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The FlexView™ Clinical Monitoring System is intended for use as a secondary annunciation of compatible primary medical device alarms.

The FlexView™ Clinical Monitoring System is for use as an accessory to primary medical devices and is currently compatible with puise oximeters, infusion pumps and ventilators. The FlexView™ Clinical Monitoring System is to supplement and not replace any part of the current primary medical device monitoring procedure.

The FlexView™ Clinical Monitoring System is for use by healthcare professionals trained in the primary medical devices that are being monitored. The FlexView™ Clinical Monitoring System is not considered to be diagnostic without skilled interpretation and does not replace physician's care.

The Flex\lew™ Clinical Monitoring System is for use with patient populations being monitored by healthcare professionals utilizing compatible pulse oximeters, infusion pumps and ventilators.

The FlexView™ Clinical Monitoring System is for use in healthcare facilities such as hospitals, or free standing surgical centers.

The FlexView™ Clinical Monitoring System is a PC based central monitoring station used to acquire information from primary medical devices (pulse oximeters, infusion pumps and redisplay it on a single monitor in a central location. It allows the remote monitoring of multiple medical devices simultaneously and provides secondary annunciation of the alarms from the primary medical devices.

This device, the FlexView™ Clinical Monitoring System, is a Class II medical device (System, Network and Communication, Physiological Monitors). The 510(k) summary indicates that its safety and effectiveness were demonstrated through risk, verification, and validation testing, concluding that its performance, functionality, and safety characteristics are substantially equivalent to the predicate device (FlexView™ Clinical Monitoring System, K003998).

However, the provided text does not contain the specific details necessary to fully answer all aspects of your request regarding acceptance criteria and a study proving device performance in the way you've outlined. The submission focuses on substantial equivalence to a predicate device rather than presenting a novel clinical study with explicit acceptance criteria for performance metrics like accuracy, sensitivity, or specificity.

Here's a breakdown of what information can and cannot be extracted from the provided document, based on your questions:

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

The document does not explicitly state specific acceptance criteria (e.g., minimum accuracy, sensitivity, specificity values) for its performance, nor does it present specific numerical performance results (like sensitivity or specificity) for the device. Instead, it states:

"Test results demonstrated that the modified FlexView™ Clinical Monitoring System performance, functionality and safety characteristics are substantially equivalent to the predicate device."

This implies the acceptance criterion was likely substantial equivalence in performance, functionality, and safety to the predicate device (K003998) through a series of internal verification and validation tests, rather than meeting predefined clinical performance thresholds.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. The submission references "risk and verification and validation testing," but does not detail the methodology, sample sizes, or data provenance (e.g., patient data, simulated data).

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)

This information is not provided. As no clinical study with a "test set" and "ground truth" derived from expert review is described, these details are absent.

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

This information is not provided.

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 MRMC study was conducted or described. This device is a monitoring system for secondary annunciation of alarms from other medical devices, not an AI-powered diagnostic tool requiring human interpretation or assistance for analysis. Therefore, the concept of "human readers improving with AI assistance" does not apply in this context.

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

The device's function is the "secondary annunciation of compatible primary medical device alarms" and it's stated to "supplement and not replace any part of the current primary medical device monitoring procedure." It is intended for "use by healthcare professionals." Therefore, it is not a standalone algorithm without human involvement. Its primary function is to relay information to human healthcare professionals.

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

This information is not provided. Given the nature of the device (a monitoring system for alarm annunciation), ground truth might pertain to the accuracy and timeliness of alarm relay, rather than diagnostic accuracy. It's plausible that internal engineering validation and verification tests, potentially using simulated or recorded physiological data, were used to confirm alarm processing and display accuracy, but the specifics are not detailed.

8. The sample size for the training set

This information is not provided. The device is described as a "PC based central monitoring station," and while it likely involves software, there's no mention of machine learning or AI that would require a "training set" in the context of supervised learning.

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

This information is not provided, as there is no indication of a "training set" being used for a machine learning model.

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