(309 days)
LUOFUCON® Collagen Wound Dressing is intended for the management of wounds including: full thickness and partial thickness wounds, pressure ulcers, ulcers, ulcers caused by mixed vascular etiologies, diabetic ulcers, partial thickness burns, donor sites and other bleeding surface wounds, abrasions, traumatic wounds healing by secondary intention, dehisced surgical incisions.
The dressing can be cut to the exact size of the wound, and can be used in multiple layers.
LUOFUCON® Collagen Wound Dressing is comprised of a porous matrix of cross-linked bovine collagen. LUOFUCON® Collagen Wound Dressing is a sterile, single use, white or off-white, pliable, absorbent and biodegradable wound dressing.
When the wound dressing absorbs wound exudate or sterile water, LUOFUCON® Collagen Wound Dressing transforms into a soft, conformable gel sheet, maintains a moist wound environment, to protect the wound and support natural healing.
LUOFUCON® Collagen Wound Dressing can be used as a primary wound dressing in direct contact with the wound, or be used in combination with other suitable secondary dressings. The dressing can be cut to the exact size of the wound, and can be used in multiple layers.
LUOFUCON® Collagen Wound Dressing is sterilized and sold after sterilization by radiation using conditions validated following ISO 11137-2:2013.
The provided text is a 510(k) summary for the LUOFUCON® Collagen Wound Dressing, which is a medical device intended for wound management. The document states that the device is substantially equivalent to a predicate device (Medline Collagen Wound Dressing, K060456).
The document does not describe a study in the context of comparing the device to human readers or an AI algorithm, but rather a set of bench tests and biocompatibility tests to demonstrate safety and effectiveness for its intended use, and to prove substantial equivalence to a predicate device. This is typical for a 510(k) submission for a wound dressing, which is not an AI-powered diagnostic device.
Therefore, many of the requested fields are not applicable to the information provided in this document.
Here's a breakdown based on the available information:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state "acceptance criteria" as numerical thresholds for specific performance metrics. Instead, it states that "the subject device meets all product performance requirements for the intended use and demonstrates substantial equivalence to the predicate device."
However, we can infer some "performance requirements" that were tested:
| Criterion | Reported Device Performance |
|---|---|
| Sterilization | Sterilized using gamma radiation to a sterility assurance level of 10^-6. Confirmed per ISO 11137-1/-2. |
| Shelf-Life | 2 years (demonstrated by real-time aging test). |
| Biocompatibility | Meets biocompatibility requirements of ISO 10993-1 standard and FDA Guidance; raised no new safety concerns. |
| Physical/Chemical/Biological Properties (Bench Tests) | Meets all product performance requirements for the intended use; demonstrates substantial equivalence to the predicate device. |
| Animal-Derived Materials Safety | Compliant with FDA guidance and ISO 22442 standards; more than 6 logs reduction of viruses. |
2. Sample size used for the test set and the data provenance
Not applicable in the context of an AI/human reader study. The document refers to "non-clinical data and performance data" and "bench tests" performed on the device itself. Specific sample sizes for these tests (e.g., number of dressings tested for tensile strength) are not provided in this summary.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. There is no mention of a test set with ground truth established by experts, as this is not an AI diagnostic device.
4. Adjudication method 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-powered device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI-powered device.
7. The type of ground truth used
Not applicable. The "ground truth" here is the physical, chemical, biological, and safety characteristics of the device being evaluated against established standards and the characteristics of the predicate device. For example, for sterility, the ground truth is "sterile at SAL 10^-6". For biocompatibility, the ground truth is "meeting ISO 10993-1 requirements".
8. The sample size for the training set
Not applicable. There is no "training set" in the context of a machine learning model for this medical device submission.
9. How the ground truth for the training set was established
Not applicable.
N/A