Acumen Assisted Fluid Management (AFM) Software Feature

The Acumen Assisted Fluid Management (AFM) Software Feature, enhanced with an AFM Prompt Reclassifier algorithm, aims to optimize fluid therapy for surgical patients by providing refined, data-driven suggestions on fluid administration. It utilizes real-time hemodynamic data processed through a dual-algorithmic approach—a core algorithm for initial assessment and a reclassifier for enhanced accuracy—to predict and improve patient response to fluid boluses, specifically by increasing the positive predictive value of "Fluid Bolus Suggested" prompts for achieving desired changes in stroke volume.

The Acumen Assisted Fluid Management (AFM) Software Feature, developed by Edwards Lifesciences, is designed as an adjunctive open-loop fluid therapy recommender for surgical patients aged 18 and older who require advanced hemodynamic monitoring. Its core function is to provide clinicians with physiological insights into a patient's estimated response to fluid therapy and their associated hemodynamics by offering suggestions. These suggestions, based on a core AFM algorithm and presented via a graphical user interface, guide clinicians regarding a patient's physiological condition and potential response to fluid administration. However, the ultimate decision to administer a fluid bolus rests with the clinician, who must consider the patient's overall hemodynamic status, and the software's suggestions are not intended for sole therapeutic decision-making. This iteration of the Acumen AFM Software Feature introduces an AFM Prompt Reclassifier (AFM PR) algorithm, which works in conjunction with the existing core AFM algorithm. The AFM PR algorithm's purpose is to re-assess the fluid bolus recommendations generated by the core algorithm by analyzing the patient's current hemodynamics. It can either confirm the original prompt or reclassify it, for instance, changing a "Test Bolus Suggested" prompt to a "Fluid Bolus Suggested" prompt or vice versa. This acts as a secondary check, aiming to increase the likelihood that "Fluid Bolus Suggested" prompts result in the desired change in stroke volume. Performance validation using an archived dataset from a US IDE Study (307 patients, 1229 data points) demonstrated that the AFM PR algorithm improved the response rate for "Fluid Bolus Suggested" prompts, indicating enhanced optimization of the software's impact on patient hemodynamics without raising new safety or effectiveness concerns.

AI Regulatory Concerns

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• Q1. What specific hemodynamic parameters does the core AFM algorithm primarily rely on to generate its initial fluid responsiveness prompts?; How does the AFM Prompt Reclassifier algorithm differentiate between situations warranting a "Test Bolus" versus a "Fluid Bolus," and what are the critical thresholds for reclassification?; What was the quantitative improvement in response rate for "Fluid Bolus Suggested" prompts with the addition of the AFM PR algorithm compared to the core AFM algorithm alone in the validation study?; Are there specific patient subpopulations or surgical contexts where the AFM PR algorithm demonstrates significantly higher or lower efficacy in improving fluid responsiveness predictions?; Beyond stroke volume, what other hemodynamic or physiological outcomes were monitored or considered to assess the overall impact and safety of the refined fluid administration suggestions?