8 isolated canine ventricles
Analytical formula predicting stroke volume based on ventricular properties (Ees, V0, and ejection time) and arterial impedance (3-element Windkessel model)
Direct measurement of stroke volume under identical arterial impedance conditions and preloads
Correlation between predicted and measured stroke volumesurrogate
A novel analytical framework accurately predicts stroke volume from the end-systolic pressure-volume relationships of the left ventricle and arterial system in an isolated canine model.
We developed a framework of analysis to predict the stroke volume (SV) resulting from the complex mechanical interaction between the ventricle and its arterial system. In this analysis, we characterized both the left ventricle and the arterial system by their end systolic pressure (Ps)-SV relationships and predicted SV from the intersection of the two relationship lines. The final output of the analysis was a formula that gives the SV for a given preload as a function of the ventricular properties (Ees, V0, and ejection time) and the arterial impedance properties (modeled in terms of a 3-element Windkessel). To test the validity of this framework for analyzing the ventriculoarterial interaction, we first determined the ventricular properties under a specific set of control arterial impedance conditions. With the ventricular properties thus obtained, we used the analytical formula to predict SVs under various combinations of noncontrol arterial impedance conditions and four preloads. The predicted SVs were compared with those measured while actually imposing the identical set of arterial impedance conditions and preload in eight isolated canine ventricles. The predicted SV was highly correlated (P less than 0.0001) with the measured one in all ventricles. The average correlation coefficient was 0.985 +/- 0.004 (SE), the slope 1.00 +/- 0.04, and the gamma-axis intercept 1.0 +/- 0.2 ml, indicating the accuracy of the prediction. We conclude that the representations of ventricle and arterial system by their Ps-SV relationships are useful in understanding how these two systems determine SV when they are coupled and interact.
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Kenji Sunagawa
Heart Failure & Transplant
W L Maughan
General Cardiology
Daniel Burkhoff
Rutgers, The State University of New Jersey
AJP Heart and Circulatory Physiology
Johns Hopkins University
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Sunagawa et al. (Tue,) studied this question.
synapsesocial.com/papers/69d9a033c7f0c3ae80a3e0d9 — DOI: https://doi.org/10.1152/ajpheart.1983.245.5.h773
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