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The Arthrex Compression FT Screws is intended for fixation of small bone fragments, such as apical fragments, osteochondral fragments and cancellous fragments. Specific applications include the following:

• Osteochondral fragments (talar vault, femoral condyle)
• apical fragments (radial head, patellar rim, navicular, metacarpal/metatarsal)
• cancellous fragments (talus)
• Carpal, metacarpal, and small hand bone
• tarsal and metatarsals
• phalanges
• Intra-articular fractures
• ankle
• proximal and distal humerus
• proximal and distal radius
• proximal and distal ulna
• osteochondral fixation and fractures
• Osteochondritis Dissecans
• Fixation of fractures and osteotomies about the knee
• Oblique fractures of the fibula
• Reconstructive surgeries of the foot
• malleolar fixation

The Arthrex Compression FT Screws are a family of screws designed to provide fixation of fractures, osteotomies and arthrodesis. These titanium screws are cannulated with a tapering head. The screws will be offered in three diameters, 2.8mm, 3.7mm and 4.1mm, and will range in length from 8mm to 50mm.

The provided document is a 510(k) summary for a medical device, the Arthrex Compression FT Screws. However, it does not describe acceptance criteria or a study proving the device meets those criteria in the context of a diagnostic AI/machine learning device.

Instead, this document focuses on demonstrating substantial equivalence to predicate devices for a physical medical screw used for bone fixation. The "study" mentioned is mechanical testing (insertion, pull-out, and compression) to show that the physical properties of the proposed screws are comparable to predicate devices. This is a common requirement for Class II medical devices seeking 510(k) clearance, where safety and effectiveness are established by showing similarity to currently marketed devices.

Therefore, I cannot provide the requested information regarding acceptance criteria and study details as they would apply to an AI/machine learning diagnostic device (e.g., performance metrics like sensitivity, specificity, AUC, human reader improvement, ground truth establishment) because this document is about a different type of medical device entirely, a bone fixation screw, and its clearance process does not involve AI performance evaluation.

The categories you requested are relevant for AI/ML device evaluations. The information present in the document is about mechanical testing and regulatory classification of a physical orthopedic implant.

If you have a document detailing a study for an AI/machine learning diagnostic device, please provide that, and I would be happy to describe its acceptance criteria and study details.

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