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Updated: Jul 12, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Modelling the cardiovascular system
Geoffrey M Shaw1, J Geoffrey Chase, Christina Starfinger
1Department of Medicine, University of Otago, Christchurch, New Zealand. Geoff.Shaw@cdhb.govt.nz
Insights
Cardiovascular disease diagnosis is challenging due to unreliable data. This study introduces advanced cardiovascular models to provide clear haemodynamic status insights for better critical care.
Area of Science:
- Cardiovascular physiology
- Medical modeling
- Critical care medicine
Background:
- Cardiovascular disease is a leading cause of death in Western countries.
- Diagnosing cardiovascular dysfunction is difficult due to unreliable clinical signs and physiological measurements.
- Patient data is often incomplete or confusing, leading to diagnostic uncertainty and suboptimal treatment.
Purpose of the Study:
- To introduce the concept of using comprehensive circulatory and cardiovascular models.
- To aggregate diverse physiological signals into a clear picture of haemodynamic status.
- To improve the diagnosis and treatment of circulatory dysfunction in critical care.
Main Methods:
- Review of existing literature on circulatory and cardiovascular models.
- Presentation of an advanced, validated cardiovascular model.
- Inclusion of initial animal validation study results.
Main Results:
- The developed model aggregates diverse signals into a clear physiological picture.
- Animal validation studies show promising initial results.
- The approach has significant potential to replace intuition with measured insight.
Conclusions:
- Full circulatory and cardiovascular models offer a promising approach to enhance diagnosis and treatment.
- These models can provide clear, measured insight into haemodynamic status.
- Future integration of models and sensors in critical care can lead to improved patient outcomes.
Abstract:
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.
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