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For the administration of fluids from a container into the patient's vascular system through a vascular access device.

The proposed devices consist of Solution Administration Sets. These devices include Basic, Secondary, CONTINU-FLO solution sets, Stand-Alone devices and Chemotherapy devices (see Table 2 for a list of subject device set names per product family). They are single use disposable, non-pyrogenic, sterile devices intended for the administration of fluids from a container into the patient's vascular system.

This is a 510(k) premarket notification for "Solution Administration Sets" by Baxter Healthcare Corporation. The document states that the devices are substantially equivalent to a predicate device (K203609 cleared on September 30, 2021).

Here's the breakdown of the acceptance criteria and the study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a specific table of acceptance criteria with corresponding performance values in the format usually seen for AI/ML devices. Instead, it describes general conformance to recognized standards and the positive outcomes of various tests.

Note: This submission is for a traditional medical device (solution administration sets), not an AI/ML device. Therefore, the questions related to AI/ML specific studies (sample size for test set, data provenance, number of experts for ground truth, adjudication, MRMC study, standalone performance, training set sample size, training set ground truth) are not applicable to this document. The "tests" described are standard engineering, biocompatibility, and sterilization validations for physical medical devices.

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

Not applicable, as this is a traditional medical device, not an AI/ML device. The testing described is bench testing and biocompatibility assessments, not a study involving patient data or a specific test set in the AI/ML context.

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)

Not applicable, as this is a traditional medical device, not an AI/ML device. Ground truth as typically defined for AI/ML models is not relevant here.

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

Not applicable, as this is a traditional medical device, not an AI/ML 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

Not applicable, as this is a traditional medical device, not an AI/ML device.

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

Not applicable, as this is a traditional medical device, not an AI/ML device.

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

Not applicable, as this is a traditional medical device, not an AI/ML device. Instead of "ground truth," the device relies on conformance to established international and national standards (ISO, ASTM, USP) and predefined acceptance criteria for various physical, chemical, and biological tests.

8. The sample size for the training set

Not applicable, as this is a traditional medical device, not an AI/ML device.

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

Not applicable, as this is a traditional medical device, not an AI/ML device.

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