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Irrisept® Antimicrobial Wound Lavage, Wound Solution Kit 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, self-contained irrigation device comprised of a 450 mL 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, Wound Solution Kit (K240552). It outlines the device's characteristics and compares it to a predicate device (Irrisept Antimicrobial Wound Lavage, K210536) to demonstrate substantial equivalence.

Based on the provided text, here's an analysis of the acceptance criteria and study information:

Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with numerical performance targets in the way one might expect for a diagnostic or AI-driven device (e.g., sensitivity, specificity, accuracy thresholds). Instead, the acceptance criteria are implicitly defined by demonstrating that the subject device's performance is equivalent to the predicate device in terms of safety and effectiveness, despite a minor modification (inclusion of sterile accessories). The underlying "performance" refers to the functional capabilities and safety profiles as evaluated through various standards and tests.

Here's an attempt to structure this information based on the provided text:

The overall acceptance criterion is "Substantial Equivalence" to the predicate device (K210536), meaning the device does not raise new safety or effectiveness questions. The rationale states: "The indication for use, intended use, principles of operation, and performance have not been altered. The minor change to add the existing Irrisept device (450 mL) with sterile accessories for use with powered irrigation does not raise any new or different questions of safety or effectiveness."

Study Details:

The provided document describes a submission for substantial equivalence for a medical device (Irrisept Antimicrobial Wound Lavage, Wound Solution Kit, K240552), not a study proving device efficacy in a clinical setting in the way one would analyze a new drug or diagnostic algorithm. Rather, it focuses on demonstrating that a modified version of an already cleared device is as safe and effective as the original. This is a common regulatory pathway for devices.

Here's how the other points apply or don't apply to this type of submission:

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

   • This submission relies heavily on bench testing and standard conformity assessments rather than "test sets" of patient data. For example, tests like Biocompatibility (ISO 10993), Preservative Antimicrobial Effectiveness (USP ), Endotoxins (USP ), Sterility (USP ), Packaging, and Functional Testing were performed.
   • The "samples" would be units of the device and its accessories subjected to these tests. The document doesn't specify the exact number of units or lot numbers used for each specific test, but implies that adequate samples were tested per the relevant standards.
   • Data Provenance: The tests are generally conducted in a laboratory setting. There is no mention of country of origin for any "data set" as might be seen for clinical trials. Some standards (e.g., from USP or ISO) are internationally recognized.

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

   • This concept is not applicable in this context. There is no "ground truth" to be established by experts in the sense of diagnosing a disease or interpreting an image for a test set. The validation is against established scientific and regulatory standards for device performance and safety (e.g., ISO, USP, ASTM). Experts involved would be those performing or supervising the laboratory tests, and their qualifications would be in areas like microbiology, toxicology, sterilization science, and engineering, demonstrating compliance with the specified standards.

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

   • This concept is not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies, particularly for diagnostic devices where subjective human interpretation needs to be standardized or resolved (e.g., multiple radiologists reviewing images). For this device, performance is evaluated against objective, measurable criteria defined by the listed standards.

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:

   • No, an MRMC comparative effectiveness study was not done. This device is a wound lavage solution and kit, not an AI-assisted diagnostic or therapeutic tool. Therefore, concepts like "human readers" or "AI assistance" are entirely irrelevant to this submission.

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

   • No, this is not applicable. This device is a physical medical device (a wound lavage solution and kit). It does not involve any algorithms or software that would have a standalone performance.

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

   • The "ground truth" here is defined by compliance with established international and national standards (ISO, USP, AAMI, ASTM) for safety, materials, manufacturing, sterilization, and functional performance. For example:
     • Biocompatibility: Ground truth is defined by the toxicological and biological response criteria specified in ISO 10993.
     • Sterility: Ground truth is "sterile" as defined by USP and validated by ISO 11135 for EO sterilization.
     • Microbial reduction: Ground truth for preservative effectiveness is defined by USP criteria for inhibiting microbial growth.
     • Functional equivalence: "Custom tests designed to show the mechanical removal of wound debris, including microorganisms, is equivalent to the predicate device." The "ground truth" for these custom tests would be the established performance characteristics of the predicate device.

8. The sample size for the training set:

   • Not applicable. This is not an AI/ML 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, there is no ground truth for a training set.

In summary, this 510(k) submission focuses on demonstrating substantial equivalence of a modified physical medical device to a previously cleared one, rather than presenting a clinical study with outcome-based performance metrics usually associated with AI or novel diagnostic technologies. The "acceptance criteria" are compliance with relevant safety and performance standards.

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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

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 450mL bottle of 0.05% Chlorhexidine Gluconate (CHG) in 99.95% Sterile Water for Irrigation, United States Pharmacopeia (USP) and an applicator (labeled Irriprobe®). 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 text describes the Irrisept Antimicrobial Wound Lavage device and its 510(k) submission for clearance. The submission focuses on demonstrating substantial equivalence to a predicate device, particularly by specifying the removal of "microorganisms" through mechanical cleansing.

However, the documentation does not contain information related to an AI/ML medical device, nor does it conduct studies involving human reader performance, expert consensus on images, or training/test set data and ground truth establishment typically associated with such device evaluations.

Therefore, I cannot populate the requested table and answer the specific questions about acceptance criteria and the study proving the device meets it, as they pertain to AI/ML device performance metrics which are not discussed in this medical device submission.

The document primarily focuses on demonstrating that the device is substantially equivalent to legally marketed predicate devices based on:

• Intended Use: Minor modification to explicitly include "microorganisms" in the removal of wound debris.
• Technological Characteristics: The proposed device remains largely unchanged from its primary predicate (Irrisept Wound Debridement and Cleansing System, K202222) in terms of solution composition, mechanism of action, how supplied, applicator, sterilization, and biocompatibility.
• Performance Testing: Extensive list of standard medical device performance tests (e.g., sterilization, biocompatibility, packaging integrity, shelf-life, endotoxin, pyrogen testing) confirming it performs as safely and effectively as the predicate. The only new specific performance claim for this 510(k) is "mechanical action equivalent to the predicate devices, demonstrating that the fluid dispensed during the use of the device is sufficient to mechanically remove debris, including microorganisms, from wounds." This implies a physical/mechanical study, not an AI/ML performance study.

Given the context, here's what can and cannot be answered:

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

This document does not present acceptance criteria and performance in the format of an AI/ML device (e.g., sensitivity, specificity, AUC). Instead, the "acceptance criteria" are implied by meeting various medical device standards and demonstrating equivalence to a predicate device.

Acceptance Criteria (Implied by Substantial Equivalence Basis) & Reported Performance:

Regarding the other points, they are not applicable to this submission:

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

• Not applicable. This is a medical device clearance based on substantial equivalence and standard performance testing, not an AI/ML performance study with a test set of data. The "mechanical action" testing would involve physical samples/models, not digital data sets.

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. No "ground truth" derived from expert consensus on images is mentioned or required for this type of device (wound lavage).

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

• Not applicable. No AI/ML test set or expert adjudication process is described.

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/ML device assisting human readers. It's a wound lavage device.

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

• Not applicable. This is not an algorithm.

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

• Not applicable in the context of AI/ML. The "ground truth" for this device would be its physical/chemical properties and its ability to mechanically remove debris, established through validated laboratory tests and engineering studies, not clinical outcomes or expert image interpretation.

8. The sample size for the training set

• Not applicable. There is no AI/ML model or training set.

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

• Not applicable. There is no AI/ML model or training set.

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