Adding these three diseases to the cardiovascular model and comparing the model predictions to the cases reported in the literature has helped to clarify the potential of this methodology for predicting the effects of therapies and maneuvers. In the process, a number of effects were discovered and then verified. Initially, propranolol was modeled as decreasing the effect of sympathetic stimulation on heart rate and inotropy. It became clear that the predicted SVR was too low, making it necessary to add the indirect effect of propranolol on SVR by leaving alpha constriction unopposed. Similarly, the propranolol effect on PVR was added, and there is some evidence for this, at least in acute interventions. Hydralazine was originally modeled as decreasing the SVR, but comparison of predictions to reported values indicated that there must also be an effect on PVR, which was confirmed by the literature. The apparent inotropic effect of hydralazine has also been alluded to in the literature. Thus, the model seems to be very sensitive to the effects of the therapies and able to account for the pathophysiological states with considerable accuracy.
This effort has also pointed out some of the weaknesses of the model. One of the main problems was the presence of heart failure in three of the cases, a pathological state not yet adequately covered by the model. There are places in the model for adjusting the basic systolic function, but the sympathetic response also changes in heart failure. Sympathetic response in general is a more complicated and subtle issue than is captured in the model, particularly in how vascular resistance changes. The dependence of systolic time on heart rate and valvular lesions is only partially captured. Still, the majority of the model seems to be robust and adequate for making predictions, at least in cases with the appropriate patient data. Therefore, it should be possible to extend this model to the other important disease entities in the domain as well as correct the weaknesses.
The computational methodology also shows promise in that it allows rapid computation of the steady state patient values and allows the user to investigate the relative contribution of various pathways to a particular effect.