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Rx Indications: Under the supervision of a healthcare professional, Microcyn Antimicrobial Skin and Wound Cleanser is intended for the cleansing, irrigation, moistening, debridement and removal of foreign material and debris from exudating wounds, acute and chronic dermal lesions including stage I-IV pressure ulcers, diabetic ulcers, post-surgical wounds, first- and second-degree burns, abrasions, minor irritations of the skin, diabetic foot ulcers, ingrown toe nails, grafted/donor sites and exit sites. It is also intended for use to moisten and lubricate wound dressings and for use with devices intended to irrigate wounds.

OTC Indications for Use: Microcyn Antimicrobial Skin and Wound Cleanser is intended for OTC use in the management of skin abrasions, lacerations, minor irritations, cuts, and intact skin.

The Microcyn Antimicrobial Skin and Wound Cleanser is a clear hypotonic solution that aids in the mechanical removal of debris and foreign material from the application site. It is also for the management of skin abrasions, lacerations, irritation, cuts, and wounds.

The provided text describes a 510(k) summary for the Microcyn Antimicrobial Skin and Wound Cleanser, which sought to demonstrate substantial equivalence to predicate devices. This type of submission does not typically involve a device that requires performance against specific clinical acceptance criteria in the same way a novel AI algorithm might. Instead, the focus is on showing that the new device is as safe and effective as a legally marketed predicate device.

Therefore, many of the requested details, such as human-in-the-loop studies, AI training/test sets, and expert adjudication, are not applicable to this type of medical device submission.

Here's a breakdown of the information that can be extracted and a clear indication of what is not present:

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

Since this is a substantial equivalence determination for a wound cleanser, the "acceptance criteria" are not defined as specific diagnostic performance metrics (e.g., sensitivity, specificity). Instead, they relate to demonstrating similar technological characteristics, safety, and effectiveness to predicate devices. The "reported device performance" is primarily about meeting various bench and biocompatibility testing standards and showing comparable properties to the predicate devices.

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

• Not Applicable. This is a wound cleanser, not a diagnostic device relying on a "test set" of patient data for performance evaluation in the context of AI. The performance data consists of laboratory bench tests and biocompatibility studies.

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

• Not Applicable. See point 2.

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

• Not Applicable. See point 2.

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:

• Not Applicable. This is not an AI-assisted diagnostic device.

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

• Not Applicable. This is not an AI algorithm.

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

• Not Applicable. Ground truth in the context of AI or complex diagnostic accuracy is not relevant here. The "ground truth" for this device's efficacy and safety relies on established scientific methods for evaluating chemical composition, microbiological effectiveness, physical properties (pH, osmolality), and biocompatibility.

8. The sample size for the training set:

• Not Applicable. This is not an AI algorithm; there is no "training set."

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

• Not Applicable. See point 8.

In summary: The provided document is a 510(k) premarket notification for a wound care product. The "study" demonstrating that the device meets "acceptance criteria" primarily refers to biocompatibility testing and bench testing (e.g., chemical properties, microbiological preservative efficacy, shelf-life testing) to show that the device is safe, performs as intended, and is substantially equivalent to existing predicate devices. It does not involve clinical studies with patient data, AI algorithms, or expert ground truthing as would be seen for diagnostic software.

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