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ColActive® Transfer is indicated for management of full and partial thickness wounds including: pressure ulcers, diabetic ulcers, ulcers caused by mixed vascular etiologies, venous ulcers, second degree burns, donor and graft sites, abrasions, dehisced surgical wounds, traumatic wounds healing by secondary intention.

ColActive® Transfer is a modification to the existing ColActive® Collagen Wound Dressing previously cleared under K050177 on 27th April 2005. ColActive® Transfer is composed of the same base matrix material; collagen and sodium alginate and is made from substantially an equivalent manufacturing process as the predicate. The new product, ColActive® Transfer is a pliable, absorbent, perforated, and biocompatible dressing. ColActive® Transfer dressings absorb and transfer moisture such as wound fluid and maintains a moist environment at the wound surface. The dressings can be cut to fit specific wounds and can be layered for the management of deep wounds. ColActive® Transfer dressings contain multiple holes that are evenly distributed across the surface area in order to facilitate the movement of excess exudates through the dressing and away from the wound. The new product will be supplied sterile packaged in a single use heat sealed medical grade foil pouch. The single use primaries will be packed, with a product insert, into cartons for distribution.

This document is a 510(k) Summary of Safety and Effectiveness for a medical wound dressing, ColActive® Transfer. It focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study to prove the device meets specific acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, study details, and performance metrics is not explicitly provided in this document.

Here's an analysis based on the provided text:

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

The document does not provide a table of acceptance criteria with specific quantitative targets. Instead, it relies on demonstrating substantial equivalence to a predicate device by comparing technological characteristics and performance through "bench testing."

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 mentions "bench testing," including "heat stability, crosslinking, fluid/water absorption, as well as visual testing (Defect Free surface and even dressing thickness)." However, it does not specify sample sizes for these tests or the data provenance. These are laboratory tests typically performed on manufactured batches of devices, not clinical data sets.

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 applicable and therefore not provided. The study relies on bench testing of physical properties and comparison to a predicate device, not on expert interpretations or ground truth establishment in a clinical context.

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

This information is not applicable and therefore not provided. Adjudication methods are typically used in clinical studies with human assessors, not for bench testing of physical device properties.

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

An MRMC comparative effectiveness study was not performed. This is a wound dressing, not an AI-powered diagnostic device, so AI assistance is not relevant.

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

This is not applicable. The device is a physical wound dressing; it does not involve any algorithms or AI for standalone performance.

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

The concept of "ground truth" as typically used in AI/diagnostic studies is not applicable here. The "truth" for the performance tests (bench tests) would be the measured physical properties of the device (e.g., absorption capacity in ml/cm², stability at certain temperatures). These are objective measurements against predefined specifications or comparison to the predicate, not subjective expert consensus or clinical outcomes data.

8. The sample size for the training set

This is not applicable as there is no "training set" for this device. It is a physical medical device, not a machine learning model.

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

This is not applicable, as there is no training set or ground truth in that context.

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