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The HomeChoice® Personal Cycler Peritoneal Dialysis System is intended for automatic control of dialysate solution exchanges in the treatment of pediatric and adult renal failure patients undergoing peritoneal dialysis.

The HomeChoice® Personal Cycler Peritoneal Dialysis System provides automatic control of dialysate solution exchanges for low fill volume and standard fill volume therapies with software drain logic designed specific to each fill volume range.

This document is a 510(k) summary for the Baxter HomeChoice® Personal Cycler Peritoneal Dialysis System, detailing its substantial equivalence to a previously cleared device. It is not a study report containing detailed performance data. Therefore, the information requested about acceptance criteria and study details cannot be fully extracted from the provided text.

Specifically, the document states:
"The HomeChoice® Personal Cycler Peritoneal Dialysis System is exactly the same as the predicate device, with the exception that the modified device provides low fill volume mode drain logic for renal failure patients requiring fill volumes of 60 - 1000 mLs."

This statement implies that the device's performance is expected to be substantially equivalent to the predicate device, with the only change being a software modification for handling low fill volumes. A 510(k) submission generally focuses on demonstrating substantial equivalence rather than conducting a new, exhaustive performance study with distinct acceptance criteria and outcomes for every aspect of the device.

Based on the provided text, here is what can be inferred and what is explicitly not available:

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

• Acceptance Criteria: Not explicitly stated. For a 510(k) of this nature, the "acceptance criteria" likely revolve around demonstrating that the new drain logic for low fill volumes performs as intended and does not introduce new safety or effectiveness concerns, maintaining substantial equivalence to the predicate. This would typically involve software verification and validation activities (e.g., testing against specifications for drain accuracy, alarm functionality, patient safety parameters for the new fill volume range, etc.). However, these specific criteria are not detailed in this summary.
• Reported Device Performance: Not explicitly stated in quantitative terms. The document only mentions the purpose of the modification (low fill volume mode drain logic for 60-1000 mLs) and implies that it works as intended to maintain substantial equivalence. Detailed performance metrics (e.g., drain efficiency, accuracy for specific volumes, alarm response times) are not provided.

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified. Given it's a software modification to an existing device, it's possible testing was done internally by the manufacturer, but no details are provided.

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 and not provided. The device (automated peritoneal dialysis system) does not involve interpreting medical images or data that would typically require expert consensus for establishing ground truth in the way a diagnostic AI device would. The "ground truth" here would relate to the correct functioning of the machine's software and hardware according to its specifications for liquid exchange, which is assessed through engineering and clinical performance testing, not expert interpretation of data.

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

• Not applicable and not provided. See explanation for point 3.

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. This is not a diagnostic AI device that assists human readers/interpreters. It is a medical device for automated peritoneal dialysis.

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

• Not applicable in the typical sense of "standalone AI performance." The device is largely automated, and the "drain logic" is an algorithm. Its performance would be assessed in a standalone manner (i.e., the machine performs its function without human intervention during the dialysis exchanges) to ensure it meets specifications, but this isn't framed as a "standalone AI study" in the context of diagnostic AI.

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

• The "ground truth" for a device like this would be established by engineering specifications for fluid volumes, flow rates, alarm conditions, and clinical safety and effectiveness parameters for peritoneal dialysis. This would typically be assessed through device testing, bench testing, and potentially some limited clinical validation to ensure the new drain logic performs safely and effectively for the stated patient population and fill volume range. It would not typically involve expert consensus on interpretations of medical data or pathology. Specific details are not provided.

8. The sample size for the training set

• Not applicable. This device is not an AI/ML model that undergoes "training" on a dataset in the way a diagnostic algorithm would. The "logic" is programmed software, not a learned model from a training set.

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

• Not applicable. See explanation for point 8.

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