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Total hip arthroplasty is intended to provide increased patient mobility and reduce pain by replacing the damaged hip joint articulation in patients where is evidence of sufficient sound bone to seat and support the components. Total hip replacement is indicated in the following conditions:

• A severely painful and/or disabled joint from osteoarthritis, traumatic arthritis, rheumatoid arthritis, or congenital hip dysplasia.
• Avascular necrosis of the femoral head.
• Acute traumatic fracture of the femoral head or neck.
• Failed previous hip surgery including joint reconstruction, internal fixation, arthrodesis, hemiarthroplasty, surface replacement arthroplasty, or total hip replacement.
• Certain cases of ankylosis.
  The DePuy® C-Stem AMT Hip Stem is indicated for cemented use only.

The C-Stem AMT hip is a collarless, tapered, press-fit femoral stem. It is manufactured from wrought stainless steel (Ortron 90° conforming to ISO 5832-9) and is polished overall. The stem is offered in 7 sizes, with each body size having either a standard or high offset. It may be used with commercially available modular femoral heads, either metal or ceramic, to form the femoral component of a total hip prosthesis. Accessory items include previously cleared cement restrictors and centralizers.

The provided text is a 510(k) summary for the DePuy® C-Stem AMT Hip Prosthesis, which describes the device and claims substantial equivalence to previously cleared devices. It does not contain information about acceptance criteria, device performance studies, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, or training set details as typically found for an AI/ML device submission.

As this is a 510(k) for a traditional medical device (a hip prosthesis), not an AI/ML device, the detailed questions about acceptance criteria and study design for an AI/ML model are not addressed in this document. The "study" mentioned here refers to the demonstration of substantial equivalence to predicate devices, primarily through comparison of materials, intended use, and design principles, rather than performance metrics typically associated with AI/ML evaluation.

Therefore, most of the requested information cannot be extracted from the provided text.

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