Assessment of ventricular contractility and ventricular-arterial coupling with a model-based sensor.

Estimation of ventricular contractility and ventricular arterial coupling is clinically important in diagnosing and treating cardiac dysfunction in the critically ill. However, experimental assessment of indexes of ventricular contractility, such as the end-systolic pressure-volume relationship, requires a highly invasive maneuver and measurements that are not typical in an intensive care unit (ICU). This research describes the use of a previously validated cardiovascular system model and parameter identification process to evaluate the right ventricular arterial coupling in septic shock.

Subject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: animal experiments and proof of concept.

A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models of pulmonary embolism, hypovolemia with PEEP titrations and induced endotoxic shock. However, these studies required both left and right heart catheters to collect the data required for subject-specific monitoring and diagnosis-a maximally invasive data set in a critical care setting although it does occur in practice. Hence, use of this model-based diagnostic would require significant additional invasive sensors for some subjects, which is unacceptable in some, if not all, cases.

Model-based prediction of the patient-specific response to adrenaline.

A model for the cardiovascular and circulatory systems has previously been validated in simulated cardiac and circulatory disease states. It has also been shown to accurately capture the main hemodynamic trends in porcine models of pulmonary embolism and PEEP (positive end-expiratory pressure) titrations at different volemic levels. In this research, the existing model and parameter identification process are used to study the effect of different adrenaline doses in healthy and critically ill patient populations, and to develop a means of predicting the hemodynamic response to adrenaline.

Study of ventricular interaction during pulmonary embolism using clinical identification in a minimum cardiovascular system model.

Cardiovascular disturbances are difficult to diagnose and treat because of the large range of possible underlying dysfunctions combined with regulatory reflex mechanisms that can result in conflicting clinical data. Thus, medical professionals often rely on experience and intuition to optimize hemodynamics in the critically ill. This paper combines an existing minimal cardiovascular system model with an extended integral based parameter identification method to track the evolution of induced pulmonary embolism in porcine data.

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.

Quantifying agitation in sedated ICU patients using digital imaging.

Agitation is a significant problem in the Intensive Care Unit (ICU), affecting 71% of sedated adult patients during 58% of ICU patient-days. Subjective scale based assessment-methods focused primarily on assessing excessive patient motion are currently used to assess the level of patient agitation, but are limited in their accuracy and resolution. This research quantifies this approach by developing an objective agitation measurement from patient motion that is sensed using digital video image processing.

Quantifying agitation in sedated ICU patients using heart rate and blood pressure.

Agitation is a significant problem in the intensive care unit (ICU), affecting 71% of sedated adult patients during 58% of ICU patient-days (Fraser and Riker 2001 NY Health-Syst. Pharm. 20 17-24).