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The APR-T Revision Hip Stem is intended for prosthetic replacement of the proximal portion of the femur during hip arthroplasty. This hip stem can be used for total hip replacements (i.e., replacements where both the femur and acetabulum are replaced) or for hemi-arthroplasties where the hip stem-head assembly articulates directly with wellpreserved articular cartilage. For this indication, the stem must be paired with one of the following Sulzer Orthopedics endoprosthesis: the Unipolar with 12/14 Taper, cleared for use via 510(k)s K833403 and K934159, or the Bipolar component which was cleared for use via 510(k)s K833404 and K873815 and is indicated for use with a CoCr modular femoral head. Specific diagnostic indications include: 1. Patient conditions of inflammatory degenerative joint disease (e.g., theumatoid arthritis) and noninflammatory degenerative joint disease (e.g., osteoarthritis, avascular necrosis); 2. Those patients with failed previous surgery where pain, deformity, or dysfunction persist; and, 3. Revision of previously failed hip arthroplasty. The APR-T Revision Hip Stern is intended for use with or without bone cement.

The APR-T Revision Hip Stem is part of a family of femoral replacement components which are used during primary and revision hip arthroplasties. Its proximal design features an asymmetric wedge and circumferential CSTi ™ porous coating. In addition, a porouscoated medial collar helps achieve improved proximal fixation. The stem's anatomic design follows the natural curve of the diaphyseal canal for better fit, and features a coronal slot at the distal end to reduce stiffness in the larger sizes.

This document is a 510(k) summary for the APR-T® Revision Hip Stem, a medical device for hip replacement. It does not contain any information about acceptance criteria or a study proving the device meets those criteria in the context of an AI/ML device.

The document discusses substantial equivalence to predicate devices, which is a regulatory pathway for demonstrating safety and effectiveness for certain medical devices, but it does not involve performance metrics or studies in the way you've described for an AI/ML device.

Therefore, I cannot extract the requested information from the provided text.

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