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

The Equinoxe™ fracture adapter tray connects to the Equinoxe™ fracture humeral stems via a morse taper and a non-breakaway locking screw using a 5/16-18 thread instead of the primary adapter tray connecting to the primary/revision humeral stems via a spherical taper and a breakaway locking screw using a M6 thread

This document is a 510(k) premarket notification for a medical device called the Exactech® Equinoxe Reverse Shoulder Fracture Humeral Adapter Tray and Fracture Humeral Adapter Tray Locking Screw. The purpose of this notification is to demonstrate that the new device is substantially equivalent to legally marketed predicate devices, meaning it is as safe and effective.

The provided text does not contain a study that proves the device meets specific acceptance criteria in the format requested. Instead, it describes an engineering evaluation conducted to verify the device's performance. The acceptance criteria and "reported device performance" would typically be found within the detailed engineering evaluation report, which is not fully provided here.

However, based on the provided text, I can infer some aspects and highlight what is missing from the request.

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information (Not Available in the Provided Text for the requested items):

The provided text is a summary of a 510(k) submission, which focuses on demonstrating substantial equivalence to a predicate device rather than detailing a clinical study with human subjects, or a standalone algorithm-only performance study. Therefore, most of the requested information for AI/imaging device studies is not applicable or not present in this type of document.

Below is a breakdown of why each point is missing or not applicable in this context:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable / Not Provided: This device is a mechanical implant (shoulder prosthesis components), not an AI algorithm or a diagnostic imaging device. The "test set" for this type of device typically refers to samples or prototypes used in mechanical engineering evaluations (e.g., fatigue testing, tensile testing) rather than a dataset of patient images or clinical outcomes. The document refers to "engineering evaluations" but does not specify the number of samples tested or their provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable / Not Provided: Ground truth, in the context of expert consensus, is typically established for diagnostic devices or AI algorithms where interpretation of data (e.g., images) by human experts is key. For mechanical implants, "ground truth" relates to physical properties and performance measured against engineering standards, not expert interpretation. The "experts" involved would be engineering and materials specialists designing and testing the device, and potentially orthopedic surgeons providing clinical input on requirements, but not in the sense of adjudicating a "test set" as described in the request.

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

• Not Applicable: Adjudication methods like 2+1 or 3+1 are used for resolving discrepancies in expert interpretations (e.g., radiologists' readings). This is not relevant for the engineering evaluation of a mechanical 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: MRMC studies are specific to diagnostic devices, particularly in imaging, to evaluate the performance of human readers, sometimes with AI assistance. This is a mechanical implant; therefore, an MRMC study is not relevant.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not Applicable: This device is a physical implant, not an algorithm.

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

• Engineering Standards / Biomechanical Principles: For this type of device, the "ground truth" for performance would be based on established engineering standards (e.g., ISO or ASTM for orthopaedic implants), biomechanical principles derived from cadaveric studies or in-silico models, and clinical requirements for long-term implant function and durability. The summary states "Engineering evaluations were conducted to verify that the performance of the proposed components would be adequate for anticipated in vivo use." This implies performance was measured against such standards.

8. The sample size for the training set

• Not Applicable: As this is a mechanical implant and not an AI algorithm, there is no "training set" in the conventional sense of machine learning. The design and development of the device would involve iterative design, prototyping, and testing (the "engineering evaluations"), but not a data-driven training process.

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

• Not Applicable: Since there is no training set, this question is not applicable. The design "ground truth" would be established through clinical need assessment, biomechanical analysis, material science principles, and existing predicate device performance.

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