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Vivorté Trabexus" is a moldable, self-setting, gradually resorbable, calcium phosphate bone void filler. Vivorté Trabexus" is indicated for use to fill bony voids or defects of the skeletal system (i.e., extremities, pelvis) that may be surgically created or osseous defects created from traumatic injury to the bone and only for bony voids or defects that are not intrinsic to the stability of the bony structure. Vivorté Trabexus™ may be manually applied to the bony defect or applied to the defect through a cannula. Vivorté Trabexus" is resorbed and remodeled by the body as new bone formation occurs during the healing process.

Vivorté Trabexus™ is a moldable, self-setting, gradually resorbable, biocompatible, calcium phosphate bone void filler. The device is provided in kit sizes of 3 cc, 5 cc, and 10 cc, corresponding to the amount of bone void filler produced when the components of the kit are mixed together.

This document is a 510(k) premarket notification for the Vivorté Trabexus™ device. It doesn't contain a detailed clinical study with acceptance criteria and device performance results in the format requested. The document focuses on demonstrating substantial equivalence to a predicate device based on bench testing.

Therefore, many of the requested sections regarding acceptance criteria, study details, ground truth, experts, and human reader performance cannot be fully extracted from this document.

However, I can extract the available information regarding non-clinical testing and the comparison to the predicate device.

Key Findings from the Document:

The Vivorté Trabexus™ is a new version of an existing device (Vivorté BVF™ Lite™). The primary difference is the inclusion of an additional accessory: a delivery cannula. The substantial equivalence is based on the argument that this accessory does not impact the safety and effectiveness of the device.

Here's a summary of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

This document does not provide specific quantitative acceptance criteria or detailed device performance metrics beyond "Pass" for the non-clinical tests.

Note: The document states "Performance testing according to the design verification test methods indicated by the risk analysis was conducted." However, it does not detail these test methods or specific quantitative acceptance criteria. The "Not applicable" for Extrudability suggests that this test might have been relevant for the predicate device but perhaps less so for the new device given the cannula accessory.

2. Sample Size Used for the Test Set and Data Provenance

• Test Set Sample Size: Not specified for any of the non-clinical tests.
• Data Provenance: Not explicitly stated, but these are likely in-house (Vivorté, Inc.) non-clinical bench tests. The country of origin for the data is not mentioned. The tests are retrospective in the sense that they were conducted for this 510(k) submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Not applicable. This document describes non-clinical bench testing, not a clinical study requiring expert ground truth for interpretation.

4. Adjudication Method for the Test Set

• Not applicable. This was non-clinical bench testing, not a study requiring adjudication of expert interpretations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. This was not a clinical study involving human readers or AI.

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

• No. This document does not describe an algorithm or AI.

7. The Type of Ground Truth Used

• For the non-clinical tests, the "ground truth" would be the established scientific and engineering principles and standards for evaluating the properties of medical devices (e.g., biocompatibility standards, packaging integrity standards).

8. The Sample Size for the Training Set

• Not applicable. This document does not describe an AI/ML algorithm or a training set.

9. How the Ground Truth for the Training Set was Established

• Not applicable. This document does not describe an AI/ML algorithm or a training set.

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