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The Armis VeriCyn® Wound Wash is to be used with a lavage system to create mechanical movement at the wound surface by delivery of a solution and is indicated for use in cleansing and removal of foreign material including microorganisms and debris from wounds (such as stage I-IV pressure ulcers, diabetic foot ulcers, post surgical wounds, first degree and partial thickness burns, grafted and donor sites).

The ARMIS VeriCyn® Wound Wash is an aqueous solution for irrigation and debridement of wounds. The solution is a clear, colorless, no-odor aqueous solution that is used to remove debris, including microorganisms from wounds though the use of a lavage system. ARMIS VeriCyn® Wound Wash contains: Hydrogen Peroxide, Acetic Acid, Disodium EDTA and Purified water. VeriCyn® Wound Wash has been tested for compliance with ISO 10993.

The provided text describes information for a 510(k) submission for the Armis VeriCyn® Wound Wash. Based on the content, this is a medical device (a wound wash solution) and not an AI/ML device, therefore, many of the requested criteria (like ground truth, experts, MRMC studies, training set, etc.) are not applicable.

However, I can extract the relevant acceptance criteria and details of the non-clinical testing performed to establish substantial equivalence.

Here's the information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are largely based on demonstrating substantial equivalence to a predicate device (Next Science™ Irrigation Solution) through non-clinical testing, ensuring safety and effectiveness for its intended use. The "reported device performance" refers to the results of these non-clinical tests.

2. Sample size used for the test set and the data provenance

Not applicable for this type of device (wound wash solution). The "test set" here refers to the samples of the wound wash solution and materials that underwent physical, chemical, and biological testing, not a dataset of patient images or clinical cases. The provenance of the data is from specific laboratory tests conducted on the device components and the final product, as detailed under "Non-Clinical Tests Performed."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. No expert consensus "ground truth" as typically understood for AI/ML devices is relevant here. The standards for testing (e.g., ISO 10993, USP , , ) provide the "ground truth" of performance criteria, and the tests themselves are conducted by qualified laboratory personnel following these established protocols.

4. Adjudication method for the test set

Not applicable. Adjudication methods like "2+1" or "3+1" are used in clinical trials involving human interpretation, often for AI/ML device validation. For this wound wash solution, performance is assessed against established physical, chemical, and biological standards through laboratory testing.

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/ML device; it is a physical wound wash solution. MRMC studies are used to evaluate diagnostic or screening AI/ML devices.

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

Not applicable. This is not an AI/ML algorithm.

7. The type of ground truth used

The "ground truth" for this device's performance is based on established international and national standards and test methodologies for medical device safety, biocompatibility, and functional performance. These include:

• ISO 10993 series: For biocompatibility testing (Cytotoxicity, Sensitization, Irritation, Acute Systemic Toxicity, Material Mediated Pyrogenicity).
• USP : For Preservative Effectiveness.
• USP and : For Bioburden.
• Internal specifications: For physical properties like Clarity, Color, pH, and Viscosity, which are then compared to the predicate or deemed safe.
• Functional wound-wash study: To demonstrate mechanical removal of debris.

8. The sample size for the training set

Not applicable. This device does not use a training set as it is not an AI/ML algorithm.

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

Not applicable. This device does not have a training set.

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BD Surgiphor™ Antimicrobial Irrigation System is intended to mechanically loosen and remove debris, and foreign materials, including microorganisms, from wounds.

The BD Surgiphor™ Antimicrobial Irrigation System is a 2-step system of aqueous solutions for irrigation and debridement of wounds. The 2-step process includes one bottle of Surgiphor™ Solution (0.5% Povidone Iodine) which is used first to loosen wound debris, and one bottle of SurgiRinse™ Solution (saline solution, USP 99.95%) which is used second to rinse the loosened debris from the wound. The mechanical action of fluid moving across the wound provides the mechanism of action and aids in the removal of debris, and foreign materials, including microorganisms, from wounds. The BD Surgiphor™ Antimicrobial Irrigation System is provided as a two-part terminally sterilized system with 450 mL of each solution. The povidone in the Surgiphor™ Solution serves as a preservative to ensure that no unwanted microbial growth occurs in the solution after the bottle is open.

The provided text describes a 510(k) premarket notification for the "BD Surgiphor Antimicrobial Irrigation System." It focuses on demonstrating substantial equivalence to predicate devices, particularly regarding the addition of "microorganisms" to the device's indications for use.

Based on the provided text, the device is a medical irrigation system, not an AI/ML device. Therefore, the questions about acceptance criteria, study design, and performance related to AI/ML (e.g., sample size, ground truth establishment, expert adjudication, MRMC studies, standalone performance, training sets) are not applicable to this submission.

The document primarily addresses the substantial equivalence of a physical medical device. The "performance testing" section refers to standard medical device testing (e.g., sterility, biocompatibility, packaging, stability, fluid pressure testing for mechanical action), not AI/ML model performance.

