(228 days)
Dermacyn™ Wound Cleanser is intended for moistening and debriding acute and chronic dermal lesions, such as Stage I-IV pressure ulcers, statis ulcers, diabetic ulcers, post-surgical wounds, first and second degree burns, abrasions and minor irritations of the skin.
The subject device is a wound cleansing solution that is intended for the cleansing of dermal wounds. The mechanical action of fluid moving across the wound provides for the mechanism of action and aids in the removal of foreign objects such as dirt and debris. The subject device is offered in various bottle sizes.
The provided text is a 510(k) summary for the Dermacyn™ Wound Cleanser. This type of regulatory submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting detailed studies with acceptance criteria and performance metrics in the way a clinical trial for a new drug or a novel AI software would.
Therefore, the document does not contain the specific information requested regarding acceptance criteria and performance studies in the context of device performance, test sets, expert adjudication, or AI assistance.
Here's a breakdown of why the requested information is absent based on the provided text:
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Acceptance Criteria and Reported Device Performance: Not applicable in this context. The 510(k) summary focuses on demonstrating that the device is "substantially equivalent" to existing products, not on meeting specific performance criteria related to accuracy, sensitivity, or other typical metrics for a diagnostic or AI device. It mentions "Non-clinical testing was conducted to confirm the safe and effective performance," but it doesn't quantify or specify acceptance criteria for these tests. The "performance" assessment is comparative, showing it performs similarly to predicate devices.
- Table of Acceptance Criteria and Reported Device Performance: This information is not explicitly provided. The summary states "Non-clinical testing was conducted to confirm the safe and effective performance of Dermacyn™ Wound Cleanser. Pre-clinical testing also demonstrated the biocompatibility of the subject device." However, no quantifiable acceptance criteria or reported numerical performance metrics are given.
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Sample Size and Data Provenance for Test Set: This kind of information is generally not included in a 510(k) summary for a wound cleanser. The "testing" mentioned is likely related to manufacturing quality, sterility, shelf-life, and biocompatibility, not a clinical "test set" in the sense of a medical imaging or AI device.
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Number of Experts and Qualifications: Not applicable. The "ground truth" concept, as used in the context of expert review for medical devices or AI, does not apply to a physical wound cleanser. The "truth" here would be its chemical and physical properties and its effect on wounds, which are assessed through laboratory and possibly limited preclinical studies, not expert consensus on interpretations.
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Adjudication Method: Not applicable for the reasons mentioned above. There's no interpretive "ground truth" that needs adjudication.
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Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not applicable. This type of study is relevant for diagnostic devices where human readers interpret medical data (e.g., radiologists reading images) and AI might assist them. A wound cleanser does not involve human interpretation in this manner.
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Standalone Performance: While the wound cleanser operates "stand-alone" in its intended use, the concept of "standalone performance" in the context of device evaluation usually refers to an algorithm's performance without human intervention, which is not relevant here. The device itself is standalone.
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Type of Ground Truth Used: The "ground truth" for a wound cleanser would be its physical and chemical properties and its biological effects (e.g., sterilization effectiveness, irritation potential, wound healing mechanisms), established through laboratory assays and possibly animal models, rather than expert consensus, pathology, or outcomes data in humans for substantial equivalence. The document indicates "Pre-clinical testing also demonstrated the biocompatibility of the subject device."
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Sample Size for Training Set: Not applicable. There is no AI component or machine learning model being "trained."
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How Ground Truth for Training Set was Established: Not applicable.
In summary, the provided 510(k) document is for a non-AI, non-diagnostic medical device. The regulatory pathway for such devices focuses on demonstrating substantial equivalence to predicate devices based on indications for use, technological characteristics, and safety data (e.g., biocompatibility) rather than detailed clinical performance studies with acceptance criteria, test sets, and expert adjudication, which are more typical for novel diagnostic or AI-powered devices.
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