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. The hemodynamic effects on arterial blood pressures and stroke volume (cardiac index) are simulated in the model and adrenaline-specific parameters are identified. The dose dependent changes in these parameters are then related to adrenaline dose using data from studies published in the literature. These relationships are then used to predict the future, patient-specific response to a change in dose or over time periods from 1-12 hours. The results are compared to data from 3 published adrenaline dosing studies comprising a total of 37 data sets. Absolute percentage errors for the identified model are within 10% when re-simulated and compared to clinical data for all cases. All identified parameter trends match clinically expected changes. Absolute percentage errors for the predicted hemodynamic responses (N=15) are also within 10% when re-simulated and compared to clinical data. Clinically accurate prediction of the effect of inotropic circulatory support drugs, such as adrenaline, offers significant potential for this type of model-based application. Overall, this work represents a further clinical, proof of concept, of the underlying fundamental mathematical model, methods and approach, as well as providing a template for using the model in clinical titration of adrenaline in a decision support role in critical care. They are thus a further justification in support of upcoming human clinical trials to validate this model

Mathematical multi-scale model of the cardiovascular system including mitral valve dynamics. Application to ischemic mitral insufficiency

Valve dysfunction is a common cardiovascular pathology. Despite significant clinical research, there is little formal study of how valve dysfunction affects overall circulatory dynamics. Validated models would offer the ability to better understand these dynamics and thus optimize diagnosis, as well as surgical and other interventions. A cardiovascular and circulatory system (CVS) model has already been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiologically accurate “open on pressure, close on flow” law. However, it does not consider real-time valve opening dynamics and therefore does not fully capture valve dysfunction, particularly where the dysfunction involves partial closure. This research describes an updated version of this previous closed-loop CVS model that includes the progressive opening of the mitral valve, and is defined over the full cardiac cycle. Simulations of the cardiovascular system with healthy mitral valve are performed, and, the global hemodynamic behaviour is studied compared with previously validated results. The error between resulting pressure-volume (PV) loops of already validated CVS model and the new CVS model that includes the progressive opening of the mitral valve is assessed and remains within typical measurement error and variability. Simulations of ischemic mitral insufficiency are also performed. Pressure-Volume loops, transmitral flow evolution and mitral valve aperture area evolution follow reported measurements in shape, amplitude and trends. The resulting cardiovascular system model including mitral valve dynamics provides a foundation for clinical validation and the study of valvular dysfunction in vivo. The overall models and results could readily be generalised to other cardiac valves

A Model-based Approach to Cardiovascular Monitoring of Pulmonary Embolism

peer reviewe

Physiological modeling, tight glycemic control, and the ICU clinician: what are models and how can they affect practice?

Critically ill patients are highly variable in their response to care and treatment. This variability and the search for improved outcomes have led to a significant increase in the use of protocolized care to reduce variability in care. However, protocolized care does not address the variability of outcome due to inter- and intra-patient variability, both in physiological state, and the response to disease and treatment. This lack of patient-specificity defines the opportunity for patient-specific approaches to diagnosis, care, and patient management, which are complementary to, and fit within, protocolized approaches

The conditioning of medical gases with hot water humidifiers

During invasive mechanical ventilation due to the dryness of medical gases is necessary to provide an adequate level of conditioning. The hot water humidifiers (HWH) heat the water, thus allowing the water vapor to heat and humidify the medical gases. In the common HWH there is a contact between the medical gases and the sterile water, thus increasing the risk of patient’s colonization and infection. Recently to avoid the condensation in the inspiratory limb of the ventilator circuit, new heated ventilator circuits have been developed. In this in vitro study we evaluated the efficiency (absolute/relative humidity) of three HWH: (1) a common HWH without a heated ventilator circuit (MR 730, Fisher&Paykel, New Zeland), (2) the same HWH with a heated ventilator circuit (Mallinckrodt Dar, Italy) and (3) a new HWH (DAR HC 2000, Mallinkckrodt Dar, Italy) with a heated ventilator circuit in which the water vapor reaches the medical gases through a gorotex membrane, avoiding any direct contact between the water and gases. At a temperature of 35°C and 37°C the HWH and heated tube were evaluated. The absolute humidity (AH) and relative humidity (RH) were measured by a psychometric method. The minute ventilation, tidal volume respiratory rate and oxygen fraction were: 5.8 ± 0.1 l/min, 740 ± 258 ml, 7.5 ± 2.6 bpm and 100%, respectively. Ventilator P2 Use of a bougie during percutaneous tracheostom

Prediction of hemodynamic changes towards PEEP titrations at different volemic levels using a minimal cardiovascular model.

A cardiovascular system model and parameter identification method have previously been validated for porcine experiments of induced pulmonary embolism and positive end-expiratory pressure (PEEP) titrations, accurately tracking all the main hemodynamic trends. In this research, the model and parameter identification process are further validated by predicting the effect of intervention. An overall population-specific rule linking specific model parameters to increases in PEEP is formulated to predict the hemodynamic effects on arterial pressure, pulmonary artery pressure and stroke volume. Hemodynamic changes are predicted for an increase from 0 to 10cmH₂O with median absolute percentage errors less than 7% (systolic pressures) and 13% (stroke volume). For an increase from 10 to 20cmH₂O median absolute percentage errors are less than 11% (systolic pressures) and 17% (stroke volume). These results validate the general applicability of such a rule, which is not pig-specific, but holds over for all analyzed pigs. This rule enables physiological simulation and prediction of patient response. Overall, the prediction accuracy achieved represents a further clinical validation of these models, methods and overall approach to cardiovascular diagnosis and therapy guidance