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510(k) Data Aggregation
(214 days)
The Arthrex Univers Apex OptiFit Humeral Stem is indicated in replacement when conditions include severe pain or significant disability resulting from degenerative, theumatic disease, or injury of the glenohumeral joint; nonunion humeral head fractures of long duration; irreducible 2- and 4- part proximal humeral fractures; of the humeral head; or other difficult clinical management problems where arthrodesis or re-sectional arthroplasty is not acceptable.
The glenoid components are designed fixation in the joint and must only be used with an appropriate bone cement.
The proposed Univers Apex OptiFit Humeral Stem is the humeral stem component of a shoulder prosthesis system. It consists of a stem, a trunion, an inclination block, pins, and screws. All the components are comprised of titanium with a titanium plasma spray (TPS) coating.
The provided text describes the regulatory clearance for a medical device called "Arthrex Univers Apex OptiFit Humeral Stem." It focuses on demonstrating substantial equivalence to a predicate device rather than outlining detailed acceptance criteria and performance data for a novel artificial intelligence (AI) or machine learning (ML) device.
Therefore, the document does not contain the information requested regarding acceptance criteria and a study proving device performance in the context of AI/ML. The performance data mentioned refers to:
- Yield strength testing on samples with and without titanium plasma spray coating, with the acceptance criteria being "met for all samples." This is a material property test, not a performance study for an AI/ML diagnostic or assistive device.
- Computational electromagnetic simulation testing to assess RF heating in bone tissue, demonstrating the device is "MR Conditional." This relates to MRI compatibility, not a diagnostic or therapeutic performance study.
In summary, this document is a 510(k) premarket notification for a traditional medical device (humeral stem), not an AI/ML device. As such, it does not provide the information requested about AI/ML device acceptance criteria, performance studies, sample sizes, expert involvement, or ground truth establishment.
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