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The ReliaTect™ Post-Op Dressing with CHG is intended to cover and protect a wound caused by percutaneous medical devices such as drains, chest tubes, orthopedic pins, fixtures, and wires.

ReliaTect™ may also be used to cover and secure a primary dressing.

ReliaTect™ inhibits microbial growth within the dressing and prevents external contamination.

The ReliaTect™ Post-Op Dressing with CHG is a transparent adhesive dressing integrated with Chlorhexidine Gluconate (CHG), a well-known antiseptic agent with broad-spectrum antimicrobial activity.

The provided document is a 510(k) summary for the ReliaTect™ Post-Op Dressing with CHG. This device is a medical dressing, not an AI/ML powered device, so information typically requested for AI/ML device studies (such as sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC studies, standalone performance, training set details) is not applicable or available in this document.

However, I can extract information related to the acceptance criteria and performance testing that was conducted for this device.

1. Table of Acceptance Criteria and Reported Device Performance

The document states, "The acceptance criteria were met for all characteristics and comparison against the predicate demonstrated equivalent performance." It also mentions "bench testing studies, including antimicrobial efficacy, demonstrate the two devices have comparable performance."

While specific numerical acceptance criteria values are not provided, the following tests were conducted, and the device met the criteria and showed equivalent performance to the predicate device:

2. Sample size 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 as it pertains to clinical studies often conducted for AI/ML devices. The testing mentioned (bench testing, in vitro testing, and a porcine study) are laboratory and animal studies, not human clinical trials with specific test sets in the context of AI/ML.

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 and not provided. The device is a physical dressing, and its performance was assessed through laboratory and animal studies rather than expert-derived ground truth as would be used for diagnostic AI/ML systems.

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

Not applicable and not provided for the reasons stated above.

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 and not provided. This is a physical medical device, not an AI-powered diagnostic tool engaging human readers.

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

Not applicable and not provided for the reasons stated above.

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

The "ground truth" for this device's performance was established through:

• Bench Testing: Objective measurements against established physical and chemical standards for properties like fluid handling, adhesion, and moisture transmission.
• In vitro Testing: Laboratory culture results for antimicrobial efficacy, demonstrating log reduction against specific microorganisms.
• Animal Study: Direct observation and evaluation of wound healing in a porcine model, with performance compared to a predicate device.

8. The sample size for the training set

Not applicable and not provided. This is not an AI/ML device that requires a training set.

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

Not applicable and not provided for the reasons stated above.

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The BD ChloraShield IV Dressing with CHG antimicrobial, per K152923, is intended to cover and protect catheter sites and to secure devices to the skin. Common applications include securing IV catheters, other intravascular catheters and percutaneous devices.

The BD ChloraShield IV Dressing with CHG antimicrobial consists of a transparent adhesive dressing with integrated Chlorhexidine Gluconate (CHG), a well known antiseptic agent with broad-spectrum antimicrobial activity, which serves as a preservative within the dressing.

This document is a 510(k) premarket notification for a medical device called the "BD ChloraShield IV Dressing with CHG antimicrobial". It describes a special 510(k) application, which is used for modifications to a previously cleared device where the modification does not affect the indications for use or the fundamental scientific technology of the device.

The core purpose of this document is to demonstrate "substantial equivalence" to a predicate device (K113836, Benehold CHG Transparent Film Dressing) after a specific change: expanding the specification for Chlorhexidine Gluconate (CHG) content in the dressing.

There is no information in this document about the use of AI, machine learning, or any form of algorithmic performance that would necessitate the detailed acceptance criteria and study design requested in the prompt.

The "performance testing" section (Section 7) refers to:

• Antimicrobial efficacy testing to the requirements set forth within USP 51.
• Verification/validation activities confirming that the specification change was "well within the requirements".
• Antimicrobial efficacy test results demonstrating conformance.

This is a chemical/material performance study, not a performance study of an AI/ML diagnostic or assistive device. Therefore, I cannot extract the requested information regarding AI/ML performance, ground truth establishment, expert review, or MRMC studies, as those concepts are irrelevant to this specific device and its regulatory submission.

The prompt asks for acceptance criteria and study details related to an AI/ML device, which this document is clearly not about.

As such, I cannot fulfill the request in the way it is structured. I can only confirm that the document describes a regulatory submission for an IV dressing and indicates that performance testing involved antimicrobial efficacy testing, demonstrating the modified CHG specification still met the requirements of the original submission.

No information regarding AI/ML performance, ground truth, experts, or MRMC studies is present in the provided text.

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