materials Technology (Fairfield, OH)" and "NexTek Innovations (Logan, UT)". This is laboratory-based testing, not human clinical or retrospective/prospective data collection from patients.

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

    • This question is not applicable to this type of device (an external fixation system). "Ground truth" in the context of mechanical testing is established by the test standards (ASTM F1541-17) and the results obtained from the testing equipment, not by expert human interpretation like in diagnostic AI.

    4. Adjudication method for the test set

    • This question is not applicable. There is no human adjudication for mechanical test results; the results are quantitative measurements against defined standards.

    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

    • This question is not applicable. This device is a mechanical external fixation system, not an AI-assisted diagnostic tool. No human reader studies (MRMC) were conducted or are relevant.

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

    • This question is not applicable. There is no algorithm or software for "standalone performance" in this context.

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

    • The "ground truth" for demonstrating substantial equivalence for this device is based on pre-defined mechanical testing standards (ASTM F1541-17) and the measured performance of both the subject device and the predicate device under these standardized conditions.

    8. The sample size for the training set

    • This question is not applicable. This device does not involve machine learning or a "training set."

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

    • This question is not applicable. As there is no training set for an AI algorithm, no ground truth was established for it.
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