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The Delta Xtend Shoulder Prosthesis is indicated for use in treatment of a grossly deficient rotator cuff joint with:

• . severe arthropathy and/or;
• a previously failed joint replacement and/or: ●
• fracture-dislocations of the proximal humerus where the articular surface is severely . comminuted, separated from its blood supply or where the surgeon's experience indicates that alternative methods of treatment are unsatisfactory

The patient's joint must be anatomically and structurally suited to receive the selected implant(s), and a functional deltoid muscle is necessary to use the device.

Delta Xtend hemi-shoulder replacement is also indicated for hemi-arthroplasty if the glenoid is fractured intraoperatively or for the revision of a previously failed Delta Xtend Reverse Shoulder.

The metaglene component is HA coated and is intended for cementless use with the addition of screws for fixation.

The modular humeral stem and humeral epiphysis components are HA coated and intended for cementless use.

All other metallic components are intended for cemented use only.

The DePuy Delta Xtend™ Reverse Shoulder System is a total shoulder prosthesis that consists of monobloc and modular humeral stems, humeral cup, humeral head, humeral spacer, glenosphere, metaglene and metaglene screws.

This document is a 510(k) Substantial Equivalence Determination Letter from the FDA for the DePuy Delta XTend™ Reverse Shoulder System. It is a regulatory document and does not contain information about the acceptance criteria or a study proving the device meets acceptance criteria in the manner typically understood for software or AI/ML devices.

The information provided pertains to the substantial equivalence of a medical device (shoulder prosthesis), not a software or AI/ML product. The "acceptance criteria" discussed are related to demonstrating that the new device is as safe and effective as a legally marketed predicate device, primarily through non-clinical testing and comparison of technological characteristics.

Therefore, many of the requested fields (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, ground truth types, training set sample size) are not applicable to the information presented in this document.

However, I can extract the relevant information from the document as it would apply to a physical medical device submission for substantial equivalence:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a typical "acceptance criteria" table with numerical performance metrics as expected for software. Instead, the acceptance criteria for a physical device like this revolve around demonstrating equivalence in design, materials, intended use, and performance to a predicate device.

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

• Sample Size: Not applicable. The "test set" in this context refers to non-clinical testing and comparison of specifications, not a dataset of patient images or outcomes for an algorithm. The document mentions a "stack analysis" for the metaglene devices, implying detailed engineering comparison of physical components.
• Data Provenance: Not applicable. The data is derived from the design specifications and non-clinical testing of the physical device components.

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

• Not applicable. Ground truth, in the context of AI/ML, refers to validated labels for a dataset. For a physical device, the "truth" is established through engineering design, material science, and mechanical testing against recognized standards. The "stack analysis" would likely involve qualified engineers or designers.

4. Adjudication method for the test set:

• Not applicable. There is no "adjudication" in the sense of expert consensus on interpretations for a dataset. The "adjudication" for substantial equivalence is performed by the FDA based on the manufacturer's submission and relevant regulations and guidance.

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:

• No. This is a physical medical device (shoulder prosthesis), not an AI/ML product. Therefore, MRMC studies are not applicable.

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

• No. This is a physical medical device, not an algorithm.

7. The type of ground truth used:

• Not applicable in the AI/ML context. For this medical device, the "ground truth" for its safety and effectiveness is established through adherence to engineering design principles, material standards, biocompatibility testing, and mechanical performance testing (e.g., fatigue, wear) to demonstrate its equivalence to already approved predicate devices. The document explicitly states "No non-clinical testing was required to demonstrate substantial equivalence" and "No clinical tests were conducted to demonstrate substantial equivalence," implying that the comparison of technological characteristics and design analysis were sufficient.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML product, so there is no training set.

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

• Not applicable.

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