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Antimicrobial Silicone PHMB Foam Wound Dressings are indicated for use in the management of

• · post-surgical incisions,
• · pressure sores,
• · venous stasis ulcers,
• · diabetic ulcers,
• · donor sites.
• · abrasions,
• · lacerations,
• · superficial and partial thickness burns,
• · dermatologic disorders,
• · other wounds inflicted by trauma and,
• · as a secondary dressing or cover dressing for packed wounds.

Antimicrobial Silicone PHMB Foam Wound Dressing, is a polyurethane foam trilaminate dressing impregnated with Polyhexamethylene Biguanide (PHMB), an agent that protects the dressing from bacterial penetration and colonization. The foam in the dressing has a microporous hydrophilic foam structure that absorbs wound exudate and maintains a moist wound healing environment.

Based on in vitro performance data, the Antimicrobial Silicone PHMB Foam Wound Dressing provides a barrier to bacterial penetration through the dressing and the PHMB prevents colonization and proliferation of bacteria, yeast and mold within the dressing for up to 7 days. Antimicrobial Silicone PHMB Foam Wound Dressing, when tested in-vitro has demonstrated to be effective against gram positive bacteria, gram negative bacteria, yeast and mold challenge organisms within the dressing.

The perforated wound contact layer contains a gentle silicone adhesive that provides secure, nonirritating adhesion and supports non-traumatic removal during dressing changes.

The device is presented in a border (adhesive) version. The dressing is supplied sterile in a range of sizes between 10.24 in2 (64cm) to 64 in2 (400cm).

The provided text describes a 510(k) submission for a medical device called "Antimicrobial Silicone PHMB Foam Wound Dressing." The submission aims to demonstrate substantial equivalence to a predicate device, "Silicone PHMB Foam Wound Dressing (K190819)." The key difference is the addition of an antimicrobial claim for the subject device.

Here's an analysis of the acceptance criteria and supporting study information based on the provided text:

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

The document does not explicitly state acceptance criteria in the typical numerical performance thresholds (e.g., sensitivity > X%, specificity > Y%). Instead, the "acceptance" is focused on demonstrating substantial equivalence to an existing predicate device, particularly concerning the newly added antimicrobial claim.

Acceptance Criteria (Implicit from the 510(k) submission):

• Antimicrobial Efficacy: The modified device must demonstrate efficacy against gram-positive bacteria, gram-negative bacteria, yeast, and mold within the dressing.
• Identical Design, Materials, and Manufacturing Process: The subject device must be identical to the predicate device in these aspects, except for modifications related to the antimicrobial claim.
• Substantially Equivalent Intended Use and Performance Characteristics: The device's overall intended use and other performance (biocompatibility, absorption, MVTR, waterproofness, peel resistance, bacterial barrier, distribution) must be consistent with the predicate device.
• No New Questions of Safety or Effectiveness: The modifications should not introduce new safety or effectiveness concerns.

Reported Device Performance (from "Performance Testing Summary" and "Comparison of Technological Characteristics"):

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

The document mentions in-vitro testing for antimicrobial efficacy. It does not provide a specific "sample size" in terms of number of patient cases or imaging data. Instead, it refers to testing against "mold challenge organism," "gram positive bacteria, gram negative bacteria, yeast and mold challenge organisms."

• Sample Size: Not applicable in the context of patient cases or images for this type of in-vitro study. The "sample" would be the wound dressing material itself and the microbiological cultures. Specific numbers of microbial samples or dressing replicates are not provided.
• Data Provenance: In-vitro testing. No country of origin is specified for the testing itself, but the manufacturer is based in the UK. The study is prospective in the sense that the testing was conducted specifically for this submission, although it followed a "well-established modified AATCC TM 100 method previously used for the predicate device."

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 is not applicable to the type of study presented. The ground truth for antimicrobial efficacy is established through standardized objective in-vitro microbiological testing methods (modified AATCC TM 100) using known challenge organisms, not through expert consensus or interpretation of patient data.

