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The NEO CR Knee System components are indicated for use in skeletally mature individuals, with severe knee pain and disability, with an intact posterior cruciate ligament, undergoing surgery for total knee replacement due to:

• Osteoarthritis, rheumatoid arthritis, post-traumatic arthritis, moderate deformities and femoral condyle osteonecrosis.
• Failed osteotomies, failed partial knee replacement, or failed total knee replacement whose age, weight and activity level are compatible with an adequate long-term result.
• Post-traumatic loss of joint configuration, particularly when there is patellofemoral erosion, dysfunction or prior patellectomy.
• Moderate valgus, varus, or flexion deformities.
  Neo CR Knee System components are indicated for use only with cement and are single use devices.

The NEO CR Knee System includes components designed for total knee replacement. The system includes femoral components, tibial trays, patellar components and surgical instrumentation. The Neo CR Knee System femoral component, when used with the Neo CR articular surfaces, is designed to achieve flexion at high angles and provide a clinical ROM up to 150 degrees.

The provided text describes a 510(k) summary for the NEO CR Knee System, a total knee replacement device. It establishes substantial equivalence to predicate devices based on design and performance testing. However, the document does not contain the specific information required to answer your questions regarding acceptance criteria and a study proving the device meets those criteria in the context of AI device performance.

Specifically, the document focuses on regulatory clearance for a physical medical device (a knee implant) and not an AI medical device. The criteria listed are for the mechanical and material performance of the knee implant itself, and the "performance testing" mentioned refers to engineering tests, not studies of AI algorithm efficacy or diagnostic accuracy.

Therefore, I cannot provide the requested information from the given text.

Here's why the required information is missing:

• Acceptance Criteria for AI/Performance: The document discusses performance testing for the knee implant's mechanical properties (fatigue strength, locking mechanism, range of motion, contact stress), not diagnostic accuracy, sensitivity, specificity, or other metrics typically used for AI device acceptance.
• Study Proving Acceptance Criteria: The document mentions "performance testing" was done, but it does not detail specific studies, sample sizes, ground truth establishment, or expert evaluation methods relevant to AI performance.
• Sample Size (Test Set/Training Set) and Data Provenance: This information is not present as the "device" in question is a physical implant, not an AI algorithm.
• Number of Experts/Qualifications/Adjudication Method: These are relevant for establishing ground truth in AI diagnostic studies, which is not applicable here.
• MRMC Comparative Effectiveness Study: Such studies are conducted to evaluate the human-AI interaction or impact of AI assistance on human readers. This is not mentioned.
• Standalone Performance: This refers to the AI algorithm's performance without human interaction. Not applicable here.
• Type of Ground Truth: For AI, this would be pathology, expert consensus on images, clinical outcomes, etc. For a mechanical implant, ground truth relates to engineering specifications and physical measurements.
• Ground Truth for Training Set: This is specific to AI model training, which is not relevant to a physical knee implant.

In summary, the provided 510(k) summary is for a traditional medical device (knee implant) and thus does not contain the details pertaining to acceptance criteria and studies for an AI-powered medical device.

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