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The EVOTECH™ Endoscope Cleaner and Reprocessor, a washer/disinfector, is indicated for use with high- level disinfectant CIDEX® OPA Concentrate and an enzymatic detergent (CIDEZYME GI) to achieve cleaning and high level disinfection of heat sensitive (>60°C) semi-critical endoscopes. Manual cleaning of medical devices (endoscopes) is not required prior to placement in the EVOTECH System when selecting those cycles that contain a wash stage. (Manual cleaning of mystical devices (endoscopes) is required when selecting the Disinfect only or Disinfect/Alcohol Flush Cycle.)

The EVOTECH™ Endoscope Cleaner and Re-processor was cleared under the Premarket Notification process (K040883) found substantially equivalent on March 15, 2005. Subsequent to that the EVOTECH ECR was granted a cleaning claim in Premarket Notification K061899 (found substantially equivalent on October 26, 2006). The system is designed to clean and disinfect endoscopes. The system performs tests to check for connection of endoscopes, for leaks in endoscopes, and for blockage of lumens. The device will clean and high-level disinfect endoscopes and provides for automated alcohol flush of the lumens. The system also has a self-disinfection cycle that can be selected (recommended to be performed every 5 days) to prevent the build up of biofilm in fluid pathways.

The provided text is a 510(k) summary for a Special 510(k) submission for the EVOTECH™ Endoscope Cleaner and Reprocessor. This type of submission is for modifications to a previously cleared device that do not affect the safety or effectiveness. As such, it does not typically include new clinical studies or detailed performance data against acceptance criteria for cleaning and high-level disinfection, but rather verification that the modifications do not negatively impact these established performances.

Therefore, many of the requested items (e.g., acceptance criteria, detailed device performance, sample sizes for test/training sets, expert qualifications, MRMC studies) are not applicable to this specific type of submission and the information provided.

However, I can extract information related to the modifications and the non-clinical tests performed to ensure they did not impact the device's original performance.

Here's a breakdown of what can be extracted and what is not provided:

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

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

• Not provided. The document focuses on demonstrating that modifications did not impact existing performance, rather than re-proving the device's primary function with new detailed studies. The "non-clinical tests" mentioned are specific to verifying the modifications.

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/Not provided. This submission is not likely to involve expert ground truth for image interpretation or diagnosis. The "ground truth" for the non-clinical tests would have been the established specifications and performance parameters for each modified component.

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

• Not applicable/Not provided. Adjudication methods are typically for clinical studies with subjective assessments. The tests described are objective engineering verifications.

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/Not provided. This is an endoscope cleaning and reprocessing device, not an AI-assisted diagnostic tool. Therefore, MRMC studies are not relevant.

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

• Not applicable/Not provided. This is a hardware device with associated software, not an AI algorithm.

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

• For the verification of modifications, the "ground truth" was based on:
  • Engineering specifications and compatibility testing: For material compatibility, dispensing volume, and reproducibility of the disinfectant dispenser.
  • Functional performance standards: For spray arm rotation/pattern, MEC monitor equivalence, and lid motor control safety.
  • Software validation protocols.

8. The sample size for the training set

• Not applicable/Not provided. This is not an AI/machine learning device.

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

• Not applicable/Not provided.

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