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The Equinoxe® Shoulder Proximal Humerus Fracture Plate System is indicated for Open Reduction Internal Fixation (ORIF) procedures of the proximal humerus. Clinical indications are as follows:

• Fractures, fracture dislocations, osteotomies, and non-unions of the proximal humerus.

The Equinoxe Proximal Humerus Fracture Plate System is for use in the repair of proximal humerus fractures. The system consists of the following components. With the exception of blade locking screws, all components are provided in various sizes.

• Proximal Humerus Fracture Plates
• Locking Screws, Cancellous and Cortical
• Humeral Blades
• Blade Locking Screws
• Compression Screws, Cortical
  Made of 316L Stainless Steel (per ASTM F138-08), all components are supplied nonsterile and must be sterilized in a provided re-usable sterilization container, prior to implantation. Cleaning and Sterilization instructions are provided in the package insert for the Equinoxe® Proximal Humerus Fracture Plate System.

The provided document is a 510(k) Summary for the Exactech® Equinoxe® Proximal Humerus Fracture Plate System. It describes a medical device and its substantial equivalence to predicate devices, rather than a study evaluating a device's performance against acceptance criteria for an AI/CAD system. Therefore, most of the requested information, such as sample sizes, expert qualifications, and ground truth methodologies, is not applicable to this document.

However, I can extract the information related to the device's performance and the "study" (in this context, mechanical and simulated-use tests) that proves it meets acceptance criteria, which are primarily based on equivalence to predicate devices.

Here's the breakdown of what can be extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

For this type of medical device (fracture plate system), "acceptance criteria" are generally established through comparison to legally marketed predicate devices and conformity to recognized industry standards (e.g., ASTM standards for materials and biomechanical performance). "Device performance" is then demonstrated through testing to show it meets or exceeds the performance of these predicates.

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

• Sample size for test set: Not specified in terms of number of plates tested as discreet 'samples'. The "mechanical tests and simulated-use studies" would involve a number of plate configurations tested under various loading conditions, but the exact count isn't given. These are likely in vitro tests.
• Data provenance: The tests were conducted internally by Exactech, Inc. (Gainesville, Florida). The data is presumably prospective in nature, generated specifically for this 510(k) submission. No country of origin for clinical data is mentioned as this is not a clinical study.

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

• Experts and qualifications: Not applicable. For a device like a fracture plate, "ground truth" isn't established by human expert consensus as it would be for an image-based diagnostic AI. Instead, the "truth" or performance is determined by objective physical and mechanical testing against predefined standards and comparative performance with predicate devices.

4. Adjudication method for the test set:

• Adjudication method: Not applicable. This is not a study assessing human reader performance or diagnostic accuracy. Performance is determined by experimental measurements against engineering specifications and comparison with predicate device performance.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• MRMC study: No, an MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic or AI-assisted interpretation tasks, not for the mechanical performance of a surgical implant.

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

• Standalone performance: Not applicable. This device is a physical implant; there is no algorithm involved to perform "standalone" analysis.

7. The type of ground truth used:

• Type of ground truth: The "ground truth" for this device's performance is based on engineering specifications, material science standards (e.g., ASTM F138-08), and the established biomechanical performance of legally marketed predicate devices. The device's components must meet material standards and then demonstrate similar or superior mechanical strength and fatigue resistance compared to the predicate devices under simulated physiological conditions.

8. The sample size for the training set:

• Sample size for training set: Not applicable. There is no "training set" in the context of an AI/ML algorithm. For the physical device, design and development would involve iterative testing, but this isn't reported as a "training set."

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

• Ground truth for training set: Not applicable as there is no training set mentioned in the context of AI/ML. For the design and development of the physical device, ongoing R&D would rely on engineering principles, material science, and testing results against historical data and design requirements to refine the product.

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