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K Number
K082308
Device Name
MODIFICATION TO VIGILEO ARTERIAL PRESSURE CARDIAC OUTPUT/OXIMETRY MONITOR
Manufacturer
EDWARDS LIFESCIENCES, LLC.
Date Cleared
2008-12-09

(118 days)

Product Code
DXG
Regulation Number
870.1435
Type
Traditional
Panel
CV
Reference & Predicate Devices
K062134
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Vigileo APCO/Oximetry Monitor is indicated for continuously measuring hemodynamic parameters such as cardiac output and oximetry to assess oxygen delivery and consumption. When connected to an Edwards oximetry catheter, the monitor measures oximetry in adults and pediatrics.

Device Description

The Vigileo APCO/Oximetry Monitor is a microprocessor-based instrument which, when connected to a FloTrac sensor, continuously measures arterial pressure cardiac output (APCO). When connected to an Edwards oximetry catheter, the monitor measures oxygen saturation (oximetry) in adults or pediatrics. The monitor also calculates other derived parameters including cardiac index, stroke volume, stroke volume index, stroke volume variation, systemic vascular resistance, systemic vascular resistance, delivered oxygen, delivered oxygen index, and pulse oximetry saturation.

AI/ML Overview

This 510(k) submission describes the Vigileo APCO/Oximetry Monitor, which is intended to continuously measure hemodynamic parameters like cardiac output and oximetry. The submission claims substantial equivalence to a predicate device (Vigileo APCO/Oximetry Monitor: K062134) and states that functional testing was performed to demonstrate this equivalence. However, no specific acceptance criteria or detailed study results are provided in the provided text. The document focuses on the regulatory aspects of the submission and the determination of substantial equivalence based on functional testing and comparative analysis to the predicate device.

Given the information provided:

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

    • Acceptance Criteria: Not explicitly stated in the provided text. The submission broadly claims "equivalence to the predicate device" and that the device "has been demonstrated to be as safe and effective as the predicate device."
    • Reported Device Performance: Not detailed in terms of specific metrics. The text only states that the device "successfully underwent functional testing demonstrating equivalence to the predicate device."

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

    • Not specified in the provided text.

  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 as no specific test set requiring expert-established ground truth is described. The evaluation relies on functional testing and comparison to a predicate device.

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

    • Not applicable as no specific test set requiring 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 monitor, not an AI-assisted diagnostic tool for human readers.

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

    • The "functional testing" mentioned implies a standalone evaluation of the device's performance against the predicate. However, details of this testing are not provided.

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

    • Not explicitly stated. The "functional testing" would likely involve comparing the device's measurements against a known standard or a validated reference method, which serves as the de-facto ground truth for such a device. This reference method is typically the "predicate device" in a substantial equivalence claim.

  8. The sample size for the training set:

    • Not applicable, as this device is not described as involving a machine learning algorithm that requires a training set.

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

    • Not applicable, as no training set is mentioned.

§ 870.1435 Single-function, preprogrammed diagnostic computer.

(a)
Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow parameter based on information obtained from one or more electrodes, transducers, or measuring devices.(b)
Classification. Class II (performance standards).