Scaling cardiovascular parameters for population simulations

Computational models of cardiovascular function depend on the specification of parameters, whose values can depend quite strongly on particular subject characteristics (e.g., age, height, weight, disease state). In this study, we present a scaling scheme, based on the principle of elastic similarity, that allows for referencing of cardiovascular parameters to different anthropometric profiles. Combined with a sampling procedure, this scaling scheme allows for simulations of subjects of different body size. Simulated steady-state mean values, standard deviations, and ranges of important hemodynamic variables match their experimental analogs of the normal healthy adult population quite well. We conclude that scaling of cardiovascular parameters on the basis of elastic similarity provides a valid basis for incorporating the effects of size in population simulations.