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These pre-assembled stopcock gangs provide multiple access sites into a common fluid path for the administration of drugs and solutions. The luer connectors on either end of the stopcock gang allow connection to an IV set for fluid administration through an indwelling intravascular catheter.

Stopcock manifold gangs consist of individual stopcocks assembled in series through common luer fittings to form a manifold or stopcock gang. These pre-assembled stopcock gangs provide multiple access sites into a common fluid path for the administration of drugs and solutions. The luer connectors on either end of the stopcock gang allow connection to an IV set for fluid administration through an indwelling intravascular catheter.

Baxter will purchase stopcocks from Medex, Inc. and will assemble individual stopcocks into ganged configurations containing 2, 3 or 5 stopcock units. Baxter will use Medex stopcocks which vary in the number of flow paths (3 or 4 way), internal lumen diameter (large bore or standard bore) and type of luer connection (male luer slip, rotating male luer lock, and female luer lock) may be used to produce the gangs. The stopcock manifold gangs may also be marketed with a pre-attached backing plate which can be used to attach the stopcock gang to an IV pole.

This submission (K962581) is for a Stopcock Manifold Gangs, which is a medical device, not an AI/ML algorithm. Therefore, many of the requested categories related to AI/ML device studies and performance metrics (e.g., sample size for test set, number of experts, adjudication method, MRMC studies, standalone performance, training set sample size, ground truth establishment) are not applicable.

The submission describes the device, its predicate devices, and the non-clinical tests performed to demonstrate its safety and effectiveness.

Here's a breakdown of the available information based on your request, with a clear indication of not applicable where appropriate for an AI/ML context:

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

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 (N/A) for AI/ML context. This is a hardware medical device.
• For the device itself: The document does not specify exact sample sizes for each of the functional tests (e.g., how many stopcocks were tested for pressure seal). The testing was non-clinical (laboratory testing of the device components/assemblies). The "data provenance" would be internal laboratory testing by Baxter Healthcare Corporation in the USA.

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)

• N/A for AI/ML context. Ground truth in the AI sense is not applicable here.
• For the device itself: The "ground truth" for a physical device's performance is established by objective engineering standards and measurements. There wouldn't be "experts establishing ground truth" in the diagnostic sense, but rather engineers and quality control personnel performing and verifying the tests against established specifications.

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

• N/A for AI/ML context. Adjudication methods are relevant for subjective interpretations of data, not for objective physical device testing.

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

• N/A. This is a physical medical device, not an AI-assisted diagnostic tool.

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

• N/A. This is a physical medical device, not an algorithm.

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

• N/A for AI/ML context.
• For the device itself: The "ground truth" for this device's performance is based on objective engineering specifications and standards (e.g., ANSI standard MD70.1-1983 for luer conformance, measurable flow rates, pressure resistance, and mechanical stability).

8. The sample size for the training set

• N/A. This is 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

• N/A. This is a physical medical device; there is no training set or associated ground truth in the AI/ML sense.

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