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Carilex VT Dressing Kits is intended to be used with the Carilex VT device (S1 series) to manage wounds through removal of fluids, and the NPWT system is indicated for patients who would benefit from a suction device, particularly as the device may promote wound healing by removal of fluids, excess exudates, infectious material, and tissue debris.

The Carilex VT Dressing Kits is indicated for use for patients with the following wounds:

• Traumatic
• Dehisced wounds
• Partial-thickness burns
• Chronic wounds including pressure ulcers, diabetic foot ulcers and venous leg ulcers
• Acute wounds
• Flaps and grafts

Carilex VT Dressing Kits is the wound dressing to be used with the Carilex VT suction pumps for negative pressure wound therapy. This single-use dressing is manufactured using a reticulated flexible polyether and polyurethane hydrophobic material, housed in a medical grade peel pouch, and sterilized by Ethylene Oxide. The Carilex VT Dressing Kits is available in three sizes; 1) small 2) medium and 3) large

The provided text describes the Carilex VT Dressing Kits (K172725) and its equivalence to a predicate device, the DeRoyal Foam Kits (K112458). The document focuses on regulatory approval and substantial equivalence based on non-clinical tests.

Acceptance Criteria and Device Performance:

The document doesn't explicitly list "acceptance criteria" in a typical quantitative sense (e.g., sensitivity, specificity for an AI device). Instead, it states that the dressing kits met "all pre-determined acceptance criteria and passed the tests" during performance/comparison testing against the predicate device. These criteria would likely be related to the physical and functional performance of the dressing kits in managing wounds through fluid removal, as described in their intended use.

The "reported device performance" is implicitly that it performs comparably to the predicate device, thereby demonstrating substantial equivalence. The "Technological Comparison to Predicate Devices" table (pages 4-5) highlights the similarities across various attributes:

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

Missing Information:

The provided document is a 510(k) summary for a medical device (wound dressing kits), not an AI/software device. Therefore, many of the requested details, such as sample sizes, ground truth establishment methods, expert qualifications, and MRMC study specifics, are not applicable to this type of submission and are not present in the document.

Here's why and what can be gleaned:

2. Sample size used for the test set and the data provenance: Not applicable. This refers to performance testing of the physical medical device and its components, not data-driven AI. The "test set" would be the manufactured dressing kits themselves subjected to various physical and chemical tests (e.g., sterilization validation, material testing, fluid absorption/removal efficiency, biocompatibility). The document mentions "Performance/Comparison Testing of VT Dressing Kits with the predicate" and "The biocompatibility tests were performed with the final finished form of VT Dressing Kits." No details on the exact sample sizes of physical units tested or data provenance (country of origin, retrospective/prospective) are provided, as these are typically part of internal technical reports referenced in the 510(k).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically understood for AI (e.g., image annotations by radiologists) is not relevant here. The "ground truth" for this device would be established engineering and scientific standards for material properties, sterility, and device function.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This relates to expert consensus for AI ground truth.

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 for AI-assisted diagnostic or interpretive devices.

6. If a standalone (i.e., algorithm only without human-in-the loop performance) was done: Not applicable. This is for AI algorithm performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): The "ground truth" for this physical device relies on established engineering and medical standards for material properties, sterility, and functional performance. Things like ISO 10993 (biocompatibility) are the "ground truth" against which the device is measured.

8. The sample size for the training set: Not applicable. There is no AI model or algorithm being "trained" for this physical device.

9. How the ground truth for the training set was established: Not applicable.

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