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

This is not applicable to the type of study presented. Adjudication methods like 2+1 or 3+1 are used for establishing ground truth from human expert interpretations, typically in diagnostic imaging or clinical trials. Here, the ground truth is determined by the results of the specific in-vitro microbiological assay.

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 is not applicable. The device is a wound dressing, not an AI-assisted diagnostic tool.

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

This is not applicable. The device is a physical wound dressing, not an algorithm.

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

For the antimicrobial efficacy claim, the ground truth is established through objective microbiological culture results using a modified AATCC TM 100 method. This method quantifies the reduction or prevention of microbial growth on the dressing.

For the other performance characteristics (Biocompatibility, Absorption, MVTR, Waterproofness, Peel Resistance, Bacterial Barrier, Distribution), the ground truth was established by various standardized test methods (e.g., ISO 10993-1, USP 41-NF36, BS EN 13726 series, ASTM D6282-11, ASTM D4169).

8. The sample size for the training set

This is not applicable. There is no "training set" as this is not a machine learning or AI device. The testing conducted is for verification of physicochemical and antimicrobial properties.

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

This is not applicable, as there is no training set mentioned or implied for this device.

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Silicone PHMB Foam Wound Dressings are indicated for use in the management of post-surgical incisions, pressure sores, venous stasis ulcers, diabetic ulcers, donor sites, abrasions, 1st and 2nd degree burns, dermatologic disorders, other wounds inflicted by trauma, and as a secondary dressing for packed wounds.

The subject device, Silicone PHMB Foam Dressing, is a polyurethane foam trilaminate dressing impregnated with Polyhexamethylene Biguanide (PHMB), an agent that protects the dressing from bacterial penetration and colonization. The foam in the dressings has a microporous hydrophilic foam structure that absorbs wound exudate and maintains a moist wound healing environment.

Based on in vitro performance data, the Silicone PHMB Foam Wound Dressing provides a barrier to bacterial penetration through the dressing and the PHMB prevents colonization and proliferation of bacteria within the dressing for up to 7 days. Silicone PHMB Foam Wound Dressing, when tested in-vitro has demonstrated to be effective against the following bacteria (MRSA, Streptococcus pyogenes, VRE, Escherichia coli, Klebsiella pneumoniae, Serratia marcescens) and yeast (Candida albicans) challenge organisms within the dressing.

The perforated wound contact layer contains a gentle silicone adhesive that provides secure, non-irritating adhesion and supports nontraumatic removal during dressing changes.

The device is presented in a border (adhesive) version. The dressing is supplied sterile in a range of sizes between 10.24 in2 to 64 in2.

The provided text describes a 510(k) submission for a medical device, the "Silicone PHMB Foam Wound Dressing." This type of submission aims to demonstrate substantial equivalence to a legally marketed predicate device, rather than proving efficacy through clinical outcome studies with specific acceptance criteria as might be seen for novel devices or high-risk applications.

Therefore, the information typically requested in your prompt (e.g., sample size for test/training sets, number of experts for ground truth, MRMC studies, effect sizes, adjudication methods, type of ground truth for training) is not applicable in the context of this 510(k) submission for a wound dressing.

Instead, the submission focuses on performance testing (in-vitro and animal testing) and biological evaluation to demonstrate safety and functional equivalence to the predicate device.

Here's what can be extracted from the document regarding the device's performance and the supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

Since this is a 510(k) for a wound dressing, "acceptance criteria" are generally framed as demonstrating equivalence to a predicate device in terms of design, materials, indications for use, and performance characteristics. The specific metrics for "device performance" are primarily related to its physical and antimicrobial properties rather than diagnostic accuracy metrics.

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

• Sample Size: Not specified in terms of "test set" for human performance, as this is a device for physical wound management. The performance data relied on in-vitro and animal testing. Specific numbers of samples or animals are not provided in this summary document.
• Data Provenance: Not explicitly stated but the applicant is based in the UK (Advanced Medical Solutions Ltd, Winsford, Cheshire, CW7 3RT GB). The studies conducted would typically comply with international standards (e.g., ISO for biological evaluation). The document does not specify if the studies were retrospective or prospective, but in-vitro and animal studies are typically prospective experimental designs.

