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The Revital-Ox PAA High Level Disinfectant Chemical Indicator is designed to determine whether the peractic acid concentration in the high-level disinfection (HLD) phase of the chosen reprocessing cycle of the enspire 300 Series AER employing Peracetic Acid (Revital-Ox PAA High Level Disinfectant) is above the minimum effective concentration (MEC) of 850 mg/L.

Revital-Ox PAA High Level Disinfectant Chemical Indicator is a single-use chemical indicator consisting of a polypropylene strip with indicator ink printed in a patch at one end. A clear, germicide-permeable laminate is applied over the reactive patch to protect the strip from damage during handling and to prevent the ink from leaching from the substrate.

One strip is used with each Cleaning and High-Level Disinfection (HLD) and HLD only cycle by placing the strip within the enspire 300 Series Automated Endoscope Reprocessor. At the end of the cycle, if the reactive patch has turned from the starting blue color to grey/tan, it was exposed to > 850 mg/L PAA min. which indicates an effective peracetic acid dose, i.e. 'Pass'.

This document describes the Revital-Ox PAA High Level Disinfectant Chemical Indicator and its performance testing to demonstrate substantial equivalence to a predicate device.

1. Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

The provided text does not specify the sample sizes used for each test set within the "Performance Testing" section. It also does not explicitly state the country of origin of the data or whether the studies were retrospective or prospective.

3. Number of Experts and Qualifications

The document mentions a "Blind Reader" study, which implies human interpretation. However, it does not specify the number of experts used, their qualifications, or their role in establishing ground truth for the device's color change interpretation.

4. Adjudication Method

The document does not describe any specific adjudication method used for the test set interpretation, such as 2+1 or 3+1 concensus.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

A MRMC comparative effectiveness study involving human readers and AI assistance is not applicable to this device. This device is a chemical indicator that changes color to signify a concentration level, not an AI-assisted diagnostic tool for human readers.

6. Standalone Performance

The performance testing described, particularly the "Comparative Sensitivity, Comparative Specificity, Analytic Sensitivity and Analytic Specificity Study," implicitly represents a standalone (algorithm only, though in this case, a chemical reaction and visual change) performance evaluation of the chemical indicator's ability to respond to peracetic acid concentrations. The "Blind Reader" study then assesses the human interpretation of this standalone performance.

7. Type of Ground Truth Used

The ground truth for this device's performance would primarily be the measured concentration of peracetic acid (PAA) in the liquid. The chemical indicator is designed to change color when the PAA concentration is above 850 mg/L. Therefore, the ground truth is established by chemical analysis of the PAA concentration in the test solutions or in the effluent from the AER.

8. Sample Size for Training Set

The concept of a "training set" is not applicable to this device. Chemical indicators function based on chemical reactions, not machine learning algorithms that require training data.

9. How Ground Truth for Training Set Was Established

As stated above, a "training set" is not applicable. The device's color change mechanism is an inherent chemical property, not something that is "trained." The ground truth for evaluating its performance is based on precisely controlled and measured concentrations of peracetic acid.

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The SYSTEM 1 endo Liquid Chemical Sterilant Processing System is intended for liquid chemical sterilization of cleaned, immersible, and reusable semi-critical heat-sensitive medical devices and their accessories in healthcare facilities.

The SYSTEM 1 endo Processor automatically dilutes the S40 Sterilant Concentrate to its use dilution (> 1820 mg/L peracetic acid), liquid chemically sterilizes the load during a controlled 6-minute exposure at 45.5 to 60°C and rinses the load with 0.2 micron filtered water.

The SYSTEM 1 endo Processor uses only S40 Sterilant Concentrate to liquid chemically sterilize medical devices.

The SYSTEM 1 endo Liquid Chemical Sterilant Processing System is a liquid chemical sterilization system, utilizing peracetic acid to process totally immersible semi-critical heat-sensitive medical devices and their accessories. The system consists of the SYSTEM 1 endo Processor and S40 Sterilant Concentrate, interchangeable Processing Trays/Containers, and Quick Connects.

The SYSTEM 1 endo Processor is an automated, self-contained device that uses S40 Sterilant Concentrate to create and maintain the conditions necessary for liquid chemical sterilization in 6 minutes. Following processing, the liquid chemically sterilized articles are rinsed with 0.2 micron filtered potable water and are ready for use or may be prepared for storage. The processor, which is computer controlled and continually monitored, provides printed documentation of each cycle. The SYSTEM 1 endo Processor uses only S40 Sterilant Concentrate. Upon loading the single-use cup, the active ingredient in S40 - peracetic acid - is combined with inert ingredients (builders) to form a use dilution which inhibits corrosion of metals, polymers and other materials.

The interchangeable processing trays/containers are made to accommodate a variety of semi-critical instrument types and models. Each container is designed to maintain instruments in position while specific SYSTEM 1 endo Quick Connects, if required, facilitate delivery of the sterilant use-solution and rinse water to internal channels.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Points not explicitly addressed in the provided text:

The provided text (a 510(k) Summary for a medical device) focuses on demonstrating substantial equivalence to a predicate device, rather than a typical clinical study report for AI/machine learning devices. Therefore, several points in your requested information are not applicable or explicitly mentioned in this type of document.

Here's how the remaining points relate to the provided text:

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

• Test Set Sample Size: Not explicitly stated for each test. For "In-Use Testing," it mentions "Clinically used, cleaned semi-critical heat-sensitive medical devices," implying a sample was used but the size isn't quantified. For Water Filter Performance, refers to "numerous Liquid Chemical Sterilization Cycles and Diagnostic Cycles." For Cycle Qualification, it states "three (3) cycles each, Liquid Chemical Sterilization and Diagnostic."
• Data Provenance: Not explicitly stated. The document is submitted to the FDA in the USA, suggesting the testing was likely conducted in accordance with US regulatory standards, but the physical location or origin of the samples/data is not mentioned.
• Retrospective or Prospective: Not explicitly stated, though "In-Use Testing" implies real-world usage, which could be prospective if the testing was specifically set up for this submission.

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 for this type of device. The device is a liquid chemical sterilant processing system. Ground truth is established through microbiological testing (e.g., absence of viable microorganisms) and engineering verification, not human expert interpretation of images or other subjective data. No experts (like radiologists) are involved in establishing ground truth for this device's performance.

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

• Not applicable for this type of device. Adjudication methods are typically used in studies where human interpretation or classification is compared, often with disagreements needing resolution. For a sterilization system, the performance is measured objectively against predefined microbial reduction targets or engineering specifications.

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 device is not an AI-assisted diagnostic tool that involves human readers.

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

• Partially applicable, but not in the AI sense. The "device performance" in this context (sterilization efficacy, electrical safety, filter performance, software operation) is inherently "standalone" in that it's the system itself performing its intended function. There isn't an "algorithm-only" performance study distinct from the device's operational performance, as the device is the sterilizing algorithm/process. The tests described (e.g., In-Use Testing, Water Filter Performance) evaluate the device's standalone capability.

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

• Microbiological Negativity / Sterility: For the "In-Use Testing," the ground truth of "effectively liquid chemically sterilized" implies the absence of viable microorganisms (i.e., sterility) after processing. This would typically be verified through standard microbiological culture methods.
• Engineering Specifications: For Electrical Safety, Water Filter Performance, Water Filter Integrity Test, Cycle Qualification, and Software Validation, the ground truth is adherence to predefined engineering specifications, industry standards (e.g., UL standards), or functional requirements.

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device that requires a training set. The device operates based on fixed chemical and physical parameters, not learned data.

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

• Not applicable. No training set is used for this device.

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