Search Results

Irrisept® Antimicrobial Wound Lavage is intended for mechanical cleansing and removal of debris, dirt and foreign materials, including microorganisms from wounds.

Irrisept® Antimicrobial Wound Lavage is a single-use, manual, self-contained irrigation device comprised of a bottle of 0.05% Chlorhexidine Gluconate (CHG) in 99.95% Sterile Water for Irrigation, United States Pharmacopeia (USP) and accessories for irrigation. The solution is aseptically-filled in a Blow-Fill-Seal (BFS) bottle. The CHG acts as a preservative to inhibit microbial growth in the solution.

The provided document is a 510(k) summary for the Irrisept® Antimicrobial Wound Lavage (150 mL), which is a modified version of a previously cleared device (450 mL Irrisept® Antimicrobial Wound Lavage, K210536). This submission asserts substantial equivalence to the predicate device, meaning the new device generally adheres to the same performance standards established for the predicate.

The document does not detail specific acceptance criteria values or a standalone study demonstrating the device's meeting of these criteria in the context of a new clinical or performance trial for effectiveness in all aspects. Instead, it relies on demonstrating that the modified device performs equivalently to the predicate device through various tests and that the modifications do not raise new safety or effectiveness concerns.

Here's an analysis based on the provided text, addressing your specific questions to the extent the document allows:

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

The document does not explicitly state numerical acceptance criteria with corresponding reported performance values for each functional aspect. Instead, it lists various tests performed and asserts that the device (150 mL version) demonstrated the "same level of performance as the predicate device" or was "equivalent to the predicate device" in functional testing.

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

The document does not specify sample sizes for any of the tests mentioned (e.g., number of units tested for functional performance, biocompatibility, etc.).
The data provenance is not explicitly stated in terms of country of origin or whether it's retrospective or prospective. Given that this is a 510(k) summary for a modified device, the testing would be conducted prospectively for the new iteration to demonstrate equivalence.

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

This type of information is not applicable to this document. The document describes a medical device (wound lavage) and its physical and chemical properties and functional equivalence to a predicate device, not a diagnostic or AI-driven decision support system that requires expert ground truth establishment for a test set.

4. Adjudication method for the test set

This is not applicable for the same reasons as point 3.

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 lavage, not an AI or imaging diagnostic tool that would be part of a MRMC study.

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 medical device, not an algorithm.

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

For the performance testing, the "ground truth" would be established by the validated methods described (e.g., ISO standards for biocompatibility, USP methods for antimicrobial effectiveness and sterility, custom tests for functional equivalence to the predicate). It does not involve expert consensus, pathology, or outcomes data in the way a diagnostic device would. For the functional testing, "custom tests designed to show the mechanical removal of wound debris, including microorganisms, is equivalent to the predicate device" implies a controlled experimental setup to measure the efficacy of removing debris, with the predicate device's performance serving as the benchmark.

8. The sample size for the training set

This is not applicable. The device is not an AI or machine learning model that requires a training set.

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

This is not applicable for the same reasons as point 8.

Ask a specific question about this device