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The Medrad Transfer Set is intended to be used in the delivery of contrast media and saline into a syringe.

The Medrad Transfer Set is medical disposable device used to transfer intravascular contrast media and saline from a spikeable container to a power injector syringe. The device components consist of a vented spike, connector tube, a means of manually stopping flow, female luer, and individually packaged sterile caps.

The provided text describes a 510(k) premarket notification for a medical device called the "Medrad Transfer Set." This document focuses on demonstrating substantial equivalence to an already legally marketed predicate device, rather than proving the device meets specific acceptance criteria through a standalone study with performance metrics in the way one might expect for a diagnostic AI device.

Therefore, many of the requested elements (like sample size for test sets, number of experts, adjudication methods, MRMC studies, ground truth types, training set details) are not applicable or not present in this type of regulatory submission for a simple medical device.

The study described here is essentially a comparison of features and principles of operation between the proposed device and a predicate device (Merit Contrast Management System K961794) to demonstrate substantial equivalence.

Here's a breakdown based on the information provided:

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

Since this is a substantial equivalence submission for a simple transfer set, the "acceptance criteria" are not reported as quantitative performance metrics. Instead, the acceptance criteria are met by demonstrating that the proposed device is substantially equivalent to a predicate device in terms of intended use, principle of operation, materials, and other characteristics. The "reported device performance" is essentially the comparison of features.

Key Difference/Consideration for Equivalence:
The primary difference highlighted is that the predicate device included a separate disposable single-patient use tubing component for direct patient connection, whereas the Medrad Transfer Set does not. The Medrad set must be removed from the syringe before the syringe can be connected to the patient, thus preventing contact with patient fluid. This difference is addressed in the submission to ensure it does not raise new questions of safety or effectiveness.

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. This submission does not involve a "test set" in the sense of a dataset for performance evaluation of an AI algorithm. It's a review of device characteristics and intended use against a predicate.

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)

Not Applicable. There is no "ground truth" establishment in this type of submission. The comparison is based on the technical specifications and intended use of the devices.

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

Not Applicable. No test set or expert adjudication is described.

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 a mechanical transfer set, not an AI or diagnostic imaging device. No MRMC study was conducted.

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

Not Applicable. This is a hardware device, not an algorithm.

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

Not Applicable. No ground truth for performance evaluation is established or used for this type of device. The "ground truth" for substantial equivalence is the established performance and safety profile of the predicate device.

8. The sample size for the training set

Not Applicable. No training set is involved as this is not an AI algorithm.

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

Not Applicable. No training set and no ground truth for a training set are involved.

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