Cardiovascular

QMS · Adjunctive Open Loop Fluid Therapy Recommender

Cardiovascular · 21 CFR 870.5600 · Class 2

Overview

Product CodeQMS
Device NameAdjunctive Open Loop Fluid Therapy Recommender
Regulation21 CFR 870.5600
Device ClassClass 2
Review PanelCardiovascular
3rd-Party ReviewableYes

Identification

The adjunctive open loop fluid therapy recommender is a prescription device that uses software algorithms to analyze cardiovascular vital signs and predict a patient's estimated response to fluid therapy. The device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy.

Classification Rationale

Class II (special controls). The special controls for this device are:

Special Controls

In combination with the general controls of the FD&C Act, the adjunctive open loop fluid therapy recommender is subject to the following special controls:

*Classification.* Class II (special controls). The special controls for this device are:(1) Clinical performance testing under anticipated conditions of use must fulfill the following: (i) A summary of the clinical performance testing must include the relevant patient demographics, and any statistical techniques used for analyzing the data; (ii) Subjects must be representative of the intended use population for the device. Any selection criteria or sample limitations must be fully described and justified; (iii) Testing must demonstrate the recommendation consistency using the expected range of data sources and data quality encountered in the intended patients, users, and environments; and (iv) Testing must evaluate the relationship between algorithm recommendations, therapeutic actions, and predicted physiological event or status. (2) A software description and the results of verification and validation testing based on a comprehensive hazard analysis and risk assessment must be provided, including: (i) A full characterization of the software technical parameters, including algorithms; (ii) A description of the expected recommendation, accounting for differences in patient condition and environment; (iii) A description of all mitigations for user error or failure of any subsystem components (including signal detection, signal analysis, data display, and storage) that affect the device's recommendations; (iv) A characterization of algorithm sensitivity to variations in user inputs; (v) A characterization of sensor accuracy and performance; (vi) A description of sensor data quality control measures; and (vii) Safeguards to reduce the possibility of fluid overload. (3) A scientific justification for the validity of the algorithm(s) must be provided. This justification must include non-clinical verification and validation of the algorithm calculations and clinical validation using an independent data set. (4) A human factors and usability engineering assessment must be provided. (5) Labeling must include: (i) A description of what the device measures, how the device decides to issue recommendations, and the expected range of frequency of recommendations, while accounting for differences in patient condition and environment; (ii) Detailed information regarding limitations of the device's algorithm, and key assumptions made when the device issues a recommendation; (iii) Warnings identifying sensor acquisition factors that may impact measurement results; (iv) Warnings identifying user errors that affect the device's recommendations; (v) Detailed information regarding the expected impact of user input errors on the device recommendations; (vi) Guidance for interpretation of the device's recommendations, including a description that the recommendation is adjunctive to other physical vital sign parameters and patient information; (vii) Description of the impact of the compatible sensor(s) on the device's performance; (viii) The expected performance of the device for all intended patients, users, and environments; (ix) Relevant characteristics of the patients studied in the clinical validation (such as age, gender, race or ethnicity, and patient condition) and a summary of validation results; and (x) Description of the software safeguards that are in place to prevent fluid overload, and description of any limitation of the software safeguards.

Cleared Devices (2)

RecordDevice NameApplicantDecision DateDecision
K233984Acumen Assisted Fluid Management (AFM) Software FeatureEdwards Lifesciences, LLCAug 2, 2024SESE
DEN190029Acumen Assisted Fluid Management (AFM) Software FeatureEdwards LifesciencesNov 13, 2020DENG

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