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The BD ChloraShield IV Dressing with CHG antimicrobial 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 integrated with 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) Summary for a medical device called the "BD ChloraShield IV Dressing with CHG antimicrobial." It describes the device, its intended use, and the rationale for its substantial equivalence to a predicate device.

It does NOT contain information about acceptance criteria or a study proving that a device meets acceptance criteria for an AI/algorithm-based system.

The document focuses on a change in the sterilization method (from gamma radiation to Ethylene Oxide gas) for an existing medical dressing. The performance testing section (Section 7) states that "Performance testing for the BD ChloraShield™ IV Dressing with CHG antimicrobial utilized the same test methodology as the predicate device within K113836." It emphasizes that the CHG concentration, materials, and manufacturing methods remain unchanged and that the sterility requirements (Sterility Assurance Level - SAL) of 10^-6 are met without compromising the device's performance.

Therefore, I cannot extract the requested information regarding AI/algorithm acceptance criteria or study details from this document. The questions about sample sizes, expert qualifications, ground truth establishment, MRMC studies, or standalone performance are not relevant to the content of this 510(k) summary.

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

The 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.

The provided text describes a Special 510(k) submission for the "ChloraShield IV Dressing with CHG antimicrobial" due to a change in packaging material. The study reported focuses on verifying that this packaging change does not negatively impact the device's sterility and functionality.

Here's an analysis of the requested information based on the provided text:

Acceptance Criteria and Reported Device Performance

Note: The primary acceptance criterion explicitly stated and tested related to a numerical value is the Sterility Assurance Level. For Seal Strength and Bubble Leak Test, the text only states they were "verified" or "performed" without providing specific target values or quantitative results. The overarching acceptance criterion is that the new packaging "did not negatively impact the sterility assurance level" and that "the performance, functionality and manufacturing methods remain unchanged."

Study Information

The document describes a verification/validation activity rather than a traditional clinical study with a test set of patients.

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

• Sample Size (Test Set): Not explicitly stated for any of the tests (Sterility, Seal Strength, Bubble Leak Test).
• Data Provenance: The tests were conducted internally by Avery Dennison Belgie, b.v.b.a. No information on country of origin of data or whether it was retrospective or prospective in a clinical sense. These are laboratory/engineering tests.

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

• Experts: Not applicable. Ground truth for sterility or mechanical integrity tests is established by standardized laboratory methods and measurements, not expert consensus in the way a clinical image analysis study might.
• Qualifications: Not applicable for this type of testing.

4. Adjudication method for the test set:

• Adjudication Method: Not applicable. These are objective laboratory tests.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• MRMC Study: No, this type of study was not done. The device is a wound dressing, and the study described focuses on the impact of a packaging change on its physical and microbiological properties, not on reader effectiveness.

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

• Standalone Performance: Not applicable. This device is a physical medical device, not an algorithm, so "standalone performance" in the context of AI algorithms does not apply. The tests described are for the device's intrinsic properties.

7. The type of ground truth used:

• Ground Truth:
  • Sterility: Established by microbiology testing to confirm the absence of viable microorganisms, adhering to a defined Sterility Assurance Level (SAL) of 10⁻⁶. This is an objective, laboratory-derived ground truth.
  • Seal Strength and Bubble Leak Test: Established through mechanical testing methods, likely comparing results against established engineering specifications or the performance of the original device packaging. This is an objective, laboratory-derived ground truth.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. This is not an AI/ML algorithm that requires a training set.

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

• Ground Truth for Training Set: Not applicable. As there is no training set.

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