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The EVOS Small Fragment Plating System is indicated for adult and pediatric patients with osteopenic bone. It is indicated for fixation of small and long bone fractures, including, but not limited to, those of the tibia, fibula, femur, humerus, ulna, radius, pelvis, acetabulum, metacarpals, metatarsals, and clavicle.

Subject of this premarket notification are line additions to the EVOS Small Fragment Upper Extremity Plating System. The line additions are design modifications of existing plates cleared in K173293 and include changes to the shape and number of holes of the subject plates. When compared against the existing EVOS Small Fragment Plates already cleared for market, the subject plates use the same hole features and are designed to work with the same bone screws.

The subject EVOS Small Fragment Upper Extremity plates are intended to be used with existing Smith & Nephew implants and instruments that have been previously cleared for market for use with the EVOS Small Fragment Plating System.

This is a 510(k) premarket notification for a medical device, specifically EVOS Small Fragment Upper Extremity Plates Line Additions. This type of submission generally focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving efficacy or a specific level of performance through a clinical study with detailed acceptance criteria and expert reviews in the same way an AI/ML device might.

Therefore, the requested information regarding acceptance criteria, study details, expert qualifications, adjudication, MRMC studies, standalone performance, and ground truth for training/testing sets is not applicable to this type of submission. The FDA 510(k) process for this device relies on pre-clinical mechanical testing and comparison to a predicate device to establish substantial equivalence.

Here's how to interpret the provided document in the context of your request:

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

• Acceptance Criteria: For this type of orthopedic implant modification, the "acceptance criteria" are implied by demonstrating substantial equivalence to the predicate device. This typically involves showing that the new device performs at least as well as, or equivalently to, the predicate device in relevant mechanical tests, and that the modifications do not introduce new safety or effectiveness concerns. The criterion is that the "minor modifications to the shape of the plate and number of holes are not expected to impact device safety or effectiveness."
• Reported Device Performance:
  • Financial element analysis (FEA) was conducted to "evaluate the peak stress of potential design modifications to the subject plates." While no specific numerical performance metrics or thresholds are provided in this summary, the conclusion states that the "device comparisons described in this premarket notification demonstrated that the proposed devices are substantially equivalent to legally marketed predicates with respect to intended use, indications, and performance characteristics."

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• N/A. No human or animal test subjects were used. The testing was pre-clinical (FEA on plate designs).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• N/A. No expert ground truth establishment for a test set is mentioned, as this was a pre-clinical, mechanical assessment of device modifications.

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

• N/A. Not applicable, as there was no 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

• N/A. This device is a passive orthopedic implant, not an AI-assisted diagnostic tool.

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

• N/A. This device is a passive orthopedic implant, not an algorithm.

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

• The "ground truth" here is implied by mechanical engineering principles and analysis (Finite Element Analysis) for stress distribution, which is compared to the expectations based on the predicate device.

8. The sample size for the training set

• N/A. There is no "training set" in the context of an orthopedic implant modification. FEA involves modeling the device, not training a machine learning algorithm.

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

• N/A. Not applicable, as there is no training set mentioned or implied.

In summary, this 510(k) submission relies on pre-clinical mechanical testing (Finite Element Analysis) to demonstrate substantial equivalence of minor design modifications to an existing orthopedic implant line. The framework for evaluating AI/ML devices with clinical studies, expert consensus, and ground truth establishment does not apply here.

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