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Fracture of the proximal extremity of the humerus. Fracture of the diaphysis of the humerus.

The FH Industrie TELEGRAPH® EVOLUTION Humeral Nailing System includes short and long intramedullary cannulated humeral nails with right and left orientations, proximal screws and a washer. The nails, screws, and washer are intended for use in treatment of fracture of the proximal extremity of the humerus or fracture of the diaphysis of the humerus. All implantable components are manufactured from medical grade titanium alloy (Ti6Al4V-ELI). The nails that are the subject of this submission are cannulated.

I'm sorry, but I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them based on the provided text.

The document you provided, K200127, is a 510(k) Premarket Notification from the FDA for a medical device called the "TELEGRAPH® EVOLUTION Humeral Nailing System." This document primarily focuses on demonstrating substantial equivalence to previously cleared devices, rather than laying out specific, quantitative performance acceptance criteria or detailed study results for a new, AI-powered diagnostic device.

Here's why the provided text does not contain the information you are looking for:

• Device Type: The device described is a surgical implant (intramedullary fixation rod for humeral fractures), not an AI-powered diagnostic or imaging device. Therefore, the types of performance metrics and study designs you've asked about (e.g., sensitivity, specificity, MRMC studies, ground truth establishment for AI models) are not relevant to this mechanical device.
• Regulatory Pathway: The 510(k) pathway is for demonstrating a new device is "substantially equivalent" to a legally marketed predicate device. This typically involves comparisons of indications for use, technological characteristics (materials, design, dimensions), and often mechanical testing to show similar performance to the predicate. It does not generally require the kind of clinical performance studies with specific statistical acceptance criteria that would be needed for novel diagnostic algorithms (like those typically found in a De Novo or PMA submission for AI/ML devices).
• "Performance Testing" Section: The "Performance Testing" section in the document refers to:
  • Sterilization (ISO 11137), packaging (ISO 11607), and biocompatibility (ISO 10993-1) validations: These are standard tests for medical device safety and sterility, not clinical performance metrics.
  • Mechanical testing per ASTM F1264 and ASTM F543: These are engineering standards for testing the mechanical properties (e.g., strength, fatigue) of orthopedic implants. The conclusion states that "results have shown them to be substantially equivalent to the predicate device," which is a comparative statement rather than a demonstration of meeting predefined absolute performance thresholds.

In summary, the provided document does not discuss:

1. A table of acceptance criteria and reported device performance related to diagnostic accuracy.
2. Sample sizes for test sets in the context of diagnostic performance.
3. Number of experts establishing ground truth or their qualifications.
4. Adjudication methods.
5. MRMC comparative effectiveness studies.
6. Standalone algorithm performance.
7. Types of ground truth like pathology or outcomes data for diagnostic purposes.
8. Training set sample sizes or ground truth establishment for training an AI model.

To answer your prompt, you would typically need a regulatory submission document for an AI/ML device, which would include detailed statistical analysis plans, clinical study results, and defined performance metrics.

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REVERSE PROSTHESIS (METAL-BACK OR POROUS GLENOID IMPLANT) The ARROW Reverse Shoulder Prosthesis is indicated for patients with severe shoulder arthropathy and a grossly deficient rotator cuff or a previously failed shoulder joint replacement with a grossly deficient rotator cuff. A functional deltoid muscle and adequate glenoid bone stock are necessary to use this device. The humeral stem is intended for cementless application while the glenoid baseplate (metal-back or porous) is intended for cementless application with the addition of bone screws for fixation.

The ARROW® Reverse porous glenoid base is used in total reverse shoulder prosthesis and is designed to articulate with the ARROW® Reverse shoulder system (cleared in K112193). The porous glenoid base is used with bone screws for fixation (cleared in K112193). The ARROW® Reverse porous glenoid is intended to be implanted using the dedicated instrumentation supplied by the manufacturer. This instrument set is common for all the configurations of prosthesis: simple humeral prosthesis, total anatomical prosthesis and reverse prosthesis.

This document is a 510(k) Premarket Notification from the FDA regarding the ARROW® Reverse Porous Glenoid. It is a submission for a Class II medical device (shoulder joint prosthesis) and primarily focuses on demonstrating substantial equivalence to existing predicate devices.

This document describes a medical device (shoulder prosthesis), NOT an AI/ML powered device.

Therefore, most of the requested information about acceptance criteria, study details, expert involvement, and ground truth establishment, which are typical for AI/ML device evaluations, are not applicable here.

Here's a breakdown based on the provided document:

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

Since this is a submission for a physical medical device (shoulder prosthesis) and not an AI/ML powered device, the "acceptance criteria" are related to mechanical and material performance, and "device performance" refers to the results of engineering tests.

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

• Sample Size: The document does not specify the exact sample sizes (e.g., number of prostheses tested) for the ASTM standards or LAL testing. These are typically engineering tests performed on a defined number of device units or material samples per the standard's requirements.
• Data Provenance: The tests were conducted by the manufacturer, Fournitures Hospitalières Industrie, based in France. The data would be "prospective" in the sense that the tests were performed specifically for this 510(k) submission on newly manufactured devices or samples.

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

• Not Applicable. This is a physical device submission. "Ground truth" in the context of AI/ML models (e.g., expert annotation of medical images) is not relevant here. Device performance is assessed through standardized mechanical and biological tests. The "experts" would be the engineers and technicians performing and interpreting these standardized tests.

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

• Not Applicable. As above, adjudication methods common in AI/ML performance evaluation (e.g., for reconciling expert disagreements) are not pertinent to the mechanical testing of a medical implant.

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 not an AI-assisted device, so MRMC studies and human reader improvement with AI assistance are irrelevant to this submission.

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 algorithm.

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

• Not Applicable for AI/ML "ground truth". For a physical device, "ground truth" relates to established engineering principles and the specifications within the ASTM standards. The device is expected to perform in accordance with the established mechanical and material properties defined by these standards.

8. The sample size for the training set:

• Not Applicable. There is no "training set" as this is not an AI/ML device.

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

• Not Applicable. There is no "training set" or "ground truth" establishment in the AI/ML sense.

In summary, this document is a regulatory submission for a traditional implantable medical device, demonstrating its substantial equivalence to previously cleared devices through adherence to established material and mechanical performance standards, rather than through AI/machine learning performance metrics.

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