(217 days)
For over-the-counter use, Absorbent Antimicrobial Wound Dressing may be used for minor abrasions, lacerations, minor cuts, minor scalds and burns.
Under the supervision of a health care professional, Absorbent Antimicrobial Wound Dressing is an effective barrier to bacterial penetration, which may help reduce infection in partial thickness (second degree) burns, diabetic foot ulcers (venous stasis ulcers, arterial ulcers and leg ulcers of mixed aetiology) and pressure ulcers/sores (partial & full thickness), surgical wounds left to heal by secondary intent, traumatic wounds, wounds that are prone to bleeding such as wounds that have been mechanically or surgically debrided and oncology wounds with exudate such as fungoides-cutaneous tumors, fungating carcinoma, cutaneous metastasis, Kaposi's sarcoma and angiosarcoma.
Absorbent Antimicrobial Wound Dressing may be used on minimally exuding, non-exuding and dry wounds as stated in the DIRECTIONS FOR USE.
Absorbent Antimicrobial Wound Dressing is composed of sodium carboxymethylcellulose and ionic silver. In contact with wound exudate, the highly absorbent dressing creates a soft, cohesive gel that forms an intimate contact with the wound surface and maintains a moist woundhealing environment.
The provided text describes a 510(k) premarket notification for a medical device called "Absorbent Antimicrobial Wound Dressing." This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving the device meets specific acceptance criteria through a clinical study with detailed performance metrics.
Therefore, many of the requested sections regarding acceptance criteria, study design, sample sizes, expert ground truth, and comparative effectiveness studies are not applicable or available in this document. The submission relies on comparative bench testing and biocompatibility testing to establish substantial equivalence.
Here's a breakdown of the available information:
1. A table of acceptance criteria and the reported device performance
This information is not provided in the document. The 510(k) process for this device focuses on demonstrating substantial equivalence to a predicate device rather than meeting specific quantifiable performance criteria against a predefined standard. The document mentions "comparative bench testing" and "biocompatibility testing," but does not detail the acceptance criteria or specific performance results from these tests in a table format.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided in the document. The document mentions "comparative bench testing" but does not specify the sample sizes or data provenance (country of origin, retrospective/prospective). It also mentions "biocompatibility testing."
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 or provided. For bench testing and biocompatibility testing, "ground truth" as it relates to expert consensus for diagnostic or prognostic devices is not relevant. The ground truth for such tests typically relies on established laboratory standards and measurement protocols rather than expert human interpretation.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable or provided. Adjudication methods are typically relevant for studies involving human interpretation or clinical endpoints, not for bench testing or biocompatibility testing as described.
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
This information is not applicable or provided. The device in question is a wound dressing, not an AI-powered diagnostic or assistive technology. Therefore, an MRMC study or evaluation of human reader improvement with AI assistance is not relevant.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable or provided. The device is a wound dressing, not an algorithm. Standalone algorithm performance is not relevant.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the biocompatibility testing, the ground truth would be established through laboratory standards and measurements as defined by relevant ISO or ASTM standards for biocompatibility (e.g., cytotoxicity, sensitization, irritation indices).
For the comparative bench testing, the ground truth would be based on physical and chemical measurements comparing the Absorbent Antimicrobial Wound Dressing's properties (e.g., absorbency, silver release) against those of the predicate device (Acticoat™ Silver Coated Wound Dressing) using defined laboratory protocols. The document does not specify what specific parameters were measured or how ground truth for those parameters was established, other than implying standard laboratory methods.
8. The sample size for the training set
This information is not applicable or provided. The development of a wound dressing does not typically involve a "training set" in the context of machine learning. The product development would involve iterative design, formulation, and testing, but not a training set as understood in AI systems.
9. How the ground truth for the training set was established
This information is not applicable or provided, as there is no "training set" in the context of this traditional medical device submission.
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