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The Intersept filtered cardiotomy reservoir with Cortive surface is indicated for use in the cardiopulmonary bypass circuit during surgery for:

• an air/fluid separation chamber
• a temporary storage reservoir for priming solution and blood
• the filtration of particulates from bank blood and the storage and filtration of blood recovered from the field by suction
• the addition of medications or other fluids.

The Intersept Filtered Cardiotomy Reservoir with Cortiva BioActive Surface is a single-use, device with a sterile, nonpyrogenic fluid path. The maximum capacity of each reservoir is 2,600 mL. The maximum recommended flow rate is 2 liters per minute (LPM). Each reservoir has eight luer or 0.6 cm (0.25 in) ID access ports; four suction access ports, two pre-defoamer and two post-defoamer access ports. One of the post-defoamer access ports is intended for use as a vent. Each Intersept Filtered Cardiotomy Reservoir contains an open cell polyurethane defoamer with a 20-micron microaggregate filter covered with a polyester sleeve.

The provided document is a 510(k) premarket notification for a medical device, the "Intersept™ Filtered Cardiotomy Reservoir with Cortiva™ BioActive Surface." It details the device's indications for use, comparison to predicate devices, and a summary of testing conducted to demonstrate substantial equivalence.

However, this document does not contain the kind of detailed information typically found in acceptance criteria or a study write-up designed to prove a device meets those criteria, especially in the context of an AI-powered diagnostic device performing a specific task (like identifying lesions in medical images).

Here's why and what information is missing:

• Device Type: This submission is for a physical medical device (a cardiopulmonary bypass blood reservoir), not an AI algorithm. Therefore, the "acceptance criteria" and "study" described in the prompt, which are strongly geared towards AI performance metrics (sensitivity, specificity, AUROC, reader studies, ground truth establishment), don't directly apply in the same way.
• Performance Metrics: The "reported device performance" in this document refers to physical and biological performance (bioactivity, leaching, coverage, biocompatibility, filtration efficiency, blood trauma), not diagnostic accuracy.
• Clinical Study Design: There is no description of a clinical study involving human subjects or experts assessing diagnostic performance as would be relevant for an AI algorithm. The testing described is laboratory-based and focused on material properties and basic device function.

Based on the provided document, here's what can be extracted and what remains unanswered regarding the prompt's specific requests (assuming the prompt's structure is still applied, despite the mismatch in device type):

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

Interpretation/Note: These are not "acceptance criteria" in the sense of diagnostic performance thresholds for an AI, but rather verification/validation checks for physical and biological device properties. The "Pass" indicates the device met Medtronic's internal criteria for these tests.

2. Sample sized used for the test set and the data provenance

• Sample Size for Test Set: Not specified in the provided document. The document lists "tests" but doesn't detail the number of units or samples used for each test.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not applicable for a physical device's lab testing. The tests are laboratory-based and not derived from clinical patient data from a specific country or study type.

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

• This question is not applicable as the device is not an AI diagnostic algorithm, and "ground truth" in the context of medical image interpretation by experts is not relevant to this submission. The tests performed are laboratory-based physical and biological assays.

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

• Not applicable. There is no adjudication process involving human interpretation or consensus for the validation of this physical device. Verification/validation tests are typically performed according to established protocols.

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 device is not an AI algorithm, and therefore, an MRMC study comparing human reader performance with and without AI assistance was not performed.

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

• Not applicable. The device is a physical medical device, not an algorithm.

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

• Not applicable / Differently Defined: "Ground truth" for this device refers to established scientific/engineering principles, validated analytical methods, and predetermined specifications for physical and biological characteristics (e.g., certain levels of bioactivity, filtration efficiency, or absence of harmful leaching). It's not clinical "ground truth" derived from patient outcomes or expert reads.

8. The sample size for the training set

• Not applicable. This device is not an AI algorithm that requires a training set. The development of the device would involve engineering design, material selection, and iterative testing, not "training."

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

• Not applicable. As above, no training set or its associated ground truth establishment is relevant to this physical device submission.

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