Model-based sensor of hemodynamics in critical care
A model-based approach for real time tracking of key hemodynamic parameters in a porcine model of pulmonary embolism is presented. The model and methods are clinically validated by successfully capturing a significantly wide range of dynamics and reproducing all the physiological correct responses. The mean prediction errors were at most 4.1% in the pressures and 3.1% in the volumes for 6 sets of clinical data. Pulmonary resistance was found to rise dramatically in all cases with total increases ranging from 90 − 261%. The septum volume significantly decreased corresponding to a movement of the right ventricle to the left, consistent with accepted hemodynamic response to pulmonary embolism. The model correctly predicts right ventricular-vascular decoupling and compares well to a similar highly invasive measure based on rapid inferior vena cava occlusion manoeuvre. The results show the potential for real-time sensor integration in critical care where common pressure and volume measurements can be aggregated into a simpler form that more directly points to cardiac disease states and assists in optimum therapy selection.