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The DSU Dual Stage Ultrafilter is intended to be used to filter water or bicarbonate concentrate used in hemodialysis devices. The DSU Ultrafilter assists in providing hemodialysis quality water or bicarbonate concentrate. The device is not a complete water treatment system, but serves to remove biological contaminants. Therefore, it must be used in conjunction with other water treatment equipment (i.e., RO, DI, etc.).

The DSU Dual Stage Ultrafilter is a hollow fiber filter that removes bacteria, viruses, endotoxin and particulate from water and bicarbonate concentrate used in hemodialysis.

The provided text describes the DSU Dual Stage Ultrafilter, a device intended to filter water or bicarbonate concentrate used in hemodialysis. The information primarily focuses on its regulatory submission and equivalence to a predicate device. While it mentions various tests conducted, it does not provide detailed acceptance criteria with numerical thresholds or specific performance results in a comparative table format. Therefore, some information requested cannot be fully extracted from the provided text.

Here's the information that can be extracted, and an indication of what is not present:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

The document mentions that the DSU Dual Stage Ultrafilter "has been tested for performance." However, it does not specify the sample size used for the test set for any of the mentioned tests (Flow Rate, Bicarbonate Composition, Pyrogen Removal, Virus Challenge, Bacteria Challenge, Chemical Compatibility).

The data provenance is also not explicitly stated. It's a regulatory submission to the FDA (USA), implying the testing was conducted by the manufacturer (Nephros Inc. in River Edge, NJ, USA). It does not indicate if the data is retrospective or prospective.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This device is a physical filter, not an AI/software device that relies on expert interpretation for ground truth. Therefore, this information is not applicable to this type of medical device submission. The performance is assessed through laboratory testing against physical and biological contaminants.

4. Adjudication Method for the Test Set

As this is a physical device with laboratory performance testing, adjudication methods typically used for human interpretation of medical images or data are not applicable. Test results would be objectively measured.

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

This is not applicable as the device is a physical filter, not an AI-assisted diagnostic tool involving human readers.

6. Standalone Performance Study

Yes, the studies mentioned (Flow Rate, Bicarbonate Composition Effect, Pyrogen Removal, Virus Challenge Test, Bacteria Challenge Test, and Chemical Compatibility) represent standalone performance testing of the DSU Dual Stage Ultrafilter. The text states: "The DSU Dual Stage Ultra Filter has been tested for performance." This indicates that the algorithm (in this case, the device's physical mechanism) was evaluated directly without human intervention to complete its primary function.

7. Type of Ground Truth Used

The ground truth for the stated tests would be based on objective laboratory measurements and established scientific standards for water purification and filtration efficacy (e.g., bacterial count reduction, virus removal, pyrogen levels, flow rate consistency). For example, for the "Virus Challenge Test" and "Bacteria Challenge Test," the ground truth would be the known concentration of viruses or bacteria in the input water and the measured concentration in the output water after filtration, adhering to specific test protocols.

8. Sample Size for the Training Set

This information is not applicable as this is a physical medical device, not an AI/machine learning algorithm that requires a training set.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable as this is a physical medical device, not an AI/machine learning algorithm.

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