Modelling the cardiovascular system.
Cardiovascular disease claims more lives than any other disease in westernised countries, affecting millions. Pinpointing cardiovascular system dysfunction is often difficult because the clinical signs, or the availability and interpretation of physiological measurements, are unreliable. Often patient-specific information is incomplete or confusing, as it comes from a diverse range of sources, such as invasive and non-invasive pressure measurements, flow rates and electrocardiogram signals. Health professionals therefore rely on intuition and experience to make a "clinical" diagnosis and decide treatment. Sometimes this approach results in multiple therapies being applied until a suitable treatment is found. Poor outcomes result from failure to quickly and correctly diagnose and treat the underlying condition. We introduce the concept of using full circulatory and cardiovascular models to aggregate the large number of diverse signals facing clinicians into a clear physiological picture of haemodynamic status. We briefly review the field, still in its infancy, of such models, focusing primarily on the basic approaches taken in the literature. Finally, we present one of the more advanced and best validated models, including initial results of animal validation studies. The overall approach is shown to have significant potential to provide clear, measured insight to replace often misled intuition in the monitoring, diagnosis and treatment of circulatory dysfunction in critical care. In the future, models and modern sensors will increasingly "invade" the critical care environment, and will provide the opportunity for better, more consistent care at the bedside in real time.
Shaw
Geoffrey M
GM
Department of Medicine, University of Otago, Christchurch, New Zealand. Geoff.Shaw@cdhb.govt.nz
Chase
J Geoffrey
JG
Starfinger
Christina
C
Smith
Bram W
BW
Hann
Christopher E
CE
Desaive
Thomas
T
Ghuysen
Alexandre
A
D000818:Animals; D002318:Cardiovascular Diseases / Q000503:physiopathology; D002320:Cardiovascular Physiological Phenomena; D006801:Humans; D008954:Models, Biological