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510(k) Data Aggregation

    K Number
    K142057
    Manufacturer
    Date Cleared
    2015-01-13

    (168 days)

    Product Code
    Regulation Number
    888.3040
    Reference & Predicate Devices
    Why did this record match?
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    InFix Cannulated Screw System is generally intended for fracture fixation of various bones and bone fragments, such as femoral neck, intercondylar femoral, malleolus, pilon tibial, calcaneus, talus, tibial plateau, tarsal, wrist, metacarpal, carpal, scaphoid and radius fracture. InFix Cannulated Screw System is also intended for fixation arthrodesis, iliosacral dislocations, and hallux valgus corrections.

    Accessories implants:

    The round washer is used to increase bone contact area for distributing the forces/load and prevent the screw head from sinking into the bone.

    Device Description

    The InFix Cannulated Screw System includes eight cannulated screw specifications and associated washers, which are manufactured from stainless steel and titanium alloy. The cannulated screw is a self-tapping and self-drilling screw with a cancellous thread that can be guided into a position via a guided wire. They are used to aid in the alignment and stabilization of fractures to the skeletal system.

    AI/ML Overview

    Here's an analysis of the provided text regarding the acceptance criteria and study proving device performance:

    This document is a 510(k) premarket notification for the InFix Cannulated Screw System, which is a Class II medical device. The primary purpose of this submission is to demonstrate substantial equivalence to existing predicate devices, rather than to prove de novo safety and effectiveness through extensive clinical trials.

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria CategorySpecific CriteriaReported Device Performance
    Biomechanical Testing (ASTM F543)Self-tapping performanceResults indicate substantial equivalence to legally marketed devices.
    Torsional strengthResults indicate substantial equivalence to legally marketed devices.
    Axial pullout strengthResults indicate substantial equivalence to legally marketed devices.
    Driving torqueResults indicate substantial equivalence to legally marketed devices.
    Cleaning ValidationAAMI TIR30:2011 guidance requirementsTest result shows that the acceptance criteria is met.
    Sterilization ValidationANSI/AAMI/ISO 17665-1 requirementsTest result shows that the acceptance criteria is met.

    Details Regarding the Study and Acceptance Criteria:

    This submission relies heavily on non-clinical tests to demonstrate substantial equivalence. Clinical effectiveness studies as one might find for a novel AI device are not presented here because this is a hardware medical device for which the FDA determination is about substantial equivalence to already approved devices. Therefore, the "acceptance criteria" here are largely benchmarks against the performance of predicate devices and adherence to recognized standards.

    2. Sample size used for the test set and the data provenance:

    • Biomechanical Test: The document states "The biomechanical tests ASTM F543 were performed". It does not specify the exact number of screws or test samples used for each performance metric (self-tapping, torsional, axial pullout, driving torque).
    • Cleaning Validation & Sterilization Validation: Similarly, the document does not specify the number of samples used for these validation tests.
    • Data Provenance: Not explicitly stated, but typically these tests would be conducted in a laboratory setting by the manufacturer or a contracted lab. The tests are non-clinical, so "country of origin of the data" in terms of patient demographics is not applicable. These are prospective tests performed to meet regulatory requirements.

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

    • Not applicable in this context. For a hardware device demonstrating substantial equivalence through non-clinical testing, ground truth is established by objective engineering measurements against specified physical properties and performance standards (e.g., ASTM F543). There isn't a need for expert consensus on an interpretation of an output, as would be the case for an AI diagnostic device.

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

    • Not applicable. Adjudication methods like 2+1 are used for expert review of images or data to establish a ground truth or resolve discrepancies in diagnostic labeling. This is not relevant for biomechanical or validation testing of a physical 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:

    • No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI-powered diagnostic devices or software that assists human interpretation. The InFix Cannulated Screw System is a physical bone fixation device, not a diagnostic tool or AI-assisted product.

