In Vivo Comparison of Algorithms Estimating Left Ventricular Stroke Work From LVAD-Derived Pump Parameters
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Published on: June 11, 2020
Moriz A Habigt1, Marc Hein1, Mare Mechelinck1
1Department of Anaesthesiology, Medical Faculty, RWTH Aachen University, Aachen, Germany.
Background:
Accurate assessment of cardiac work during left ventricular assist device (LVAD) therapy is essential for patient management, device explantation timing, and adaptive control algorithm development. While invasive pressure-volume methods provide accurate work and contractility assessment, their clinical applicability is limited. Non-invasive algorithms utilizing inherent pump parameters offer a promising alternative, yet no systematic comparison exists.
Methods:
Six non-invasive algorithms for estimating stroke work (SW) were compared in 22 healthy German Landrace pigs (48.9 ± 2.6 kg) with a Deltastream DP3 LVAD: maximal LVAD flow derivative, motor power-LV pressure relationship, pressure head-flow relationship, systolic fraction of pressure-flow area, and total/pulsatile components of pump current and flow. After isoflurane-induced heart failure, four interventions were performed: preload reduction (inferior vena cava occlusion, n = 105), afterload increase (aortic balloon occlusion, n = 97), dobutamine infusion (n = 21), and speed ramps (n = 14). Linear multilevel modeling revealed significant main effects for algorithm (χ2 = 582.38), intervention type (χ2 = 73.77), and their interaction (χ2 = 324.80; all p < 0.001), explaining 54.04% of variability.
Results:
The pressure head-flow algorithm demonstrated consistently high correlations across interventions, though requiring semi-invasive pressure measurements. The pump flow area algorithm performed robustly during preload, afterload, and speed ramps but failed to capture SW changes during dobutamine. The systolic fraction algorithm achieved the highest correlations during dobutamine but frequently failed mathematical optimization, limiting applicability.
Conclusion:
No single algorithm performed optimally across all conditions, necessitating context-specific selection. Pronounced inter-individual variability underscores the importance of patient-specific factors. These findings provide the first systematic comparison of non-invasive SW algorithms during LVAD therapy, offering guidance for algorithm selection.
