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The triple lumen central venous Catheter is intended for vascular access infusion and withdrawal of blood, blood products, and fluids, central venous blood pressure monitoring and continuous or intermittent drug infusion.

• Patients requiring multiple sites for IV access.
• Patients lacking useable peripheral IV sites.
• Patients requiring central venous pressure monitoring.
• Patients requiring total parenteral nutrition.
• Patients receiving incompatible medications.
• Patients requiring multiple infusions of fluids, medications, or chemotherapy.
• . Patients subject to frequent blood sampling or receiving blood transfusions.
• Patients receiving infusions that are hypertonic, hyperosmolar or infusions that have divergent pH values.

The medical device made by Sunder Biomedical Tech, CO., LTD are triple-lumen. polyurethane catheter, 5.5 and 7.0 French in size, with three independent non-communication lumens, extension lines, luer hubs and slide clamps, placed within a vein and whose distal end is intended to be located within the vena cava (inferior of superior). Central Venous Catheter (CVC) - a tubular device with single lumen or rnulti-lumen catheter, or cannula, placed within a vein and whose distal end is intended to be located within the vena cava (inferior of superior).
The catheterization kit components are configured in a Polyester Terephthalate (PET) tray and sealed with a Tyvek lid stock, and sterilized.

The provided text describes the 510(k) premarket notification for the Sunder Central Venous Catheter Kit. It details the device, its intended use, and the performance tests conducted. However, this document does not contain information about acceptance criteria or a study proving the device meets those criteria, particularly in the context of an AI/ML powered device, which the request seems to imply by asking about specific AI/ML related study artifacts such as "MRMC comparative effectiveness study", "standalone (i.e. algorithm only without human-in-the-loop performance)", "effect size", "sample sized used for the test set", "data provenance", "number of experts", "adjudication method", "type of ground truth", "training set sample size" and "how ground truth for training set was established".

The device described is a physical medical device (central venous catheter), not an AI/ML-powered diagnostic or predictive system. Therefore, the questions related to AI/ML study design are not applicable to this submission.

The document focuses on the safety and effectiveness of the physical catheter itself, comparing it to a predicate device (ARROW g* and blue Plus™ Multi-Lumen Central Venous Catheter K993691). The performance tests listed are standard for such a device.

Here's a breakdown of the information that is available, and why the other requested information is not present:

1. Table of Acceptance Criteria and Reported Device Performance:

The document lists "Performance tests" but does not provide specific acceptance criteria or quantitative results against those criteria. It summarily states: "The result of the laboratory tests demonstrate that the device is as safe as and is effective with the legally marketed predicate device."

Information Not Present (and why it's not applicable for this type of device):

• 2. Sample size used for the test set and the data provenance: Not applicable. This document refers to physical device testing, not a data-driven model. There is no "test set" in the sense of a dataset for a software algorithm.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device like a catheter comes from engineering specifications and standardized testing methods, not expert consensus on data interpretation.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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 for AI/ML-powered diagnostic assistance, which is not what this device is.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For a physical device, "ground truth" is defined by engineering specifications and material properties verified through physical and chemical testing.
• 8. The sample size for the training set: Not applicable. There is no "training set" for physical device manufacturing.
• 9. How the ground truth for the training set was established: Not applicable.

In summary, the provided document is a 510(k) summary for a physical medical device and therefore does not contain the information typically required for evaluating an AI/ML-powered device. The "study that proves the device meets the acceptance criteria" is described as a series of laboratory performance, microbiological, and biocompatibility tests, which concluded that the device is "as safe as and is effective with the legally marketed predicate device."

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