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

• Not Applicable. This is not a diagnostic device requiring expert interpretation for ground truth. Ground truth for in-vitro antimicrobial effectiveness would be based on laboratory microbiological assays, and for physical properties, on engineering and material science standards.

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

• Not Applicable. No human interpretation or adjudication process is described for this device's performance evaluation.

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/diagnostic device.

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

• Not Applicable. This is not an algorithmic device. The "standalone" performance refers to the intrinsic properties of the wound dressing (e.g., absorbency, antimicrobial activity).

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

• For Antimicrobial Efficacy: Ground truth established via
  • In-vitro microbiological assays: (e.g., confirming inhibition of bacterial/yeast growth on/in the dressing).
• For Biocompatibility: Ground truth established via
  • Compliance with International Standard ISO 10993-1: Biological evaluation based on established protocols and endpoints (e.g., cytotoxicity, sensitization, irritation) in animal models or in-vitro tests.
• For Physical Performance: Ground truth established via
  • Standardized physical testing methods: (e.g., for absorbency, fluid handling, peel adhesion), often against industry benchmarks or the predicate device's measured properties.

8. The sample size for the training set:

• Not Applicable. This is not a machine learning/AI device, so there is no "training set."

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

• Not Applicable. As there is no training set for an AI/ML algorithm.

Ask a specific question about this device

PHMB Foam Wound Dressings are indicated for use in the management of post-surgical incisions, pressure sores, venous stasis ulcers, diabetic ulcers, donor sites, abrasions, 1st and 2nd degree burns, dermatologic disorders, other wounds inflicted by trauma and, as a secondary dressing for packed wounds.

The subject device, PHMB Foam Wound Dressing, is a polyurethane foam impregnated with Polyhexamethylene Biguanide (PHMB), an agent that protects the dressing from bacterial penetration and colonization. The foam in the dressings has a microporous hydrophilic foam structure that absorbs wound exudate and maintains a moist wound healing environment. Based on in vitro performance data, the PHMB Foam Wound Dressing provides a barrier to bacterial penetration through the dressing and the PHMB prevents colonization and proliferation of bacteria within the dressing for up to 7 days. PHMB Foam dressing, when tested in-vitro has demonstrated to be effective against the following three gram positive bacteria (MRSA, MRSE, VRE), three gram negative bacteria (Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa) and two yeast (Candida albicans, Rhodotorula mucilaginosa) challenge organisms within the dressing. The device is available in Non-border (non-adhesive) and Border (adhesive) versions. The dressing is supplied sterile in a range of sizes between 4 in squared to 64 in squared.

This is a 510(k) premarket notification for a medical device, specifically a PHMB Foam Wound Dressing. The document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed clinical study with acceptance criteria for an AI/algorithm-based diagnostic device.

Therefore, the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, and ground truth for an AI device is not applicable to this document.

The document describes the device's in vitro performance against various bacteria and yeast, and biological evaluation, but these are not the type of studies relevant to the detailed AI/algorithm questions.

Here's why each specific point you asked for is not available in the provided text:

1. A table of acceptance criteria and the reported device performance: This document describes the performance of the wound dressing in terms of its ability to absorb exudate, maintain a moist environment, and prevent bacterial colonization in vitro. It does not present acceptance criteria for an AI's diagnostic performance (e.g., sensitivity, specificity, AUC).
2. Sample sized used for the test set and the data provenance: The document mentions in vitro performance data and animal testing, but not clinical test sets or data provenance in the context of an AI device.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This is irrelevant for a wound dressing's in vitro or animal testing.
4. Adjudication method for the test set: Not applicable for this type of device submission.
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 relates to AI-assisted human reading, which is not applicable here.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is not an AI algorithm.
7. The type of ground truth used: For this device, the "ground truth" would be established through laboratory testing (e.g., bacterial inhibition, fluid absorption measurements) and biological evaluation for safety, not expert consensus or pathology on images.
8. The sample size for the training set: Not applicable as there is no AI training.
9. How the ground truth for the training set was established: Not applicable as there is no AI training.

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