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The NexSite 9Fr Dual Lumen Critical Care Central Venous Catheter is indicated for long-term access to the Central Venous System. It is designed for administering IV fluids, blood products, drugs, and parenteral nutrition as well as blood withdrawal and power injection of contrast media. The maximum pressure of power injectors used with the NexSite device may not exceed 300psi.

The NexSite 9Fr Dual Lumen Catheter is a long-term central venous catheter. The polyurethane Catheter is 55.5cm in length, and has a Dacron cuff distal to the bifurcation hub. A Polyurethane/Dacron Port supplied with the Catheter is implanted subcutaneously, and is intended to minimize Catheter movement. The Catheter and Port are packaged with accessories that are used to facilitate Catheter and Port insertion.

The provided text describes the 510(k) summary for the NexSite 9Fr Dual Lumen Critical Care Central Venous Catheter.

Acceptance Criteria and Device Performance

The acceptance criteria for the NexSite 9Fr Dual Lumen Critical Care Central Venous Catheter were established based on ISO 10555-1 and ISO 10555-3 standards and by demonstrating substantial equivalence to legally marketed predicate devices.

Study Details:

1. Sample size used for the test set and the data provenance:

   • The document primarily describes in vitro testing. No specific sample sizes for each test are provided, but the testing was conducted on samples of the NexSite 9Fr Dual Lumen Critical Care Central Venous Catheter.
   • Data Provenance: The testing was performed by Marvao Medical Devices, Ltd. in Ireland (GMIT Innovation in Business Centre, Dublin Road Galway, Ireland), indicating the data is from the manufacturer's internal testing program. The document does not explicitly state if it's retrospective or prospective for the in vitro tests but implies prospective testing conducted for the 510(k) submission.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • This information is not applicable as the studies described are primarily in vitro performance tests (e.g., strength, leakage, radiopacity) against engineering standards (ISO 10555-1 and ISO 10555-3) rather than clinical studies requiring expert ground truth for patient outcomes or diagnoses. The "ground truth" for these tests would be the established benchmark values from the relevant ISO standards.

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

   • This information is not applicable as the studies are engineering performance tests, not clinical studies requiring human adjudication of outcomes or diagnoses.

4. 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:

   • No, an MRMC comparative effectiveness study was not performed, nor is it relevant to this medical device submission. The device is a physical central venous catheter, not an AI-powered diagnostic or assistive tool.

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

   • No, a standalone algorithm performance study was not performed, nor is it relevant. The device is a physical central venous catheter.

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

   • For the in vitro tests, the "ground truth" or acceptance criteria are derived from international standards (ISO 10555-1 and ISO 10555-3) and comparison to the performance of legally marketed predicate devices.
   • For the in vivo testing, the "ground truth" was a demonstration that the "device would perform as intended," which implies meeting functional objectives in a living system (likely animal models, though not explicitly stated). No clinical outcomes data or pathology was used as "ground truth" for this submission as clinical studies were not deemed necessary.

7. The sample size for the training set:

   • This information is not applicable as this submission is for a physical medical device, not an AI/machine learning algorithm that requires a training set.

8. How the ground truth for the training set was established:

   • This information is not applicable as this submission is for a physical medical device, not an AI/machine learning algorithm.

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