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APTUS® Wrist Spanning Plates 2.5 are intended for use in forearm fractures.

The subject device includes plates to be applied using a dorsal approach: two (2) plates with an anatomical pre-bent design specifically for the left and right wrist; and an additional plate design appropriate for either the left or right wrist. The plates have an overall length of 196 mm, a maximum width of 10 mm, and a maximum thickness of 3.4 mm tapering to 1.6 mm. The plates are made from titanium allov conforming to ASTM F136. The plates are designed to accommodate appropriately sized bone screws presently marketed as part of the APTUS® System and previously cleared in K103332 (cortical screws) and K051567 (TriLock locking screws). The subject device plates also are compatible with Medartis APTUS® K-Wires previously cleared in K092038.

The provided text describes a medical device, the APTUS® Wrist Spanning Plates 2.5, seeking 510(k) clearance. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than proving novel safety and effectiveness through extensive clinical trials. Therefore, the details requested in your prompt regarding acceptance criteria, study design, and performance metrics are largely absent in the provided document, as they are not typically required for a 510(k) clearance for this type of device.

However, I can extract information related to the equivalent of "acceptance criteria" through the lens of establishing "substantial equivalence" and the "study" that supports it, based on the non-clinical performance data provided.

Here's a breakdown of the information:

1. Table of Acceptance Criteria and Reported Device Performance (as inferred from the 510(k) summary):

For a 510(k) submission, "acceptance criteria" are generally interpreted as demonstrating that the new device performs at least as well as, or equivalently to, the predicate device in relevant non-clinical (and sometimes clinical, though not in this case) tests. The performance is measured against established standards.

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

• The document describes non-clinical performance data, which typically does not involve human patient test sets.
• For mechanical testing, the "sample size" would refer to the number of physical devices tested. This information is not specified in the provided text.
• Data provenance is also not explicitly stated beyond stating that "Non-clinical testing data submitted" was performed. This implies internal company testing or testing by contract research organizations (CROs).

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

• This information is not applicable as the clearance is based on non-clinical performance and not a clinical study requiring expert assessment of patient outcomes or images. The "ground truth" for non-clinical tests is based on adherence to established engineering standards and specifications.

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

• This is not applicable as there was no clinical test set requiring expert adjudication.

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 MRMC study was done. This device is a bone fixation plate, not an AI-powered diagnostic or assistive tool for human readers.

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

• No standalone algorithm performance was done. This device is a physical medical implant, not an algorithm.

7. The type of ground truth used:

• For the non-clinical tests, the "ground truth" is defined by established engineering and material science standards and specifications (e.g., ISO, ASTM, ANSI AAMI standards for sterilization, biocompatibility, shelf life, and mechanical properties).
• For demonstrating substantial equivalence in overall design and indications for use, the "ground truth" is the legally marketed predicate devices (K142906 and K131764).

8. The sample size for the training set:

• This is not applicable. This device is a physical product, not an AI model that requires a training set.

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

• This is not applicable for the same reason mentioned above.

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