Abstract

IntroductionAccurate, continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy. However, direct measurements are highly invasive in clinical practice, and current procedures for estimating SV require specialized devices and significant approximation.MethodThis study investigates the accuracy of a three element Windkessel model combined with an aortic pressure waveform to estimate SV. Aortic pressure is separated into two components capturing; 1) resistance and compliance, 2) characteristic impedance. This separation provides model-element relationships enabling SV to be estimated while requiring only one of the three element values to be known or estimated. Beat-to-beat SV estimation was performed using population-representative optimal values for each model element. This method was validated using measured SV data from porcine experiments (N = 3 female Pietrain pigs, 29–37 kg) in which both ventricular volume and aortic pressure waveforms were measured simultaneously.ResultsThe median difference between measured SV from left ventricle (LV) output and estimated SV was 0.6 ml with a 90% range (5th–95th percentile) −12.4 ml–14.3 ml. During periods when changes in SV were induced, cross correlations in between estimated and measured SV were above R = 0.65 for all cases.ConclusionThe method presented demonstrates that the magnitude and trends of SV can be accurately estimated from pressure waveforms alone, without the need for identification of complex physiological metrics where strength of correlations may vary significantly from patient to patient.

Highlights

  • Accurate, continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy

  • The method presented demonstrates that the magnitude and trends of SV can be accurately estimated from pressure waveforms alone, without the need for identification of complex physiological metrics where strength of correlations may vary significantly from patient to patient

  • This paper presents a method for continuously estimating SV from aortic pressure measurements

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Summary

Introduction

Continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy. It is important to synthesise raw clinical data such as blood pressure and heart-rate into useful physiological parameters such as stroke volume and contractility that can be used to improve diagnosis and treatment [5] This goal can be accomplished using computational models and patient-specific parameter identification methods to unmask hidden dynamics and interactions in measured clinical data [6,7]. This approach can create a clearer physiological picture from the available data and its time-course, making diagnosis simpler and more accurate, enabling personalised care [8,9].

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