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      Stroke Volume Monitoring: Novel Continuous Wave Doppler Parameters, Algorithms and Advanced Noninvasive Haemodynamic Concepts

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          Abstract

          Purpose of Review

          Adequate oxygen delivery is essential for life, with hypoxia resulting in dysfunction, and ultimately death, of the cells, organs and organism. Blood flow delivers the oxygen bound in the blood, while haemodynamics is the science of blood flow. Stroke volume (SV) is the fundamental unit of blood flow, and reflects the interdependent performance of the heart, the vessels and the autonomic nervous system. However, haemodynamic management remains generally poor and predominantly guided by simple blood pressure observations alone.

          Recent Findings

          Doppler ultrasound measures SV with unequalled clinical precision when operated by trained personnel. Combining SV with BP measurements allows calculation of flow-pressure based measures which better reflect cardiovascular performance and allows personalised physiologic and pathophysiologic modelling consistent with Frank’s and Starling’s observations.

          Summary

          Doppler SV monitoring and novel flow-pressure parameters may improve our understanding of the cardiovascular system and lead to improved diagnosis and therapy. This review examines the physics and practice of Doppler SV monitoring and its application in advanced haemodynamics.

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          Most cited references78

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          Ueber Diffusion

          Adolf Fick (1855)
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            Cardiac power is the strongest hemodynamic correlate of mortality in cardiogenic shock: a report from the SHOCK trial registry.

            We sought to analyze clinical, angiographic, and outcome correlates of hemodynamic parameters in cardiogenic shock. The significance of right heart catheterization in critically ill patients is controversial, despite the prognostic importance of the derived measurements. Cardiac power is a novel hemodynamic parameter. A total of 541 patients with cardiogenic shock who were enrolled in the SHould we emergently revascularize Occluded Coronaries for cardiogenic shocK (SHOCK) trial registry were included. Cardiac power output (CPO) (W) was calculated as mean arterial pressure x cardiac output/451. On univariate analysis, CPO, cardiac power index (CPI), cardiac output, cardiac index, stroke volume, left ventricular work, left ventricular work index, stroke work, mean arterial pressure, systolic and diastolic blood pressure (all p < 0.001), coronary perfusion pressure (p = 0.002), ejection fraction (p = 0.013), and pulmonary artery systolic pressure (p = 0.047) were associated with in-hospital mortality. In separate multivariate analyses, CPO (odds ratio per 0.20 W: 0.60 [95% confidence interval, 0.44 to 0.83], p = 0.002; n = 181) and CPI (odds ratio per 0.10 W/m(2): 0.65 [95% confidence interval, 0.48 to 0.87], p = 0.004; n = 178) remained the strongest independent hemodynamic correlates of in-hospital mortality after adjusting for age and history of hypertension. There was an inverse correlation between CPI and age (correlation coefficient: -0.334, p < 0.001). Women had a lower CPI than men (0.29 +/- 0.11 vs. 0.35 +/- 0.15 W/m(2), p = 0.005). After adjusting for age, female gender remained associated with CPI (p = 0.032). Cardiac power is the strongest independent hemodynamic correlate of in-hospital mortality in patients with cardiogenic shock. Increasing age and female gender are independently associated with lower cardiac power.
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              Effective arterial elastance as index of arterial vascular load in humans.

              This study tested whether the simple ratio of ventricular end-systolic pressure to stroke volume, known as the effective arterial elastance (Ea), provides a valid measure of arterial load in humans with normal and aged hypertensive vasculatures. Ventricular pressure-volume and invasive aortic pressure and flow were simultaneously determined in 10 subjects (four young normotensive and six older hypertensive). Measurements were obtained at rest, during mechanically reduced preload, and after pharmacological interventions. Two measures of arterial load were compared: One was derived from aortic input impedance and arterial compliance data using an algebraic expression based on a three-element Windkessel model of the arterial system [Ea(Z)], and the other was more simply measured as the ratio of ventricular end-systolic pressure to stroke volume [Ea(PV)]. Although derived from completely different data sources and despite the simplifying assumptions of Ea(PV), both Ea(Z) and Ea(PV) were virtually identical over a broad range of altered conditions: Ea(PV) = 0.97.Ea(Z) + 0.17; n = 33, r2 = 0.98, SEE = 0.09, p less than 0.0001. Whereas Ea(PV) also correlated with mean arterial resistance, it exceeded resistance by as much as 25% in older hypertensive subjects (because of reduced compliance and wave reflections), which better indexed the arterial load effects on the ventricle. Simple methods to estimate Ea (PV) from routine arterial pressures were tested and validated. Ea(PV) provides a convenient, useful method to assess arterial load and its impact on the human ventricle. These results highlight effects of increased pulsatile load caused by aging or hypertension on the pressure-volume loop and indicate that this load and its effects on cardiac performance are often underestimated by mean arterial resistance but are better accounted for by Ea.
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                Author and article information

                Contributors
                +61 2 92474144 , rap.echo@bigpond.com
                Journal
                Curr Anesthesiol Rep
                Curr Anesthesiol Rep
                Current Anesthesiology Reports
                Springer US (New York )
                1523-3855
                2167-6275
                13 November 2017
                13 November 2017
                2017
                : 7
                : 4
                : 387-398
                Affiliations
                [1 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, Ultrasound and Cardiovascular Monitoring, Critical Care Research Group, School of Medicine, , The University of Queensland, ; Brisbane, Australia
                [2 ]ISNI 0000 0004 0402 6494, GRID grid.266886.4, Discipline of Intensive Care, , University of Notre Dame Australia, ; Sydney, Australia
                [3 ]Department of Anaesthetics and Intensive Care, Bathurst Base Hospital, Bathurst, NSW Australia
                [4 ]ISNI 0000 0004 0402 6494, GRID grid.266886.4, University of Notre Dame Australia, ; Sydney, Australia
                Article
                235
                10.1007/s40140-017-0235-4
                5696447
                3b627965-6a8c-42ab-b33f-33f791269e52
                © The Author(s) 2017

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                Categories
                Advances in Monitoring for Anesthesia (LAH Critchley, Section Editor)
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2017

                stroke volume,continuous wave doppler,haemodynamic monitoring,algorithms,concepts

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