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Indicated for use with the Prisma Control Unit in providing continuous fluid management and renal replacement therapies for patients who have acute renal failure, fluid overload, or both.

The Prisma Disposable Sets are sterile disposable extracorporeal circuits containing an AN 69 HF hemofilter/dialyzer and fluid circuit for use with the Prisma Control Unit. These Prisma Disposable Sets allow the following fluid management and renal replacement therapies to be performed: SCUF - Slow Continuous Ultrafiltration CVVH - Continuous Venovenous Hemofiltration CVVHD - Continuous Venovenous Hemodialysis CVVHDF - Continuous Venovenous Hemodiafiltration

The provided text is a 510(k) summary for the Gambro Prisma M60/M100 Sets, a medical device. This document focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a study to prove performance against those criteria in the context of advanced AI/ML device evaluations.

Therefore, many of the requested categories are not applicable or cannot be extracted from this document, as the submission predates the common methodologies and requirements for AI/ML device evaluations.

Here's the information that can be extracted or deduced from the provided document, with notes on what is not applicable:

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

The document does not explicitly state quantitative acceptance criteria in a dedicated table format, nor does it present specific performance metrics like sensitivity, specificity, or AUC as would be found in an AI/ML device study. Instead, it relies on demonstrating "substantial equivalence" through "in vitro testing" to predicate devices.

2. Sample sized used for the test set and the data provenance

• Sample Size (Test Set): Not specified. The document only mentions "in vitro testing" without details on the number of tests or specific test runs.
• Data Provenance (e.g. country of origin of the data, retrospective or prospective): Not specified. The testing was "in vitro," implying laboratory-based testing rather than patient data.

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

• Number of Experts: Not applicable. The "ground truth" for this type of device (hemofilter and blood tubing set) would be established through engineering specifications, material properties, and functional performance benchmarks rather than expert clinical consensus on diagnostic images or patient outcomes.
• Qualifications of Experts: Not applicable.

4. Adjudication method for the test set

• Adjudication Method: Not applicable. Adjudication methods like 2+1 or 3+1 are used for human-reviewed data, typically in diagnostic imaging or clinical assessment, to establish a consensus ground truth. This is not relevant for in vitro functional performance testing of a physical medical 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

• MRMC Study: No, this type of study was not done. MRMC studies are specific to evaluating AI's impact on human diagnostic performance, which is not relevant for a hemofilter and blood tubing set.
• Effect Size of Human Reader Improvement: Not applicable.

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

• Standalone Performance: Not applicable. The device is not an algorithm and does not have a "standalone" performance in the sense of AI/ML evaluation. Its performance is inherent to its physical design and function. The "in vitro testing" assesses the physical device's performance directly.

7. The type of ground truth used

• Type of Ground Truth: For "in vitro testing" of a physical device like this, the 'ground truth' would be defined by established engineering and medical standards, performance specifications for flow rates, filtration efficiency, material compatibility, and sterility, as measured by standard laboratory equipment and protocols. It is not expert consensus, pathology, or outcomes data in the usual sense.

8. The sample size for the training set

• Sample Size (Training Set): Not applicable. This document describes a physical medical device, not an AI/ML algorithm that requires a "training set."

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

• Ground Truth for Training Set: Not applicable, as there is no training set for this device.

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