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The ClearSight™ finger cuff is indicated for patients over 18 years of age to noninvasively measure blood pressure and associated hemodynamic parameters when used with the EV1000 Clinical Platform NI.

The ClearSight™ finger cuff noninvasively measures blood pressure and associated hemodynamic parameters when used with a compatible Edwards' hemodynamic monitor.
The ClearSight™ system consists of a Pump-Unit, a Pressure Controller (PC2) that is worn on the wrist, a Heart Reference Sensor (EVHRS or also referred to as HRS), the ClearSight™ finger cuff, and a compatible Edwards monitor.
The ClearSight system is currently compatible and cleared for use with the monitor of the EV1000 Clinical Platform NI (EV1000NI). The purpose of this 510(k) submission is to obtain clearance for enhancements of the ClearSight™ finger cuff as well as updated indications for use to allow for flexibility of the ClearSight finger cuff to be used with a compatible Edwards' hemodynamic monitoring system.

The provided document describes the clearance of the ClearSight™ finger cuff (K190130) by the FDA. The device is a non-invasive blood pressure measurement system.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

The document does not explicitly present a table of acceptance criteria with specific numerical targets. However, it indicates that the device's performance was evaluated based on the ISO 81060-2 standard, which defines clinical validation requirements for non-invasive sphygmomanometers. This standard typically specifies accuracy requirements in terms of mean difference and standard deviation between the device's measurements and a reference standard (e.g., intra-arterial blood pressure).

The document states: "The ClearSight™ finger cuff have successfully passed all testing." This implies that the device met the performance requirements outlined in ISO 81060-2, but the specific numerical performance metrics (e.g., mean difference, standard deviation) are not provided in this summary.

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

The document mentions a "clinical validation study" was conducted in accordance with ISO 81060-2. However, it does not specify the sample size used for this study. It also does not provide information on the data provenance (e.g., country of origin of the data, retrospective or prospective nature of the study).

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)

Given that the clinical validation was for a blood pressure measurement device according to ISO 81060-2, the "ground truth" would typically be established by a reference standard. For blood pressure measurements, this is commonly invasive intra-arterial blood pressure. The standard also requires specific procedures for simultaneous measurements.

The document does not mention the involvement of experts in establishing the "ground truth" in the way it would apply to imaging or diagnostic algorithms requiring expert interpretation. Instead, the ground truth for blood pressure measurement is typically objective physiological data obtained through a recognized reference method.

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

For blood pressure measurement accuracy, the concept of "adjudication" (as found in diagnostic studies with observer variability) is generally not directly applicable. The comparison is typically between the device's automated measurements and the objective reference standard. Any discrepancies are analyzed statistically, not through an adjudication process between human readers.

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 comparative effectiveness study was done, and this type of study is not relevant for this device. The ClearSight™ finger cuff is a non-invasive blood pressure measurement system, not an AI-powered diagnostic tool that assists human readers in interpreting images or complex data. Therefore, the concept of human reader improvement with or without AI assistance does not apply.

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

This device is inherently a standalone measurement device. It directly measures blood pressure and associated hemodynamic parameters. Its performance, as validated by the clinical study, is the "algorithm only" performance (though it's a hardware device with embedded algorithms). The indications state it is "used with the EV1000 Clinical Platform NI," implying it's part of a system, but its primary function is direct measurement, not an assistive role to a human.

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

As indicated under point 3, the ground truth for the clinical validation of a non-invasive blood pressure monitor according to ISO 81060-2 is almost certainly invasive intra-arterial blood pressure measurements, considered the gold standard for continuous blood pressure monitoring.

8. The sample size for the training set

The document does not mention a training set. For a traditional medical device like a blood pressure cuff, there isn't a "training set" in the same sense as for machine learning algorithms. The device is designed, calibrated, and then validated.

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

As there is no mention of a training set in the context of machine learning, this question is not applicable to the information provided about the ClearSight™ finger cuff. The device's underlying principles are based on physiological measurement techniques, not on learning from a labeled dataset.

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