Here's a summary of what is provided regarding acceptance criteria and performance, as applicable to this medical device:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't present a formal table of quantitative acceptance criteria for performance in the way one would for an AI/ML device (e.g., accuracy, sensitivity, specificity thresholds). Instead, it states that "Substantial equivalence has been confirmed through performance testing." The performance testing described is primarily focused on demonstrating the physical and chemical properties and safety of the device, rather than a diagnostic or predictive performance metric.

2. Sample size used for the test set and the data provenance:

• Not applicable for an AI/ML context. The tests are for the physical device, not an algorithm processing data.

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):

• Not applicable. Ground truth in the context of an AI/ML study does not apply to this physical device.

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

• Not applicable. This relates to expert review of data for AI/ML model ground truth.

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 study type is for evaluating AI assistance in diagnostic tasks.

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

• Not applicable. There is no algorithm being evaluated in this submission.

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

• Not applicable in the AI/ML sense. The "ground truth" for this device's effectiveness relies on the mechanical action of fluid physically removing debris, which is demonstrated through fluid pressure testing and comparison to predicate devices, rather than a diagnostic 'truth'. The claim for "microorganism removal" is based on its mechanical action, not a specific antimicrobial kill claim.

8. The sample size for the training set:

• Not applicable. There is no training set for an AI/ML model.

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

• Not applicable. There is no training set for an AI/ML model.

In summary, the provided document is a 510(k) summary for a physical medical device, not an AI/ML device. Therefore, questions 1 (in the AI/ML context), 2, 3, 4, 5, 6, 7 (in the AI/ML context), 8, and 9 are not addressed in the text as they pertain to AI/ML model development and validation. The acceptance criteria and performance discussions are framed within the context of a medical device's physical, chemical, and sterility properties, and its intended mechanical action, demonstrating substantial equivalence to legally marketed predicates.

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Catasyn OTC is indicated for the dressing and management of minor burns, minor cuts, minor lacerations, minor abrasions, and minor irritations of the skin.

Catasyn RX may be used under the direction of a health care professional for the dressing and management of partial to full thickness dermal ulcers (pressure sores, venous stasis ulcers, arterial ulcers, diabetic ulcers), surgical wounds (post-operative incisions and donor sites) and superficial and partial thickness (second degree) burns.

Catasyn is a clear, colorless hydrogel that is composed of hypromellose, arginine derivatized chitosan, betaine, and methylparaben to form a hydrogel dressing. The device is a non-sterile, preserved hydrogel. The gel is supplied in 0.07oz. (2mL), 0.85oz (25mL), or 3oz (88.7mL) tubes.

Catasyn is a wound hydrogel that provides a moist wound environment. A moist wound environment is supportive to wound healing.

This document is a 510(k) Premarket Notification for a medical device called "Catasyn Advanced Technology Wound Hydrogel." The purpose of a 510(k) submission is to demonstrate that a new medical device is substantially equivalent to a legally marketed predicate device, meaning it has the same intended use and similar technological characteristics, or if there are differences, that those differences do not raise new questions of safety or effectiveness.

The document does not describe a study that proves the device meets specific acceptance criteria in the context of an Artificial Intelligence/Machine Learning (AI/ML) powered medical device. Instead, it presents performance data related to the physical and biological properties of the wound hydrogel itself, to show its safety and function compared to a predicate device.

Therefore, I cannot fulfill your request for information related to "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of an AI/ML device, as this document is for a non-AI/ML medical device.

To directly answer your prompt, based only on the provided document, the following points are relevant, but not in the context of an AI/ML device:

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

   While not "acceptance criteria" in the sense of an AI/ML model's performance metrics (like sensitivity, specificity, AUC), the document presents a table of Biocompatibility Testing with descriptions of the tests (the "criteria" for safety) and their results (the "performance"):

   Test	Description	Result
   Cytotoxicity Direct Contact	Cytotoxicity was evaluated using ISO-10993-5, Biological evaluation of Medical Devices-Part 5: Tests for In Vitro Cytotoxicity.	Non-toxic
   Maximization Test For Delayed Type Hypersensitivity	Delayed-type hypersensitivity was evaluated according to ISO 10993-10:2010, Biological evaluation of medical devices - Part 10: Tests for Irritation and skin sensitization.	No Sensitization reaction was observed in any of the test animals
   Dermal Irritation	Dermal irritation was evaluated according to ISO 10993-10:2010, Biological evaluation of medical devices – Part 10: Tests for irritation and skin sensitization.	No erythema or edema was observed. The Primary Irritation Index for the test article was 0.
   Acute Systemic Toxicity	Acute systemic toxicity was tested according to ISO 10993-11, Biological Evaluation of Medical Devices – Tests for Systemic Toxicity.	No Biological reactivity was observed at any time point
   Hemolysis extraction method and direct contact	Hemolysis was tested according to ASTM 756-13 for both extraction and direct contact methods.	The corrected hemolytic index was 0% for extraction and direct contact. The test article is considered non-hemolytic.

