Search Results

The Equinoxe Reverse Shoulder System is indicated for use in skeletally mature individuals with degenerative diseases of the glenohumeral joint and a grossly deficient, irreparable rotator cuff. The Equinoxe Reverse Shoulder is also indicated for a failed glenohumeral joint replacement with loss of rotator cuff function resulting in superior migration of the humeral head.

The proposed Exactech Equinoxe Reverse Shoulder 46x21mm Glenosphere represents a modification of the predicate Exactech Equinoxe Reverse Shoulder 46x25mm Glenosphere cleared in K063569. Both the predicate and proposed devices have the same intended use, general design features and basic fundamental scientific technology. The only difference between the predicate and the proposed device are the following dimensional modifications:

• 1. Reduced Lateral Offset The proposed glenosphere has a lateral offset of 21mm, which is 4mm shorter than the predicate 46x25mm glenosphere.
     These modifications are proposed to provide another glenosphere option to the existing glenospheres cleared in K063569.

This document discusses a 510(k) premarket notification for the "Exactech® Equinoxe® Reverse Shoulder 46x21mm Glenosphere." This is a medical device, specifically a component of a shoulder prosthesis. The document is a letter from the FDA to Exactech, Inc., indicating that the device has been found substantially equivalent to a legally marketed predicate device.

The "device" in question is not an AI/ML powered device, but a physical medical implant. Therefore, most of the requested information regarding AI/ML study design, such as sample sizes for test/training sets, ground truth establishment by experts, adjudication methods, or MRMC studies, is not applicable. The provided text describes engineering tests performed to demonstrate substantial equivalence for this physical product.

Here's an analysis based on the provided text, addressing the relevant sections of your request:

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

Since this is a physical medical device and not an AI/ML algorithm, the "acceptance criteria" are related to mechanical performance and the "reported device performance" are the results of engineering analyses demonstrating equivalence to a predicate device.

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

This question is not applicable as the submission is for a physical medical device. The "test set" here refers to the actual physical devices or components tested in engineering analyses, not a dataset for an AI/ML model. The document does not specify the number of physical components tested in the engineering analyses. Data provenance in this context would refer to the testing facility and procedures, which are not detailed.

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).

This question is not applicable. "Ground truth" in the context of physical device testing would refer to established engineering standards and methodologies, not expert consensus on medical images or patient outcomes. The engineering analyses are likely performed by qualified engineers following established protocols.

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

This question is not applicable. Adjudication methods like 2+1 are used for resolving disagreements among human reviewers of cases, typically in clinical studies or for establishing ground truth for AI/ML. Engineering tests typically follow standardized protocols, and results are measured objectively, not through 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.

This question is not applicable. An MRMC study is relevant for evaluating the clinical utility of an AI/ML-powered diagnostic or assistive tool. This device is a physical shoulder implant, and no AI component is described.

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

This question is not applicable. The device is a physical implant, not an algorithm.

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

This question is not applicable for a physical device in the AI/ML sense. The "ground truth" for the engineering tests would be established engineering principles, material science properties, and established benchmarks for mechanical performance of similar medical implants.

8. The sample size for the training set.

This question is not applicable. There is no AI/ML model being trained for this physical device.

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

This question is not applicable. There is no AI/ML model being trained for this physical device.

Summary of what can be gleaned about the "study" (engineering analyses) for the device:

• Device: Exactech® Equinoxe® Reverse Shoulder 46x21mm Glenosphere (a physical shoulder implant component).
• Purpose of "Study": To demonstrate substantial equivalence of the new 46x21mm glenosphere to a predicate 46x25mm glenosphere, primarily due to a dimensional modification (reduced lateral offset).
• Methodology: "Engineering analyses" were conducted.
  • Glenoid Loosening and Cyclic Fatigue Testing
  • Analysis Of Deltoid Abductor Moment Arms
  • Range of Motion Analysis
• Conclusion: The engineering studies demonstrated substantial equivalence to the predicate device.
• Data Provenance: Not specified in terms of country or retrospective/prospective, but implies laboratory-based engineering testing.

In essence, the document details the regulatory approval process for a physical medical device based on engineering tests, not an AI/ML algorithm or software.

Ask a specific question about this device