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The V.A.C.® GranuFoam® Silver Protection dressing is intended for use with the V.A.C.® family of negative pressure wound therapy systems to help promote wound healing. The dressing is an effective barrier to bacterial penetration and may help reduce infection in chronic, acute, traumatic, subacute, and dehisced wounds, diabetic ulcers, pressure ulcers, flaps, grafts and partial thickness burns.

The V.A.C.® GranuFoam® Silver Protection dressing is one of the V.A.C.® product line of dressings designed specifically for use with the V.A.C.® Family of negative pressure devices. The V.A.C.® GranuFoam® Silver Protection dressing is comprised of black, reticulated, polyurethane foam covered with a silver coating.

Acceptance Criteria and Study for V.A.C.® GranuFoam® Silver Protection Dressing

This device, the V.A.C.® GranuFoam® Silver Protection Dressing, received 510(k) clearance based on its substantial equivalence to a previously cleared predicate device, the V.A.C.® GranuFoam™ Silver Protection Dressing (K050260). The primary change in the current submission was labeling modifications, specifically the removal of a contraindication for use in magnetic resonance environments and the inclusion of labeling for conditions of safe use in such environments.

Therefore, the "acceptance criteria" and "study" are not based on the device's diagnostic performance or clinical effectiveness in the traditional sense, but rather on its safety and compatibility in a specific environment.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not applicable in the context of a new clinical study. The evaluation focused on testing in accordance with international performance standards and review of peer-reviewed published literature regarding MR safety of similar materials/devices. The document does not specify a "test set" of patients or data in the typical sense of a clinical trial.
• Data Provenance: Not explicitly stated as retrospective or prospective clinical data. The evaluation relies on international performance standards (which are typically defined guidelines and test methods) and peer-reviewed published literature (which could be derived from various sources, but the origin is not specified here).

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

Not applicable. The ground truth for MR compatibility is established through adherence to international performance standards and scientific evidence from peer-reviewed published literature, not through expert consensus on a test set of cases. These standards and literature would have been reviewed by individuals with expertise in regulatory affairs, engineering, and medical device safety (likely within the FDA and KCI).

4. Adjudication Method for the Test Set

Not applicable. There was no clinical "test set" requiring adjudication. The evaluation was based on demonstrating compliance with technical standards and scientific literature for MR compatibility.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done for this submission. This type of study is typically used to evaluate the diagnostic performance of software or imaging modalities with and without AI assistance. This device is a wound dressing, not a diagnostic tool requiring such a study.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Not applicable. This device is a physical wound dressing, not an algorithm, so a standalone performance evaluation in this context is not relevant.

7. The Type of Ground Truth Used

The "ground truth" here is the established scientific and regulatory understanding of magnetic resonance compatibility for medical devices. This is derived from:

• International performance standards: Standards specifically designed to test and assess device safety within MR environments (e.g., ASTM standards for MR safety).
• Peer-reviewed published literature: Existing scientific publications and research related to materials, device designs, and their interactions with MR fields.

8. The Sample Size for the Training Set

Not applicable. There is no "training set" for this device, as it is a physical wound dressing and not an AI/algorithm-based device.

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

Not applicable, as there is no training set.

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The V.A.C. ® GranuFoam® Silver Protection dressing is intended for use with the V.A.C. ® family of negative pressure wound therapy systems to help promote wound healing. The dressing is an effective barrier to bacterial penetration and may help reduce infection in chronic, acute, traumatic, subacute, and dehisced wounds, diabetic ulcers, pressure ulcers, flaps, grafts and partial thickness burns.

The V.A.C. Granufoam Silver Protection dressing is an addition to the V.A.C. 9 product line of dressings designed specifically for use with the V.A.C. 0 Family of negative pressure devices. The V.A.C. GranuFoam Silver Protection dressing is comprised of black, reticulated, polyurethane foam covered with a silver coating.

The provided text describes the V.A.C. GranuFoam Silver Protection Dressing and its substantial equivalence to predicate devices, focusing on its use as an antimicrobial barrier and for negative pressure wound therapy. However, the details required to fill out a comprehensive table of acceptance criteria and a detailed study description for a typical AI/device performance evaluation are not fully present in the document.

Here's an attempt to extract and infer information based on the provided text, and point out where information is missing for a complete response:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not specified for the comparative in vitro or bench testing. The document refers to "testing" and "conducted on the dressings," but doesn't provide numbers of samples or experimental runs.
• Data Provenance: Not explicitly stated (e.g., country of origin). The testing described appears to be laboratory-based ("in vitro testing", "bench testing") rather than involving human subjects. Therefore, a "retrospective or prospective" classification isn't directly applicable in the typical clinical study sense.

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

• Not applicable. The studies mentioned (in vitro, bench testing) are not clinical studies involving expert interpretation or "ground truth" establishment in a diagnostic context. They assess material properties and antimicrobial activity.

4. Adjudication method for the test set

• Not applicable. As per point 3, this is not a study where expert adjudication would be relevant.

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 device (dressing) submission, not an AI/diagnostic software submission. Therefore, MRMC studies and AI assistance are not relevant.

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

• No. This is not an algorithm or AI device.

7. The type of ground truth used

• For Antimicrobial Barrier Effectiveness: The "ground truth" would be established by microbiological laboratory standards and comparison to the known antibacterial performance of the predicate devices. The specific metrics (e.g., zone of inhibition, bacterial log reduction) are not detailed.
• For Compatibility with V.A.C. Negative Pressure Systems: The "ground truth" would be established by engineering specifications and performance characteristics (e.g., fluid handling capacity, tensile strength, pore size) of the predicate devices.
• For Biocompatibility: The "ground truth" is established by the international standard ISO-10993, which outlines methods for evaluating biological responses to medical devices.

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device.

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

• Not applicable. As per point 8, this is not an AI/machine learning device.

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