   Additionally, preservation effectiveness and shelf-life data are presented:

   • Preservation: Meets USP 51 Category 2 challenge (immediately following production and at 6-month shelf life).
   • Shelf Life: Meets specifications after 9 months of real-time aging (on a 36-month study).

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
   For the biocompatibility tests (e.g., Cytotoxicity, Maximization Test, Dermal Irritation, Acute Systemic Toxicity, Hemolysis), the document does not specify the sample sizes of cells, animals, or human subjects used. It also does not mention the country of origin of the data or whether the studies were retrospective or prospective. These are standard in vitro or in vivo (animal) lab tests, not clinical studies on human patients.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
   Not applicable, as this is not an AI/ML device requiring expert adjudication for ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) 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.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Not applicable.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc):
   The "ground truth" here refers to established biological and chemical safety standards (e.g., ISO 10993 series, ASTM 756-13, USP 51) and laboratory test results demonstrating the absence of toxicity, irritation, sensitization, or hemolytic reactions.

8. The sample size for the training set:
   Not applicable, as this is not an AI/ML device.

9. How the ground truth for the training set was established:
   Not applicable.

In summary, the provided document is a 510(k) submission for a traditional wound care product (hydrogel) and thus does not contain the information typically required for evaluating an AI/ML medical device.

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Next Science™ Irrigation Solution is to be used with a jet lavage system and is indicated for use in cleansing and removal of debris, including microorganisms, from wounds.

Next Science™ Irrigation Solution is an aqueous solution for irrigation and debridement of wounds. The solution is a clear, colorless, low-odor aqueous solution that is used to remove debris, including microorganisms, from wounds. The mechanical action of fluid moving across the wound provides the mechanism of action and aids in the removal of debris, including microorganisms, from wounds. Next Science™ Irrigation Solution will be provided in a 1000 mL polypropylene plastic container with a single port and will be labeled "not for IV use". The container will be provided in a polyethylene overwrap and packaged with six (6) containers per case. The formulation for Next Science™ Irrigation Solution is composed of ethanol, acetic acid, sodium acetate, benzalkonium chloride and water.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Next Science Irrigation Solution:

I. Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state quantitative acceptance criteria in a structured table. Instead, it relies on a qualitative comparison to the predicate device regarding safety and effectiveness, supported by various tests. The core acceptance criterion is "Substantial Equivalence" to the predicate device, Prontosan Wound Irrigation Solution (K072876).

Since no numerical performance metrics are provided in the document, I cannot create a table with specific acceptance criteria and reported device performance. The information focuses on whether the device is at least as safe and effective as the predicate.

II. Study Details

1. Sample Size used for the test set and data provenance:

   • Test Set Description: The core "test set" for the critical animal study involved eight Yorkshire pigs.
   • Data Provenance: The document does not specify the country of origin for the animal study. It was a prospective study designed to evaluate the effect of the irrigation solution.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • The document does not mention the use of experts to establish a "ground truth" for the animal study in the typical sense of expert annotation for AI algorithms. The assessment of wound healing was likely conducted by the study investigators based on observable physiological responses and histological analysis (though not explicitly detailed beyond "normal wound healing").
   • Therefore, information on the number and qualifications of experts for ground truth establishment is not provided.

3. Adjudication method for the test set:

   • The document describes that "The four wounds were treated with the same control or test solution, or an empty control (no treatment)." This indicates a controlled experimental design where different treatments (test solution, control article, no treatment) were applied to wounds on the same animals.
   • However, it does not describe an adjudication method for establishing ground truth, as it's not a human-reader interpretation study. The assessment of wound healing would be based on scientific observation and measurement.

4. 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:

   • No MRMC study was done. This device is a medical solution (irrigation solution), not an AI-powered diagnostic or assistive tool for human readers. Therefore, there's no concept of human readers improving with or without AI assistance in this context.

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

   • Not applicable. This device is a physical solution, not an algorithm. Therefore, no standalone algorithm-only performance study was conducted.

6. The type of ground truth used:

   • For the animal study, the "ground truth" was based on biological outcomes or physiological response, specifically "normal wound healing." This would have been assessed through direct observation and potentially histological analysis of the wound sites over the 24-day study period.

7. The sample size for the training set:

   • Not applicable. This is not a machine learning device that requires a training set.

8. How the ground truth for the training set was established:

   • Not applicable. As there is no training set, there's no ground truth to establish for it.

In summary, the provided document describes a medical device (an irrigation solution) and its substantial equivalence determination based on biocompatibility, functional performance, and animal testing, rather than an AI/software device requiring a test set for algorithm performance evaluation, human reader studies, or training sets.

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