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KeraStat® Cream is intended to maintain a moist wound environment. KeraStat® Cream is indicated for the management of a number of partial thickness skin wounds such as: partial thickness (first and second degree) burns, superficial injuries, cuts, and incisions/surgical wounds. Under the direction of a healthcare professional, KeraStat® Cream also may be used in the management of dry, light, and moderately exuding partial thickness wounds including: pressure (stage I-II) ulcers, venous stasis ulcers caused by mixed vascular etiologies, diabetic ulcers, radiation dermatitis, donor sites, and grafts.

KeraStat® Cream is not indicated for full thickness or third degree will be available by prescription.

KeraStat® Cream is a non-sterile, non-implantable wound dressing intended to provide a moist environment in the management of a variety of partial thickness dermal wounds. KeraStat® Cream is provided in a screw top tube for multiple uses. Each tube contains 1 oz (29.6 mL) of KeraStat® Cream, which contains 5% keratin protein incorporated into a cream base.

The provided document is a 510(k) summary for KeraStat® Cream. It focuses on demonstrating substantial equivalence to a predicate device (KeraStat® Gel) and a reference device (Biafine®), rather than presenting a study with specific acceptance criteria and performance data for the KeraStat® Cream's effectiveness in wound management.

Therefore, the document does not contain the acceptance criteria or a study that proves the device meets specific performance criteria related to its clinical efficacy in terms of wound healing endpoints.

Here's a breakdown of the requested information based on the provided text, indicating what is not available:

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

• Not Available: The document does not provide a table with specific acceptance criteria for clinical efficacy (e.g., wound size reduction, healing time, infection rates) or reported device performance against such criteria. The "Performance Data Summary of Non-Clinical Tests" lists types of tests (e.g., protein content, viscosity, pH, microbial contamination, stability) performed to ensure product quality and safety, but these are not clinical acceptance criteria for wound healing efficacy.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Available for clinical efficacy: The document mentions "Radiation Dermatitis Clinical Study", "Repeat Insult Patch Test", and "Skin Prick Test" as "human clinical testing". However, it does not provide details on the sample size for these tests, their design (retrospective or prospective), or data provenance. These clinical tests appear to be primarily for safety (e.g., sensitization, irritation) or to support specific indications like radiation dermatitis, not necessarily general wound healing efficacy benchmarks.

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/Not Available: This question typically applies to studies involving interpretation of medical images or diagnostic classification, where expert consensus establishes ground truth. Since this document is for a wound dressing and does not describe such a study for clinical efficacy, this information is not relevant or provided.

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

• Not Applicable/Not Available: Similar to point 3, this is relevant for studies involving subjective assessments or classifications by multiple readers, which is not described here for the clinical efficacy of the wound dressing.

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/Not Available: This device (KeraStat® Cream) is a medical device (wound dressing), not an Artificial Intelligence (AI) device. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant.

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

• Not Applicable/Not Available: This device is a wound dressing, not an algorithm, so this question is not relevant.

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

• Not Available for clinical efficacy: For the mentioned clinical tests (e.g., Radiation Dermatitis Clinical Study), the document does not specify how "ground truth" (e.g., actual wound status, healing progress) was established or measured. For biocompatibility and performance tests, the "ground truth" is typically defined by standardized ISO or USP methods.

8. The sample size for the training set

• Not Applicable/Not Available: This device is a wound dressing, not a machine learning model, so there is no training set in this context.

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

• Not Applicable/Not Available: As identified in point 8, there is no training set for this device.

In summary: The provided 510(k) summary primarily focuses on demonstrating that KeraStat® Cream is substantially equivalent to existing predicate and reference devices based on intended use, principles of operation, and technological characteristics (including biocompatibility and physical performance tests). It does not present a detailed clinical study with specific acceptance criteria and efficacy performance data in the way an AI or diagnostic device submission might. The "clinical tests" mentioned appear to be more geared towards safety and specific indications (like radiation dermatitis) rather than comprehensive efficacy endpoints for all listed indications.

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KeraStat® Gel is intended to provide a moist environment and absorb excess wound exudate. KeraStat® Gel is indicated for management of a number of partial thickness skin wounds such as: partial thickness (first and second degree) burns, severe sunburns, superficial injuries, cuts, and incisions/surgical wounds. Under the direction of a healthcare practitioner. KeraStat® Gel also may be used in the management of dry, light, and moderately exuding partial thickness wounds including: pressure (stage I-II) ulcers, venous stasis ulcers caused by mixed vascular etiologies, diabetic ulcers, donor sites, and grafts.

