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510(k) Data Aggregation
(30 days)
The OPTETRAK Comprehensive Knee Systems are indicated for use in skeletally mature individuals undergoing primary surgery for total knee replacement due to osteoarthritis, osteonecrosis, theumatoid arthritis and/or post-traumatic degenerative problems. They are also indicated for revious reconstructions where sufficient bone stock and soft tissue integrity are present. In the USA, the OPTETRAK Comprehensive Knee Systems are indicated for cemented use only, except for the OPTETRAK Logic PS and CR Porous Femoral Components, which are indicated for cemented or cementless use.
The OPTETRAK Logic CC Total Knee System is indicated for use in skeletally mature individuals undergoing primary surgery for total knee replacement due to osteoarthritis, osteonecrosis, theumatoid arthritis and/or post-traumatic degenerative problems. They are also indicated for revious reconstructions where sufficient bone stock and soft tissue integrity are present.
The OPTETRAK Logic CC Total Knee System is indicated for cemented use only.
This submission proposes dimensional modifications to features common to all Optetrak Logic tibial inserts, Optetrak Logic trapezoidal tibial trays, and Optetrak Logic Combo tibial trays. These modifications are designed to enhance intraoperative assembly.
This document is a 510(k) premarket notification for a medical device called the "Exactech Optetrak Logic Enhanced Assembly," a knee joint prosthesis. It primarily focuses on demonstrating substantial equivalence to previously cleared devices rather than presenting a study to prove acceptance criteria for an AI device.
Therefore, most of the requested information about acceptance criteria, study design, expert involvement, and ground truth establishment for an AI device cannot be extracted from this document, as it describes a physical medical implant, not an AI system.
However, I can provide the limited information that is present within the document:
1. Table of Acceptance Criteria and Reported Device Performance:
This document describes mechanical testing performed on the device:
| Acceptance Criteria / Test Conducted | Reported Device Performance (Summary) |
|---|---|
| Micromotion testing | Results demonstrate substantial equivalence to cited cleared predicate devices. |
| Shear testing | Results demonstrate substantial equivalence to cited cleared predicate devices. |
Note: The document states "Results of engineering studies referenced in this 510(k) submission demonstrate proposed Optetrak Logic and Optetrak Logic CC devices are substantially equivalent to cited cleared predicate Optetrak Logic devices." It does not provide specific numerical acceptance criteria or detailed performance metrics against those criteria within this summary. It refers to these studies as being "referenced" within the full 510(k) submission.
2. Sample size used for the test set and the data provenance: Not applicable. This document refers to mechanical engineering studies of a physical device, not a test set of data for an AI algorithm.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically understood for AI devices involving expert review is not relevant here. The "ground truth" in this context would likely be engineering specifications and mechanical performance standards, established by engineers.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This is not a human-in-the-loop diagnostic study for an AI device.
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: Not applicable. This document is for a physical medical implant, not an AI diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the mechanical tests, the ground truth would typically be established by engineering standards, material properties, and comparative performance against predicate devices which themselves have established safety and effectiveness.
8. The sample size for the training set: Not applicable. This is not an AI algorithm requiring a training set.
9. How the ground truth for the training set was established: Not applicable. This is not an AI algorithm.
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