Prediction of Hemodynamic Response to Epinephrine via Model-Based System Identification.

In this study, we present a system identification approach to the mathematical modeling of hemodynamic responses to vasopressor-inotrope agents. We developed a hybrid model called the latency-dose-response-cardiovascular (LDC) model that incorporated 1) a low-order lumped latency model to reproduce the delay associated with the transport of vasopressor-inotrope agent and the onset of physiological effect, 2) phenomenological dose-response models to dictate the steady-state inotropic, chronotropic, and vasoactive responses as a function of vasopressor-inotrope dose, and 3) a physiological cardiovascular model to translate the agent's actions into the ultimate response of blood pressure. We assessed the validity of the LDC model to fit vasopressor-inotrope dose-response data using data collected from five piglet subjects during variable epinephrine infusion rates. The results suggested that the LDC model was viable in modeling the subjects' dynamic responses: After tuning the model to each subject, the r (2) values for measured versus model-predicted mean arterial pressure were consistently higher than 0.73. The results also suggested that intersubject variability in the dose-response models, rather than the latency models, had significantly more impact on the model's predictive capability: Fixing the latency model to population-averaged parameter values resulted in r(2) values higher than 0.57 between measured versus model-predicted mean arterial pressure, while fixing the dose-response model to population-averaged parameter values yielded nonphysiological predictions of mean arterial pressure. We conclude that the dose-response relationship must be individualized, whereas a population-averaged latency-model may be acceptable with minimal loss of model fidelity.