KeraStat® Gel is not indicated for full thickness (third degree) burns. This device will be available by prescription.

KeraStat® Gel is a sterile, non-implantable, water-based gelatinous (hydrogel) wound dressing intended to act as a protective covering in the management of a variety of partial thickness dermal wounds. KeraStat Gel is provided in a sterile, screw top tube for one-time use. Each tube contains 5 mL of KeraStat Gel, which contains 5% keratin protein rehydrated and polymerized in a water base, and is available by prescription from a healthcare professional.

Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the KeraStat® Gel device:

This document is a 510(k) summary, which focuses on demonstrating "substantial equivalence" to a predicate device, rather than proving the device meets specific performance acceptance criteria in the same way a PMA (Premarket Approval) would. Therefore, the information provided is geared towards showing similarity to an already approved device rather than standalone performance against pre-defined metrics.

1. Table of Acceptance Criteria and Reported Device Performance

Because this is a 510(k) submission based on substantial equivalence, explicit "acceptance criteria" for clinical performance metrics (like sensitivity, specificity, or improvement rates) are not typically defined or reported for the new device in the same way they would be for a novel device. Instead, the "acceptance criteria" are effectively that the new device (KeraStat® Gel) is demonstrated to be as safe and effective and performs as well as the legally marketed predicate device (Keratec Wound Dressings) through various non-clinical and clinical tests.

The document states:

• "Biocompatibility and device performance study results support the safety and effectiveness of KeraStat Gel. Biocompatibility, non-clinical, and clinical testing have confirmed that KeraStat Gel functions as intended without adverse effects."
• "KeraStat Gel is as safe and effective and performs as well as the legally marketed predicate device based on an evaluation of biocompatibility, bench, nonclinical, and clinical performance; any differences in technological characteristics outlined in Table 1 do not raise new questions about the safety and effectiveness of KeraStat Gel."

So, the "reported device performance" is essentially that it meets the safety and effectiveness profile of the predicate device, although no specific quantitative metrics are provided in this summary.

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

The document lists "Clinical testing: ● Repeat Insult Patch Test O - Skin Prick Test O" and "nonclinical, and clinical testing" under Performance Testing. However, it does not specify the sample size used for these clinical tests. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective) for any clinical or non-clinical studies.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This type of information is not applicable or not provided in this 510(k) summary. The clinical tests mentioned (Repeat Insult Patch Test, Skin Prick Test) are designed to assess direct physiological responses (e.g., allergic reactions) rather than requiring expert interpretation of diagnostic images or outcomes for establishing a "ground truth" in the way it might be needed for an AI/CAD decision support system. These tests are typically evaluated by qualified medical professionals (e.g., dermatologists or allergists), but the specific number and qualifications are not detailed here.

4. Adjudication Method for the Test Set

This information is not applicable or not provided. Since the primary clinical tests mentioned are patch and prick tests for biocompatibility (allergies/irritation), they don't typically involve adjudication methods like those used for expert consensus on image interpretation. The outcome of such tests is usually a direct observation of a physical reaction.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This information is not applicable. The KeraStat® Gel device is a wound dressing, not an AI or CAD (Computer-Aided Detection) system that assists human readers in interpreting data. Therefore, an MRMC study comparing human reader performance with and without AI assistance is not relevant to this device.

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

This information is not applicable. As stated above, KeraStat® Gel is a wound dressing, not an algorithm or AI device.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

For the biocompatibility aspects, the "ground truth" would be established by the direct physiological response observed during the Repeat Insult Patch Test and Skin Prick Test (e.g., presence or absence of a reaction) and possibly standard toxicological endpoints in animal studies. For device performance in wound healing, while not explicitly detailed how results are measured in this summary, the "ground truth" would typically relate to clinical assessment of wound healing, reduction in exudate, and absence of adverse events, observed during clinical use or in animal models (like the "Porcine thermal burn" mentioned). However, the specific methodology for establishing this in the context of clinical observations is not described.

8. The Sample Size for the Training Set

This information is not applicable or not provided. This is not an AI/ML device that requires a training set. If there were multiple studies performed, the sample sizes for participant enrollment in those studies are not detailed.

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

This information is not applicable. Since this is not an AI/ML device, there is no "training set" in that context.

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