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The proposed Vial-Mate Reconstitution Device has the same intended use as previously cleared devices of its type. The Vial-Mate Reconstitution Device is intended to provide the pharmacist or health practitioner a means of connecting a standard 20 mm single dose drug vial to an I.V. solution container without mixing the vial contents with the diluent until immediately before administration of the reconstituted drug to the patient.

The Vial-Mate Reconstitution Device is an accessory intended for use by the pharmacist or health practitioner in the reconstitution and transfer of drugs into Baxter solution containers. This product is similar to the currently marketed Baxter ReConPlus™ Reconstitution Device, cleared under K910793 on March 21, 1991. Like the ReConPlus™ Reconstitution Device, it provides a means of connecting a standard 20 mm single dose drug vial to an I.V. solution container without reconstituting and mixing the vial contents with the diluent until immediately before administration of the drug to the patient.

There is one solution contact material in the proposed Vial-Mate Reconstitution Device which is new to Baxter. It is an elastomeric material which is used in the septum of the device. The other solution materials used in the proposed device were previously tested and used in other Baxter devices for similar IV solution administration applications.

This document describes a 510(k) Premarket Notification for the Vial-Mate Reconstitution Device. As such, it primarily focuses on establishing substantial equivalence to a predicate device rather than presenting a detailed study with acceptance criteria and performance metrics for a complex algorithm or AI system.

Here's an analysis based on the provided text, addressing your points where applicable, and noting where the information is not provided because it pertains to a different type of device or regulatory submission:

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

The provided text does not contain a quantitative acceptance criteria table with reported device performance in the manner you'd expect for an AI/algorithm-based device. Instead, it refers to overall functional requirements and regulatory standards.

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 explicitly provided in the 510(k) summary. For a medical device like a reconstitution device, testing typically involves bench testing, sterility testing, and biocompatibility assessments, rather than clinical studies with "test sets" in the AI sense. The number of samples for these tests would be determined by relevant standards and protocols, but are not disclosed here. Data provenance (country of origin, retrospective/prospective) is not applicable or stated for this type of submission.

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 concept of "ground truth" established by experts for a test set is not applicable to a physical medical device like a reconstitution device. Ground truth, in the context of AI/ML, refers to a label or diagnosis that an algorithm attempts to predict, which would then be compared to expert consensus or pathology. The evaluation of this device is based on its physical properties, material safety, and functional operation.

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

Not applicable for this type of device and regulatory submission. Adjudication methods are typically used in clinical studies involving interpretation of data (e.g., medical images) to resolve discrepancies among multiple expert opinions, which isn't relevant here.

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. MRMC studies are designed to compare the diagnostic accuracy of human readers with and without AI assistance, which is irrelevant for a passive mechanical device like the Vial-Mate.

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

Not applicable. The Vial-Mate is a physical device, not an algorithm.

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

Not applicable. The "ground truth" for a mechanical device relates to its adherence to engineering specifications, material standards (e.g., ISO 10993 for biocompatibility), and functional performance requirements (e.g., leak-proof, proper drug transfer).

8. The sample size for the training set

Not applicable. The concept of a "training set" applies to machine learning algorithms, not to the development and testing of a physical medical device like the Vial-Mate.

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

Not applicable for the same reasons as points 7 and 8.

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