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SILVERSEAL® Orthotic Components with X-Static® are used as components on various orthotic devices intended for medical purposes that can be worn as a cervical collar or brace. The component comprises a knitted stockinette which is made of 90% cotton or polyester, and 10% X-Static®, which is 1.5% silver oxide. The component provides the skin with an antimicrobial barrier.

SILVERSEAL® Orthotic Components with X-Static® are made of flexible, non-adherent fabric consisting of a knitted or made or in fabric which is 90% cotton or polyester, and 10% of a continuous nylon fiber substrate with a metallic silver surface containing approximately 1.5% silver oxide.

The Noble Fiber Technologies, Inc. 510(k) submission for the SILVERSEAL® Orthotic Components with X-Static® does not include acceptance criteria or a study that evaluates device performance against specific efficacy endpoints in the same way a diagnostic or therapeutic device might. Instead, this submission focuses on biocompatibility and substantial equivalence to a predicate device.

Here's an breakdown of the relevant information provided:

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

This document does not present quantitative acceptance criteria or a performance table for efficacy. The "performance" assessment is based on biocompatibility and antimicrobial properties, which are discussed qualitatively.

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

The document states that the device was "subjected to standard in vivo biocompatibility" tests, including sensitization, irritation, and acute in vivo blood incompatibility. However, it does not specify the sample size for these tests. It also does not explicitly state the country of origin of the data or whether the tests were prospective or retrospective, although biocompatibility testing is typically prospective. The testing was performed by "North American Science Associates, Inc. (NAMSA)."

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 information is not provided. Biocompatibility testing typically involves laboratory professionals and toxicologists, but no details on "experts" or their qualifications for establishing ground truth are given in this K051256 summary.

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

This information is not provided. Adjudication methods are not typically relevant for standard biocompatibility testing. The assessment of biocompatibility usually relies on established laboratory protocols and interpretation of results against predetermined biological endpoints.

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. This device is a component of an orthotic, and its performance evaluation is based on biocompatibility and antimicrobial properties, not on diagnostic or therapeutic effectiveness requiring human reader-dependent interpretation or AI assistance.

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

This is not applicable. This device is not an algorithm or AI system. Its performance relates to material properties and biological interaction.

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

The ground truth for biocompatibility testing is based on established biological endpoints and toxicological principles, as defined by international standards (ISO 10995, likely a typo for ISO 10993 which is for Biological Evaluation of Medical Devices). This involves evaluating for adverse biological reactions such as irritation, sensitization, and specific toxic effects, usually observed in animal models (in vivo) or in vitro cell cultures.

8. The sample size for the training set:

This is not applicable. This device is not an AI/ML algorithm that requires a "training set."

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

This is not applicable. As mentioned above, there is no training set for this type of device.

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