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The Exactech Optetrak® Unicondylar Knee System is intended for partial replacement of the medial or lateral articulating surface of the knee joint. The system is indicated for primary surgery in skeletally mature patients with one or more of the following clinical conditions:

• . Non-inflammatory osteoarthritis, osteonecrosis and/or traumatic arthritis
• 트 Functional deformity
• Tibial condyle or plateau fractures that are not manageable by other techniques
• I Traumatic bone and/or cartilage lesions
  All components are intended for cemented use only.

The Exactech Optetrak® Unicondylar Knee system is comprised of six sizes of symmetric femoral components and six sizes of asymmetric (right and left side-specific) all-poly tibial components. These components articulate together and are used to replace a portion of the human knee joint that has been debilitated by injury or disease. Specifically, these components are used to replace the damaged biological articular geometry on the medial or lateral aspects of both right and left knees.

This 510(k) summary describes a traditional medical device (knee prosthesis), not an AI/ML-driven device. As such, the requested information pertaining to AI/ML device studies (such as sample size for test sets and training sets, ground truth establishment, expert qualifications, adjudication methods, and MRMC studies) is not present in this document.

However, I can extract information related to the performance testing that was conducted for this device.

A table of acceptance criteria and reported device performance:

Here's an analysis of the study information based on the provided text, highlighting what is missing or not applicable due to the nature of the device:

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

   • This document describes "Functional testing and engineering analysis" for a knee prosthesis. This type of testing typically involves mechanical bench testing, such as fatigue, wear, and strength tests, rather than clinical data from a "test set" as understood for AI/ML performance evaluation.
   • Therefore, information on sample size (in terms of patient data) and data provenance (country, retrospective/prospective) is not applicable or provided in this context.

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

   • For a traditional medical device like a knee implant, "ground truth" is typically established through engineering standards, mechanical testing protocols, and clinical outcomes evidence from predicate devices. There isn't a "ground truth" derived from expert consensus on images or clinical assessments in the same way as for an AI/ML diagnostic device.
   • Therefore, this information is not applicable or provided.

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

   • As described and explained above, this concept related to expert review and consensus on clinical data is not applicable to the type of performance testing reported for this device.

4. 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:

   • This is a traditional medical device (knee implant), not an AI/ML-driven device. Therefore, an MRMC study and analysis of AI assistance effect size is not applicable and was not performed.

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

   • This is a physical medical device, not an algorithm. Therefore, "standalone performance" in the context of an algorithm is not applicable.

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

   • For this device, "ground truth" for performance is primarily based on:
     • Engineering and Material Standards: Compliance with ASTM standards (e.g., ASTM F-75 for cobalt-chromium alloy, ASTM-F648 for UHMWPE).
     • Functional Testing: Mechanical tests
     • Performance of Predicate Devices: The established clinical history and performance of legally marketed predicate devices (Zimmer MG, Link Endo-Modell, DePuy Preservation) serve as a benchmark for substantial equivalence. The "intended use" and "performance characteristics" of the new device are compared to these.

7. The sample size for the training set:

   • This is a traditional medical device, not an AI/ML device that requires a "training set" of data. Therefore, this information is not applicable.

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

   • As there is no "training set" for this type of device, this information is not applicable.

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