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This bag is intended for the collection of effluent during Automated Peritoneal Dialysis (APD) Therapy.

Baxter's Cycler Drainage Bag product line currently consists of a sterile 15L Cycler Drainage Bag (5C4145P). This 15 L Cycler Drainage Bag is a single use device intended for the collection of effluent during Automated Peritoneal Dialysis (APD) Therapy and can be used with Baxter's APD Sets with Cassette, Manifold Sets and Extension Sets. The purpose of this drain bag is to allow the collection of the spent effluent in the event that a patient does not have access to a drain from the location where APD therapy is performed. The basis for this submission is the addition of a non-sterile version of the 15L Cycler Drainage Bag to the current product line. The product line does not come into direct or indirect contact with the patient's body tissue. The intended use, material, design, and function of the proposed device will be the same as the currently marketed 15 L Cycler Drainage Bag.

The provided document describes a 510(k) premarket notification for a new non-sterile version of Baxter's 15L Cycler Drainage Bag (product code 5C4145NS), comparing it to the currently marketed sterile version (5C4145P) which serves as the predicate device. The primary difference is the sterility status.

1. Table of Acceptance Criteria and Reported Device Performance:

Note: The document states that "All results meet the acceptance criteria," therefore, the reported device performance for all listed criteria is implicitly "Met."

2. Sample Size Used for the Test Set and the Data Provenance:

The document does not explicitly state the sample sizes for each specific test or the data provenance (e.g., country of origin) for the test sets. The tests are described as "design verification tests" conducted by Baxter Healthcare Corporation. It is implied these are internal company tests, so the data provenance would be internal to Baxter, likely in the US (where Baxter is headquartered). The studies appear to be prospective, as they were conducted to support the premarket notification for a new product configuration.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts:

This information is not provided. The tests described are largely objective engineering and microbiological performance tests (e.g., leak tests, force measurements, bioburden, microbial travel), which typically rely on predefined specifications and instrumentation rather than expert consensus on a "ground truth" in the diagnostic sense.

4. Adjudication Method for the Test Set:

Not applicable. As noted above, the tests are objective performance evaluations against established engineering and safety specifications, not subjective assessments requiring adjudication.

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 device is a medical accessory (drainage bag), not a diagnostic imaging or AI-enabled device. Therefore, MRMC studies and AI-related effectiveness are not relevant.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

Not applicable. This device is a medical accessory, not an algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.):

The "ground truth" for the performance tests outlined (Capacity/Leak, Drain Line Spike/Leak, Clamp forces, Bioburden, Microbial travel, Cycler System Level, Removal forces, Solvent Bond Leak Strength, Connection Duration) is based on engineering specifications, established industry standards (e.g., ISO, AAMI), and risk analyses. For biocompatibility, it's adherence to ISO-10993. For microbial travel, it's the lack of contamination reaching a critical point (APD cassette). These are objective, measurable criteria, not subjective human interpretations.

8. The Sample Size for the Training Set:

Not applicable. This device is a physical medical accessory, not an AI/machine learning algorithm requiring a training set.

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

Not applicable. No training set is involved.

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