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Kerecis® Tendon Protect is indicated for the management and protection of tendon injuries in which there has been no substantial loss of tendon tissue.

Kerecis® Tendon Protect is a medical device made from solid fish skin (North Atlantic Cod) sheets of thickness no less than 0.4 mm. The product is intended to provide a covering around the newly repaired tendon for the management and protection of tendon injuries in which there has been no substantial loss of tissue. The device with natural structure and proteins from fish skin is applied around the newly repaired tendon. The structure of the fish skin provides a supportive environment for new host tissue deposition as part of wound healing while still providing an initial barrier facilitating the sliding of the repaired tendon within the surrounding tissue during tendon use. The biomechanical strength for the tendon itself is provided separately by sutures used to repair the tendon tear and/or by sutures or bone anchors used to attach the tendon tissue to the bone.

The fish skin is fully integrated into the surrounding tissue over time, with corresponding new host tissue deposition. The device is biocompatible, non-crosslinked, bioresorbable, strong, and pliable. Its tensile strength supports fixation by sutures customary for tendon protection surgical procedures. The device is intended for one-time use and supplied sterile in labelled Tyvek® pouch packaging.

The subject device is available in following sizes:

• 3x5 cm size
• 6x9 cm size

Kerecis® Tendon Protect is a standalone, single use medical device made from fish skin that is technologically similar to the predicate device Tendon Wrap Tendon Protector (K053655) (Substantial Equivalence) and identical to the Kerecis® Reconstruct™ (K202430).

The provided text is a 510(k) clearance letter and summary for a medical device called "Tendon Protect." It details the device's characteristics, indications for use, and a summary of the non-clinical performance testing conducted to demonstrate its safety and effectiveness and substantial equivalence to predicate devices. However, it does not contain the specific detailed information typically found in acceptance criteria tables or a comprehensive study report, particularly regarding a multi-reader multi-case (MRMC) study, standalone algorithm performance, or the detailed methodology for ground truth establishment that would be associated with AI/ML-based medical devices.

The document describes a physical medical device (surgical mesh made from fish skin) rather than an AI/ML-based diagnostic or assistive software. Therefore, many of the questions related to AI/ML specific criteria (such as sample size for training set, number of experts for ground truth, adjudication methods, MRMC studies, and standalone algorithm performance) are not applicable to this particular device submission.

Here's a breakdown of the applicable information found in the document:

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

The document mentions that the device "met all the pre-defined acceptance criteria" for various tests, but it does not provide a table detailing the specific numerical or quantitative acceptance criteria and the corresponding reported performance values. It only states that the tests were "conducted and passed successfully according to the test specifications."

2. Sample sizes used for the test set and the data provenance:

• Test Set Sample Size: Not explicitly stated for most tests (e.g., biocompatibility bench tests). For the Tendon GLP Chicken Study, it is a chronic model evaluating early, mid-term, and late time points, comparing the subject device to a control and a negative control. The specific number of animals or tendons tested is not provided.
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies appear to be pre-clinical (bench and animal testing), not human clinical data, and are likely prospective given they are part of a regulatory submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This is not applicable as the device is a physical surgical mesh, not a diagnostic or AI-based device requiring expert interpretation of images or signals for ground truth. Ground truth for the animal study would be based on objective scientific measurements and observations (e.g., histology, biomechanics).

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

This is not applicable for the reasons stated above.

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 is not applicable as the device is a physical surgical mesh, not an AI-assisted diagnostic tool.

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

This is not applicable as the device is a physical surgical mesh, not an AI algorithm.

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

For the animal study:

• Histopathology evaluation
• Macroscopic evaluations
• Tendon biomechanical function assessment
• Overall animal health

For bench testing, ground truth would be established by the physical and mechanical properties of the material itself, measured against predefined specifications.

8. The sample size for the training set:

This is not applicable as the device is a physical surgical mesh, not an AI/ML system requiring a training set.

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

This is not applicable for the reasons stated above.

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