Model-based computation of total stressed blood volume from a preload reduction manoeuvre

• Published in: Mathematical biosciences Vol. 265; pp. 28 - 39
• Main Authors: Pironet, Antoine, Desaive, Thomas, Geoffrey Chase, J., Morimont, Philippe, Dauby, Pierre C.
• Format: Journal Article Web Resource
• Language: English
• Published: United States Elsevier Inc 01.07.2015; Elsevier
• Subjects: Animals; Blood Volume - physiology; Cardiovascular & respiratory systems; Cardiovascular System; Engineering, computing & technology; Fluid Therapy; Hemodynamics - physiology; Human health sciences; Ingénierie, informatique & technologie; Mathematical model; Models, Animal; Models, Theoretical; Parameter identification; Sciences de la santé humaine; Stressed blood volume; Swine; Systèmes cardiovasculaire & respiratoire; Stressed blood volume; Cardiovascular system; CVS; SV; MCFP; SBV; Fluid therapy; ICU; Parameter identification; Mathematical model; CO
• ISSN: 0025-5564; 1879-3134
• DOI: 10.1016/j.mbs.2015.03.015

•Total stressed blood volume (SBV) is associated with the success of fluid therapy.•SBV dictates the behavior of mathematical models of the cardiovascular system.•SBV is computed using data from a preload reduction manoeuvre.•The method proposed is more straightforward than the traditional one. Total stressed blood volume is an important parameter for both doctors and engineers. From a medical point of view, it has been associated with the success or failure of fluid therapy, a primary treatment to manage acute circulatory failure. From an engineering point of view, it dictates the cardiovascular system’s behavior in changing physiological situations. Current methods to determine this parameter involve repeated phases of circulatory arrests followed by fluid administration. In this work, a more straightforward method is developed using data from a preload reduction manoeuvre. A simple six-chamber cardiovascular system model is used and its parameters are adjusted to pig experimental data. The parameter adjustment process has three steps: (1) compute nominal values for all model parameters; (2) determine the five most sensitive parameters; and (3) adjust only these five parameters. Stressed blood volume was selected by the algorithm, which emphasizes the importance of this parameter. The model was able to track experimental trends with a maximal root mean squared error of 29.2%. Computed stressed blood volume equals 486 ± 117 ml or 15.7 ± 3.6 ml/kg, which matches previous independent experiments on pigs, dogs and humans. The method proposed in this work thus provides a simple way to compute total stressed blood volume from usual hemodynamic data.