OBJECTIVES: Continuous flow left ventricular assist devices are used in end-stage systolic heart failure. However, about one half of the patients with heart failure exhibit diastolic dysfunction with a normal ejection fraction. In the present study, the possible hemodynamic consequences of continuous flow left ventricular assist devices use for these patients were investigated. METHODS: A previously developed cardiovascular model was modified to reproduce the peculiar hemodynamics of heart failure with a normal ejection fraction. The model was based on and validated with patient data derived from the published data. A continuous flow left ventricular assist device model was included and the hemodynamic effects of pump support evaluated at rest and during exercise. RESULTS: The model accurately reproduced the published data both at rest and during exercise, leading to simulated hemodynamic values within the standard deviations of patient variability. At rest, pump support decreased the end-diastolic left ventricular pressure (6 vs 15 mm Hg) and volume (88 vs 135 mL). During exercise, maximal pump support substantially unloaded the left ventricle (end-diastolic pressure, 14 vs 35 mm Hg; volume, 133 vs 158 mL) and the pulmonary venous circulation (left atrial pressure, 12 vs 24 mm Hg) and resulted in a slight increase in cardiac output (11.7 vs 9.9 L/min). CONCLUSIONS: The simulation results suggested that continuous flow left ventricular assist devices improve the hemodynamics in patients with heart failure and a normal ejection fraction. For an optimal use of continuous flow left ventricular assist devices, low speeds should be maintained at rest, to avoid suction. However, during physical activity, higher speeds are needed to prevent an abnormal increase in the ventricular filling pressures typical of patients with heart failure and a normal ejection fraction.
OBJECTIVES: Continuous flow left ventricular assist devices are used in end-stage systolic heart failure. However, about one half of the patients with heart failure exhibit diastolic dysfunction with a normal ejection fraction. In the present study, the possible hemodynamic consequences of continuous flow left ventricular assist devices use for these patients were investigated. METHODS: A previously developed cardiovascular model was modified to reproduce the peculiar hemodynamics of heart failure with a normal ejection fraction. The model was based on and validated with patient data derived from the published data. A continuous flow left ventricular assist device model was included and the hemodynamic effects of pump support evaluated at rest and during exercise. RESULTS: The model accurately reproduced the published data both at rest and during exercise, leading to simulated hemodynamic values within the standard deviations of patient variability. At rest, pump support decreased the end-diastolic left ventricular pressure (6 vs 15 mm Hg) and volume (88 vs 135 mL). During exercise, maximal pump support substantially unloaded the left ventricle (end-diastolic pressure, 14 vs 35 mm Hg; volume, 133 vs 158 mL) and the pulmonary venous circulation (left atrial pressure, 12 vs 24 mm Hg) and resulted in a slight increase in cardiac output (11.7 vs 9.9 L/min). CONCLUSIONS: The simulation results suggested that continuous flow left ventricular assist devices improve the hemodynamics in patients with heart failure and a normal ejection fraction. For an optimal use of continuous flow left ventricular assist devices, low speeds should be maintained at rest, to avoid suction. However, during physical activity, higher speeds are needed to prevent an abnormal increase in the ventricular filling pressures typical of patients with heart failure and a normal ejection fraction.
Authors: Chihiro Miyagi; Barry D Kuban; Christine R Flick; Anthony R Polakowski; Takuma Miyamoto; Jamshid H Karimov; Randall C Starling; Kiyotaka Fukamachi Journal: Heart Fail Rev Date: 2021-05-01 Impact factor: 4.214
Authors: Chihiro Miyagi; Kiyotaka Fukamachi; Barry D Kuban; Shengqiang Gao; Takuma Miyamoto; Christine R Flick; Anthony R Polakowski; David J Horvath; Randall C Starling; Jamshid H Karimov Journal: J Card Fail Date: 2022-01-10 Impact factor: 6.592
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Authors: Andreas Escher; Young Choi; Fraser Callaghan; Bente Thamsen; Ulrich Kertzscher; Martin Schweiger; Michael Hübler; Marcus Granegger Journal: Ann Biomed Eng Date: 2020-03-30 Impact factor: 3.934
Authors: Christoph Gross; Libera Fresiello; Thomas Schlöglhofer; Kamen Dimitrov; Christiane Marko; Martin Maw; Bart Meyns; Dominik Wiedemann; Daniel Zimpfer; Heinrich Schima; Francesco Moscato Journal: PLoS One Date: 2020-03-18 Impact factor: 3.240