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The APTUS® 2.0 Radial Head System is intended for use in proximal radial fractures and osteotomies.

The APTUS® 2.0 Radial Head System consists of small titanium fixation plates, conventional screws and locking screws. The system is intended to be used for internal fixation of small bones.

This is a 510(k) premarket notification for a medical device called the "APTUS® 2.0 Radial Head System." A 510(k) submission generally focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than conducting a full clinical study to prove novel device performance against acceptance criteria. Therefore, the information typically requested in your prompt regarding acceptance criteria, study details, and performance metrics (like sensitivity, specificity, or reader improvement with AI) is not explicitly present in a standard 510(k) summary for a device like a bone fixation system.

However, I can extract and infer some contextual information based on the provided text, particularly concerning the device's equivalence to predicate devices, which serves as a proxy for "meeting acceptance criteria" in the context of a 510(k).

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

Since this is a 510(k) for a bone fixation system, the "acceptance criteria" revolve around demonstrating substantial equivalence to existing, legally marketed predicate devices. The performance is assessed by comparing key attributes of the new device to those of the predicate.

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

• Sample Size for Test Set: Not applicable in the context of a 510(k) substantial equivalence submission for this type of device. There isn't a "test set" of patients or images used to evaluate its diagnostic or predictive performance in the way described for AI/software devices. The evaluation is primarily based on a comparison of device characteristics.
• Data Provenance: Not applicable. The "data" here refers to the specifications and materials of the device and the predicate device, not clinical data from patients.

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

• Not applicable. There is no "ground truth" established by experts for a test set in a 510(k) for a bone fixation system. The assessment is a regulatory review comparing the physical and functional aspects of the device to predicates.

4. Adjudication method for the test set:

• Not applicable. No test set requiring adjudication in this context.

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 orthopedic implant (plate, screws), not an AI/software device. Therefore, MRMC studies and AI assistance metrics are not relevant.

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

• No. This is a physical orthopedic implant, not an algorithm or software.

7. The type of ground truth used:

• Not applicable in the typical sense of clinical ground truth (e.g., pathology, outcomes). The "ground truth" for a 510(k) in this context is the established safety and effectiveness of the predicate devices to which the new device is compared. The FDA has already determined these predicate devices to be safe and effective.

8. The sample size for the training set:

• Not applicable. No "training set" is used for a bone fixation system in a 510(k) submission.

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

• Not applicable. No "training set" or corresponding ground truth establishment in this context.

In summary:

The provided document is a 510(k) summary for a physical medical device (bone fixation system). The "acceptance criteria" are implicitly met by demonstrating substantial equivalence to already approved predicate devices across several key characteristics (intended use, operating principle, design, materials, manufacturing processes). This type of submission relies on comparing the device's specifications and characteristics to those of legally marketed devices, rather than conducting new clinical performance studies that define specific acceptance thresholds for metrics like sensitivity or specificity.

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