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

    • Not applicable. This device is a physical implant. The concept of "standalone algorithm performance" does not apply.

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

    • For the biomechanical tests (ASTM F543), the "ground truth" is established by engineering standards and direct physical measurements. The performance of the InFix Cannulated Screw System is compared against the known performance characteristics of the predicate devices and the requirements of the ASTM standard.
    • For cleaning and sterilization validations, the "ground truth" is adherence to the specified industry standards (AAMI TIR30:2011 and ANSI/AAMI/ISO 17665-1).

    8. The sample size for the training set:

    • Not applicable. This device is hardware and does not involve machine learning or AI, and therefore has no "training set."

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

    • Not applicable. As there is no training set for this hardware device, there is no ground truth to be established for it.
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    K Number
    K082949
    Date Cleared
    2008-11-25

    (54 days)

    Product Code
    Regulation Number
    888.3040
    Why did this record match?
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Cortical Screws are intended for fixation of fractures, osteotomies and nonunions of the clavicle, scapula, olecranon, humerus, radius, ulna, pelvis, tibia, calcaneous, femur and fibula.

    Large Cannulated Screws (4.5mm diameter and larger) are intended for fracture fixation of large bones and large bone fragments. Diameters 6.5mm and larger are intended for large bones and large bone fragments such as femoral neck fractures; slipped capital femoral epiphyses; tibial plateau fractures; ankle arthrodeses; pediatric femoral neck fractures; intercondylar femur fractures; and subtalar arthrodeses.

    Small Cannulated Screws (4.0mm diameter and smaller) are intended for fixation of fractures and non-unions of small bones and small bone arthrodeses. Examples include scaphoid and other carpal fractures, metacarpal and phalangeal fusions, osteotomies, and bunionectomies.

    Device Description

    Cannulated screws are machined, metallic screws with a cannulation that are self drilling and self tapping, which can be guided into position by a guide wire.

    Cortical and cancellous screws are machined, metallic screws and are self tapping.

    All screws utilize a hex shaped recess that accepts a standard hex drive. Each type is offered in a variety of diameters and lengths, as well as short, medium, and fully threaded options.

    Materials: The devices are manufactured from 316L Stainless Steel which meets ASTM F138 standards.

    Function: Bone screws functions are to provide immediate stability and temporary fixation during the natural healing process.

    AI/ML Overview

    The provided text is a 510(k) premarket notification for OrthoPediatrics Bone Screws. It primarily focuses on demonstrating substantial equivalence to previously marketed predicate devices rather than presenting a study against specific acceptance criteria for the new device's performance.

    Therefore, the document does not contain the information requested regarding acceptance criteria and a study that proves the device meets those criteria.

    Key reasons for this include:

    • 510(k) Premarket Notification Focus: A 510(k) is a premarket submission made to FDA to demonstrate that the device to be marketed is at least as safe and effective as a legally marketed device (predicate device) and does not require premarket approval (PMA). This is typically achieved by demonstrating "substantial equivalence," not by conducting new clinical studies or setting and meeting new performance acceptance criteria for the device itself.
    • Lack of Performance Data: The document describes the device, its materials, function, and indications for use. It lists predicate devices. However, there is no mention of specific performance metrics (e.g., strength, durability, fatigue life, accuracy) for the OrthoPediatrics Bone Screws, nor any study data (sample sizes, ground truth, expert opinions) that would demonstrate the device meets such criteria.
    • No Mention of AI/Algorithm: The context of "AI," "test set," "training set," "experts," "adjudication," "MRMC," and "standalone algorithm performance" strongly suggests a request related to an AI/Machine Learning device. The OrthoPediatrics Bone Screws are described as machined, metallic screws, which are physical hardware devices, not software or AI-driven systems.

    In summary, this document is for a medical device (bone screws) seeking market clearance through substantial equivalence, and as such, it does not include performance studies with acceptance criteria in the manner described for software or AI-based diagnostic/assistive devices.

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