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The Equinoxe Reverse Shoulder System is indicated for use in skeletally mature individuals with degenerative diseases of the glenohumeral joint and a grossly deficient, irreparable rotator cuff. The Equinoxe Reverse Shoulder is also indicated for a failed glenohumeral joint replacement with loss of rotator cuff function resulting in superior migration of the humeral head.

The Exactech Equinoxe Reverse Shoulder Glenospheres and Extended Locking Cap are for use in reverse total shoulder arthroplasty. The modifications proposed by this submission describe minor geometry changes to the predicate Exactech Equinoxe Glenospheres and Locking Cap; these geometry modifications are the entire basis for the proposed devices.

The provided text describes a 510(k) premarket notification for a medical device, the Exactech® Equinoxe® Reverse Shoulder Glenospheres. However, the document does not contain information related to an AI/ML-driven device or diagnostic software. Instead, it details the engineering and material testing performed for a physical medical implant.

Therefore, I cannot fulfill your request to describe acceptance criteria and study proving device performance for an AI/ML device based on the provided text, as the document does not discuss such a device.

To provide the requested information, the input text would need to describe a study evaluating the performance of an AI/ML algorithm or software for a diagnostic or predictive task.

Here's why the provided text is not relevant to your request:

• Device Type: The device described is a shoulder joint prosthesis (implant), not an AI/ML diagnostic or assistive tool.
• Testing: The non-clinical testing listed (ASTM F2028, ASTM F1378, pyrogen testing) are standard mechanical, materials, and sterility tests for physical implants, not performance evaluations for algorithms (e.g., sensitivity, specificity, AUC).
• Ground Truth: The concept of "ground truth" (expert consensus, pathology, outcomes data) is typically for validating diagnostic accuracy, which is not applicable to a physical implant in the same way.
• Human Readers/Experts: The document does not mention human readers, experts establishing ground truth for image interpretation, or MRMC studies, as these are relevant to evaluating diagnostic image analysis.
• Training/Test Sets: There is no mention of data sets for training or testing an algorithm.

If you can provide a different document that describes an AI/ML medical device, I would be happy to analyze it according to your specific criteria.

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