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Curaline Polyurethane Foam Dressings are intended for the management of partial and full thickness wounds; pressure ulcers (Stage I-IV); diabetic ulcers; acute and chronic venous stasis ulcers; arterial ulcers; skin grafts, donor and recipient sites; burns (1" and 2nd degree); skin tears and avulsions; abrasions; tube, catheter, and IV sites; dermatologic disorders: under compression bandages and wraps; traumatic wounds; acute and chronic wounds: and minimal, moderate, and heavily exuding wounds.

The Curaline Polyurethane Foam Dressing is composed of a hydrophilic polyurethane matrix backed with a semipermeable polyurethane film which limits oxygen and moisture vapor permeability and is a barrier to liquids. The dressing contains a cleanser (F68 surfactant), a moisturizer (glycerin), and an absorbing agent (superabsorbent polymer), all in the polyurethane matrix. Both F68 and glycerin are soluble in wound fluid or skin moisture. The superabsorbent polymer contained in the dressing draws and absorbs moisture from wound fluid.

The provided text is a 510(k) summary for the Curaline Polyurethane Foam Dressing. It describes the device, its intended use, and claims substantial equivalency to legally marketed predicate devices. The document details studies conducted to prove the device's safety through biocompatibility tests. However, it does not contain the type of AI-specific acceptance criteria, performance data, or study designs (e.g., sample sizes for test/training sets, expert qualifications, MRMC studies) that your request outlines.

Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor details about sample sizes, expert ground truth establishment, adjudication methods, MRMC studies, or standalone algorithm performance, as these items are not present in the provided text.

The closest relevant information from the document is related to the biocompatibility studies, which are a type of acceptance criteria for medical devices, albeit not AI-specific performance criteria.

Here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance (Biocompatibility)

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

• Sample Size for Test Set: Not specified for biocompatibility studies beyond "New Zealand White rabbits" for skin irritation.
• Data Provenance: Not explicitly stated, but these are in vitro and animal safety studies. Country of origin is not mentioned.

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)

• Not applicable/Not specified. Biocompatibility tests rely on standardized laboratory protocols and observations rather than expert human interpretation of complex data for ground truth.

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

• Not applicable/Not specified. As above, these are lab tests with defined endpoints, not subjective human assessments requiring 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

• No. This is a medical dressing, not an AI diagnostic or assistive device.

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

• No. This is a medical dressing, not an algorithm.

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

• For biocompatibility: Standardized assay results (e.g., cell viability for cytotoxicity, visual assessment of skin reactions for irritation/sensitization) in accordance with ISO standards.

8. The sample size for the training set

• Not applicable. This is not an AI device.

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

• Not applicable. This is not an AI device.

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The Acticoat® Moisture Control dressing, an addition to the Acticoat® Dressing line of products is intended as an absorbent dressing which provides an effective barrier to bacterial penetration. Acticoat® Moisture Control Dressing is indicated for use in light to moderately exuding partial and full thickness wounds including decubitus ulcers, diabetic ulcers, 1st and 2nd degree burns, and donor sites. Acticoat® Moisture control may be used over debrided and partial thickness wounds.

The absorbent, antimicrobial barrier dressing consists of three layers. An outer blue polyurethane film layer, a central polyurethane foam layer and a nanocrystalline silver coated polyurethane film wound contact layer. The layers are heat laminated together to form a single dressing. The dressing can be cut to size and maintains its antimicrobial activity for up to 7 days.

This 510(k) premarket notification for K050030, the Acticoat® Moisture Control Dressing, is for a wound dressing and as such, does not involve the typical software-driven device acceptance criteria and studies you might expect for an AI/ML product. The submission is focused on demonstrating substantial equivalence to a predicate device, which means proving that the new device is as safe and effective as a legally marketed device.

Therefore, the requested information about acceptance criteria, device performance, sample sizes for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training sets, and ground truth establishment for AI/ML models is not applicable to this type of device submission.

Instead, the "acceptance criteria" for this submission are met by demonstrating the following:

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

Regarding the specific questions which are NOT applicable to this 510(k) submission for a wound dressing:

2. Sample sizes used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable for a wound dressing substantial equivalence submission. Performance data for a direct animal or human study for this specific claim of equivalence is not detailed in the summary.
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): Not applicable. "Ground truth" in the context of AI/ML models is not relevant here.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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/imaging device.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This is not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" here is the established safety and effectiveness of the legally marketed predicate device.
8. The sample size for the training set: Not applicable. There is no AI/ML model for which a training set would be used.
9. How the ground truth for the training set was established: Not applicable.

In summary, this 510(k) document demonstrates substantial equivalence by comparing the new device's intended use, technological characteristics (materials, design, manufacturing), and biocompatibility to a predicate device (Acticoat® Foam Dressing K000051) which has already been deemed safe and effective. The FDA's acceptance of this submission means they agreed that the Acticoat® Moisture Control Dressing is substantially equivalent to the predicate and does not raise new questions of safety or effectiveness.

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