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The ARROW® Reverse Shoulder long keel and short keel glenoid base is indicated for patients with severe shoulder arthropathy and a grossly deficient rotator cuff or a previously failed shoulder joint replacement with a grossly deficient rotator cuff. A functional deltoid muscle and adequate glenoid bone stock are necessary to use this device. The humeral stem is intended for cemented or cementless application while the metal-back glenoid baseplate is intended for cementless application with the addition of bone screws for fixation.

The ARROW® Reverse Shoulder long keel and short keel glenoid base consist of a metal-back glenoid base, used with bone screws for fixation and assembled with previously cleared glenosphere. These components are used in total reverse prosthesis and are designed to articulate with ARROW® Reverse Shoulder System cleared in K112193.

The bone fixation screws are cleared in K112193.

The ARROW® Reverse Shoulder long keel and short keel glenoid base is intended to be implanted using the dedicated instrumentation supplied by the manufacturer. This instrument set is common for all the configurations of prosthesis (and identical to those for ARROW® anatomical (K093599) and reverse shoulder system (K112193)).

The provided document is a 510(k) premarket notification for a medical device (ARROW® Reverse Shoulder long keel and short keel glenoid base) and focuses on demonstrating substantial equivalence to predicate devices, rather than establishing performance against specific acceptance criteria for a novel device or software. Therefore, much of the requested information regarding acceptance criteria, specific study designs, expert involvement, and ground truth establishment, which are typical for software-as-a-medical-device (SaMD) or diagnostic devices, is not directly applicable or available from this type of regulatory submission.

However, I can extract the information that is present and explain why other aspects are not applicable.

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of explicit acceptance criteria with numerical targets and reported performance values in the way one would typically expect for a diagnostic or AI-driven device. Instead, the "performance" is assessed through a cyclic mechanical protocol to demonstrate substantial equivalence to predicate devices.

2. Sample size used for the test set and the data provenance

The "test set" for this device refers to the physical devices subjected to mechanical testing. The document does not specify the exact sample size (number of devices or components tested) used for the cyclic mechanical protocol.

Regarding data provenance, the testing was performed by the manufacturer, Fournitures Hospitalières Industrie, in France. The document does not specify if different batches or manufacturing runs were tested, nor does it refer to "countries of origin" for data in the context of clinical populations, as this is a mechanical testing scenario for an orthopedic implant.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This question is not applicable to this type of device and study. For a mechanical device like a shoulder implant component, "ground truth" is not established by human experts in the diagnostic sense. The "ground truth" for mechanical performance is typically defined by engineering specifications, material properties, and validated testing methods (e.g., ISO standards, ASTM standards) that simulate in-vivo conditions. The evaluation of whether the mechanical tests were performed correctly and meet the implicit equivalence criteria would be done by engineers and regulatory reviewers, not medical experts establishing a diagnostic ground truth.

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

This question is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies or for establishing ground truth in diagnostic imaging cases, especially when there's inter-reader variability. For mechanical testing of a medical device, the results are typically quantitative and objective measurements (e.g., strength, fatigue life). The "adjudication" (if one could even call it that) of the test results themselves would be against predefined engineering acceptance criteria, potentially verified by internal quality control or external testing labs, not by a panel of experts.

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

This question is not applicable. An MRMC study is relevant for evaluating the performance of diagnostic devices or AI algorithms that assist human readers (e.g., radiologists). The ARROW® Reverse Shoulder long keel and short keel glenoid base is an orthopedic implant (a physical device), not a diagnostic tool or an AI-assisted system.

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

This question is not applicable. This device is a physical implant, not an algorithm or software. Therefore, there is no "standalone algorithm only" performance to evaluate.

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

The document does not describe "ground truth" in terms of clinical or diagnostic data. For the mechanical testing, the "ground truth" is effectively the performance of the predicate devices and generally accepted mechanical engineering principles and standards for orthopedic implants under simulated physiological loads. The goal was to show that the new device's mechanical performance was "substantially equivalent" to these established benchmarks.

8. The sample size for the training set

This question is not applicable. As this is a physical medical device (an implant), there is no "training set" in the context of an AI algorithm or a statistical model derived from a dataset.

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

This question is not applicable (see response to #8).

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