How does a loss of aortic compliance impact critical care metrics of hemodynamics during steady-state and transient conditions in an in silico model?
In silico computational model generating parameters quantifying ventricular-vascular coupling and pressure-volume construct
Simulation of loss from normal-to-stiff aortic compliance (CA) and decrease in preload during vascular occlusion
Normal aortic compliance
Changes in critical care metrics of hemodynamics (pulse pressure, end-systolic pressure, arterial compliance, arterial elastance, dynamic arterial elastance, and mechanical efficiency)surrogate
An in silico model demonstrates that critical care hemodynamic metrics are sensitive to changes in aortic compliance, providing insights into the management of intraoperative hypotension.
Abstract Mean arterial pressure and cardiac output provide insufficient guidance for the management of intraoperative hypotension (IOH). In silico models offer additional insights into acute changes in hemodynamic parameters that may be encountered during IOH. A computational model (CM) generated parameters quantifying ventricular–vascular coupling, and pressure–volume construct across levels of aortic compliance (C A ). We studied how a loss from normal‐to‐stiff C A impacts critical care metrics of hemodynamics during vascular occlusion. Pulse pressure (PP), end‐systolic pressure ( P es ), arterial compliance (Art‐ca), arterial elastance (Art‐ea), and dynamic arterial elastance (Eadyn), along mechanical efficiency (ME) were measured at five levels of C A . A loss in C A impacted all variables. During steady‐state conditions, PP, P es , and stroke work increased significantly as C A decreased. Art‐ca decreased and Art‐ea increased similarly; Eadyn increased and ME decreased. During a decrease in preload across all C A levels, arterial dynamics measures remained linear. The CM demonstrated that a loss in C A impacts measures of arterial dynamics during steady‐state and transient conditions and the model demonstrates that critical care metrics are sensitive to changes in C A . While Art‐ca and Art‐ea were sensitive to changes in preload, Eadyn did not change.
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Lawrence J. Mulligan
Cooper University Hospital
Justin Ungerleider
Cooper Medical School of Rowan University
Adam Friedman
Brookdale University Hospital and Medical Center
Physiological Reports
North Dakota State University
University of North Dakota
Cooper University Hospital
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Mulligan et al. (Wed,) studied this question.
synapsesocial.com/papers/6a1cfa4e7f448865515d9ca9 — DOI: https://doi.org/10.14814/phy2.15920
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