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PressureWire Net is intended to condition physiological signals from measuring devices (PressureWire and an external pressure transducer), transmit and receive via radiofrequency, and reconditions the signals to its original format so that those can be displayed on and/or recorded in a receiving device (RadiAnalyzer Xpress or other Monitor systems). The physiological signals can also be distributed via cable.

Indication for Use:

PressureWire Net is indicated to condition a physiological signal from the cardiovascular system, transmit and receive via radiofrequency, and recondition the signal to its original format so that it can be displayed. The physiological signal can also be distributed via cable.

PressureWire Net is a radiofrequency physiological signal transmitter and receiver that is used for conditioning a physiological signal so that it can be transmitted via radiofrequency from one location to another, e.g., a host system.

PressureWire Net receives signals from the manufacturer's PressureWire and from a standard external pressure transducer, and then transmits those signals to a host system for further calculation and presentation. The subject device expands the contact range to also include a standard USB connector.

The provided text is a 510(k) summary for the PressureWire Net device. The information details the device's intended use, substantial equivalence to predicate devices, and regulatory compliance. However, it does not include specific details about acceptance criteria, a study proving the device meets those criteria, or any of the detailed performance metrics, sample sizes, or ground truth establishment methods typically found in clinical validation studies.

This document focuses on establishing substantial equivalence based on non-clinical performance data (adherence to standards and internal design procedures) and a literature review/product performance of predicate devices. There is no mention of a standalone algorithm study, MRMC study, or any specific study designed to measure the device's diagnostic performance against defined acceptance criteria.

Therefore, most of the requested information cannot be extracted from the provided text.

Here is what can be inferred or explicitly stated from the document:

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

No explicit acceptance criteria or reported device performance metrics (e.g., sensitivity, specificity, accuracy, precision) are provided in the document. The substantial equivalence is based on the device being "as safe and effective for its intended use as the predicate device(s)" based on its design and adherence to standards.

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. No test set or clinical performance data from a specific study is described. The assessment is based on non-clinical data and a literature review of predicate device performance.

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. No ground truth establishment for a test set is described.

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

Not applicable. No test set or adjudication method 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

No. An MRMC comparative effectiveness study was not done or described. This device is not an AI-assisted diagnostic tool; it is a physiological signal transmitter and receiver.

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

No standalone algorithm performance study was described. This device is hardware that transmits physiological signals.

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

Not applicable. No ground truth for a clinical study is mentioned. The device's safety and effectiveness are supported by its design adherence to standards and the performance of predicate devices.

8. The sample size for the training set

Not applicable. As this is not an AI/machine learning device, there is no mention of a training set.

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

Not applicable. As this is not an AI/machine learning device, there is no training set mentioned.

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