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The Single Use Cleaning Adapter is intended to be used only to pre-clean the endoscope's air/water channel post-procedure, and not to be used during a patient procedure.

The Defendo Single Use Cleaning Adapter for Olympus Endoscopes is a single use, non-sterile disposable valve that fits onto the air/water cylinder of Olympus endoscopes (that do not contain a balloon channel). It allows air and water to be flushed through the endoscope's air/water channels after an endoscopic procedure is completed to remove debris. The adapter is not intended to be used with patients and a warning tag comes with the device providing this information. The materials of the valve are non-patient contacting. The adapter is used post-procedure to pre-clean the endoscope before it goes thru high-level disinfection and/or sterilization. The adapter is attached to the air/water channel of an endoscope. When the adapter is attached to the endoscope, air can flow down the channel of the endoscope. If water is desired to flow down the channel, the device is depressed. When released, air will once again flow down the endoscope channel. The Defendo Olympus Single-Use Cleaning Adapter for Olympus Endoscopes assembly consists of a cap, a spring, a spring cup, an overmolded boot, the cleaning valve stem, the valve stem backflow umbrella valve, and valve stem sealing gaskets and a warning label.

The provided document describes a 510(k) premarket notification for a medical device (Defendo Single Use Cleaning Adapter for Olympus Endoscopes) and uses the term "acceptance criteria" in the context of non-clinical performance testing. However, the document does not detail a study proving that the device meets acceptance criteria related to an AI/ML component or algorithmic performance, as would be expected for a product with an AI/ML component.

Instead, the "acceptance criteria" mentioned refer to engineering and performance specifications for a mechanical device. The information provided is about a physical cleaning adapter, not a software or AI/ML algorithm.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, type of ground truth, training set size and ground truth establishment) are not applicable to the device described in this 510(k) submission, as it is a physical, non-AI medical device.

I will populate the table and answer the questions based on the information available in the document, while explicitly stating when information is not present or not applicable due to the nature of the device.

Acceptance Criteria and Device Performance for Defendo Single Use Cleaning Adapter for Olympus Endoscopes

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not specified in the document. The testing described is for a physical device, and the "sample size" would refer to the number of physical units tested, which is not detailed.
• Data Provenance: Not applicable in the context of clinical AI/ML data. The "data" are results from mechanical and functional tests of the device. The testing was non-clinical, likely conducted in a lab environment.

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

• Not Applicable. This device is a physical cleaning adapter, not an AI/ML system requiring expert-adjudicated ground truth labels for a test set. The "ground truth" for its performance is determined by engineering specifications and direct physical measurements.

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

• Not Applicable. No human adjudication method (like those used for clinical image labeling) is relevant for the non-clinical performance tests of this mechanical device.

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. No MRMC study was conducted as this is a mechanical medical device, not an AI/ML system designed to assist human readers.

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

• Not Applicable. This device is not an algorithm. Its performance is evaluated through direct physical and functional tests.

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

• Not Applicable. The "ground truth" for this device's performance is objective engineering and functional specifications (e.g., specific flow rates, force measurements, presence/absence of leaks, breakage strength). It does not involve clinical "ground truth" like pathology or outcomes data.

8. The sample size for the training set:

• Not Applicable. This is a physical device, not an AI/ML model that requires a training set.

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

• Not Applicable. As there is no AI/ML model or training set, the concept of establishing ground truth for training is irrelevant.

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