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The Prismaflex® control unit is intended for:

• Continuous Renal Replacement Therapy (CRRT) for patients weighing 20 kilograms or more with acute renal failure and/or fluid overload.
• Therapeutic Plasma Exchange (TPE) therapy for patients weighing 20 kilograms or more with diseases where removal of plasma components is indicated.
  All treatments administered via the Prismaflex® control unit must be prescribed by a physician.

The Prismaflex control unit is a software controlled device that performs the following functions:

• Loads and primes the Prismaflex disposable set automatically.
• Pumps blood through the blood flow path of the Prismaflex disposable set.
• Delivers anticoagulant solution into the blood flow path.
• Pumps sterile infusion solutions into the blood flow path of the Prismaflex disposable set according to therapy in use.
• Pumps sterile dialysate into the fluid compartment of the filter in CRRT therapies.
• Controls the patient fluid removal or plasma loss according to the therapy in use.
• Monitors the system and alerts the operator to abnormal situations through alarms.
  The Prismaflex® has a touch screen user interface that provides operating instructions.
  The Prismaflex® provides color coding and bar-code identification of the filter sets that are automatically loaded. The Prismaflex continually monitors the operation of the machine and displays one of four (4) types of alarms if an abnormal situation occurs. The Prismaflex® has five (5) pumps that allow multiple therapeutic combinations; including a "pre-blood pump" that allows infusion of a supplemental solution for hemodilution or anticoagulation of the extracorporeal circuit.

The provided text describes a 510(k) submission for the Prismaflex® System, a hemodialysis delivery system. This type of submission is for demonstrating substantial equivalence to a predicate device, not for proving a device meets specific clinical acceptance criteria through a comparative effectiveness study in the same way an AI/ML device might. Therefore, many of the requested elements for an AI/ML study, such as sample size for test sets and training sets, expert qualifications, adjudication methods, and MRMC studies, are not applicable or not provided in the document.

The "acceptance criteria" here are implicitly the performance specifications of the device as compared to its predicate devices, along with compliance with relevant international standards for medical electrical equipment. The "study that proves the device meets the acceptance criteria" is broadly referred to as "Complete software and system verification and validation including functional, performance and safety requirements" and "Compliance has been demonstrated to the following international standards."

Here's the information extracted and adapted to the best extent possible given the nature of the document:

1. Table of Acceptance Criteria (as implied by comparison to predicates) and Reported Device Performance

The device's performance is implicitly evaluated against the predicate devices for key operational parameters. The document focuses on demonstrating that the Prismaflex® (Software Version 5.10) performs similarly to or within acceptable ranges of the predicate devices.

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

This information is not provided in the document. The submission details a medical device (a hemodialysis system) for which performance is typically verified through engineering tests, bench tests, and potentially clinical validation activities (which are not detailed here as a specific "test set" with patient data). The document states "Complete software and system verification and validation including functional, performance and safety requirements," but does not specify sample sizes or data provenance for these verification activities.

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)

This information is not applicable to this type of device submission. Ground truth, in the context of expert consensus, is relevant for diagnostic devices that interpret signals or images. For a hemodialysis delivery system, "ground truth" would relate to accurate physical measurements and system functionality, not expert interpretation of patient data.

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

This information is not applicable as an adjudication method for expert consensus is not relevant to the type of device and testing 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

This information is not applicable. This is not an AI/ML diagnostic device, and therefore, an MRMC study with human readers assisting AI is irrelevant.

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

This information is not applicable. The Prismaflex® system is a physical medical device with software, not a standalone algorithm.

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

The "ground truth" for this device's performance is based on engineering specifications, physical measurements, and compliance with recognized international standards. For example, the accuracy of flow rates would be verified against known calibrated standards, not expert consensus or pathology.

8. The sample size for the training set

This information is not provided and is largely not applicable in the context of device hardware and software verification for a 510(k) of this nature. "Training set" is primarily a concept used in AI/ML development.

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

This information is not applicable. There is no "training set" in the AI/ML sense for this device. The system's functionality and performance are verified against pre-defined engineering requirements and industry standards.

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