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Fibrillar Collagen Wound Dressing is indicated for the management of moderately to heavily exudating wounds and to control minor bleeding.

Fibrillar Collagen Wound Dressing may be used for the management of exudating wounds such as:

• Pressure ulcers
• Venous stasis ulcers
• Diabetic ulcers
• Acute wounds, for example trauma and surgical wounds
• Partial-thickness burns

The Fibrillar Collagen Wound Dressing is an absorbent microfibrillar collagen matrix intended for the management of moderately to heavily exudating wounds and the control of minor bleeding. When interacting with the wound fluid, the product immediately begins to absorb the exudates. The Fibrillar Collagen Wound Dressing is applied directly to the secreting wound and protects the wound bed and delicate new tissue. In addition, the product, being comprised of microfibrillar collagen, has intrinsic hemostatic properties, which can be used to control minor bleeding.

The product is available in various sizes and is provided sterile, non-pyrogenic, and for single use only.

This document does not contain an AI/ML device, and therefore does not have acceptance criteria or study information relevant to AI/ML performance. Instead, it is a 510(k) premarket notification for a Fibrillar Collagen Wound Dressing, claiming substantial equivalence to a predicate device.

The document discusses:

• Regulatory information: FDA approval, regulatory class, product code, general controls, and compliance with various parts of the Code of Federal Regulations.
• Indications for Use: For the management of moderately to heavily exudating wounds and control of minor bleeding, applicable to pressure ulcers, venous stasis ulcers, diabetic ulcers, acute wounds (trauma, surgical), and partial-thickness burns.
• Device Description: An absorbent microfibrillar collagen matrix that absorbs exudates, protects the wound bed, and has intrinsic hemostatic properties.
• Comparison to Predicate Device (K030921): Shows identical indications for use, material (collagen), biocompatibility, sterility, pyrogenicity, and single-use/reuse characteristics.
• Nonclinical Tests: The submission included summary-level information demonstrating compliance with design controls and risk analysis. Specific tests mentioned are:
  • Cytotoxicity (L929 MEM Elution, ISO 10993-5)
  • Sensitization (Guinea Pig Maximization, ISO 10993-10)
  • Intracutaneous Reactivity (Rabbits, ISO 10993-10)
  • Acute Systemic Toxicity (Mice, ISO 10993-11)
  • Pyrogenicity (Rabbit Pyrogen Study, USP )
  • Additional in-vivo implantation and subchronic toxicity testing of the predicate device was leveraged.
• Conclusion: The device is substantially equivalent to its legally marketed predicate based on the design control process and non-clinical studies.

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CollaFirm Collagen Wound Dressing is indicated for the management of full and partial thickness wounds including; pressure ulcers, diabetic ulcers, ulcers caused by mixed vascular origin, venous ulcers, donor and graft sites, abrasions, traumatic wounds healing by secondary intention, dehisced surgical wounds, first and second degree burns. For Prescription use

CollaFirm Collagen Wound Dressing, a highly purified porcine Type I, collagen wound dressing which, when applied to a wound surface, absorbs wound fluid and maintains a moist wound environment in the management of wound healing. The CollaFirm Collagen Wound Dressing is provided in a patient ready, one (1) gram, envelop.

This document describes the 510(k) submission for the CollaFirm Collagen Wound Dressing. As such, it is not a study proving device performance against acceptance criteria in the manner of an AI/ML device. Instead, it demonstrates substantial equivalence to predicate devices through non-clinical testing and shared technological characteristics and intended use.

Here's an breakdown of the information based on the provided text, addressing your questions where applicable to a non-AI/ML device submission:

1. Table of Acceptance Criteria and Reported Device Performance

For this type of medical device (collagen wound dressing), the "acceptance criteria" are typically the standards and tests performed to demonstrate safety, effectiveness, and substantial equivalence to existing predicate devices.

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

This document does not specify "sample sizes" in the context of a "test set" as would be relevant for an AI/ML device. The "testing" here refers to non-clinical laboratory tests performed on the device material itself. The provenance of this data is from controlled laboratory experiments, not patient data in the sense of a clinical trial or AI model evaluation.

• Sample Size for Test Set: Not applicable in the context of typical AI/ML device evaluation. The "sample" is the manufactured device material used for the specified laboratory tests (e.g., cytotoxicity, irritation, sensitization, sterility, pyrogenicity, stability). The specific number of samples tested for each assay is not detailed in this summary but would be part of the full test reports.
• Data Provenance: The tests were conducted in accordance with ISO standards and USP (United States Pharmacopeia) for sterility. This indicates the testing was performed in a laboratory setting. Country of origin for data is not explicitly stated but would typically be from accredited testing facilities. The data is non-clinical/pre-clinical.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. For this type of device submission, there is no "ground truth" in the sense of medical image interpretation or disease diagnosis established by experts. Substantial equivalence relies on comparing the device's characteristics and performance to established standards and predicate devices.

4. Adjudication Method

Not applicable. There is no adjudication method needed for establishing ground truth, as the ground truth concept (expert consensus in diagnostic tasks) does not apply here. The evaluation relies on standardized laboratory tests and comparison to predicate devices, which are objective measurements or assessments.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document explicitly states: "CollaFirm Collagen Wound Dressing has not been studied in a clinical setting." This type of study would involve human readers (e.g., clinicians) evaluating cases, which is typically for AI-assisted diagnostic or prognostic tools.

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

No, a standalone performance study (algorithm only) was not done. This is not an AI/ML device, so concepts like "algorithm only" or "human-in-the-loop" are not relevant. The device is a physical wound dressing.

7. The Type of Ground Truth Used

Not applicable in the context of AI/ML. For this submission, "ground truth" is established through:

• Standardized laboratory tests: E.g., ISO standards for biocompatibility (cytotoxicity, irritation, sensitization), USP for sterility, LAL for pyrogenicity. The results of these tests, against predetermined pass/fail criteria, serve as empirical evidence.
• Comparison to predicate devices: The "ground truth" for substantial equivalence often involves demonstrating that the new device's properties and performance are comparable to (or within acceptable limits of) legally marketed predicate devices that have already been deemed safe and effective by the FDA. The amino acid analysis is an example of this.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device, so there is no "training set."

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

Not applicable. This is not an AI/ML device, so there is no "training set" or "ground truth for the training set."

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