[Virtual heart studies and its applications].
This paper presents the development of virtual heart studies and its applications.
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This paper presents the development of virtual heart studies and its applications.
Clinical cardiovascular medicine uses two models for atherosclerosis: primary and secondary prevention. The essential goal of both strategies is risk factor modification, but intervention strategies and funding mechanisms to achieve these goals have traditionally differed, leading to professional and clinical segregation. The current system defies biological reality, patients and families are not well served, and important opportunities for improved care are lost. Developing a more inclusive paradigm of primary and secondary prevention remains a significant challenge. Such a paradigm could transform a longstanding trend of two solitudes where efforts in one area rarely benefit from new developments in the other. New models need to be developed that balance and integrate diagnostic, curative and preventive care, and that coordinate public health and personal health services. Working on 'bridging strategies' will help create synergies that will lead the way to further integration and will help improve the heart health of the population.
Hypertension and its related comorbidities continue to drain South Carolina of approximately $9 billion dollars a year in direct medical costs and indirectly through lost productivity. Improving control rates of blood pressure and associated cardiovascular risk factors in the primary care physician's office is a fundamental and crucial step to decrease the very high incidence of stroke and cardiorenal diseases. By monitoring prescribing patterns through the Initiatives' data feedback program, providing evidence-based management approaches through educational seminars, and by applying improved treatment protocols, physicians can have a profound impact on outcomes. The growing collaborative partnership spawned by the Hypertension Initiative now includes primary care providers, Hypertension Specialists in the local community, and the ASH Carolinas-Georgia Chapter. The growth and impact of the partnership is facilitated by a dynamic data auditing and feedback program that provides the basis for constructive change focused on optimizing cardiovascular risk factor control in patients across the State. By continuing to make progress in addressing the control of blood pressure and associated cardiovascular risk factors through a growing collaborative partnership with primary care providers statewide, South Carolina can move from worst to first in cardiovascular health. In the future, we hope to add a dynamic health promotion program to active disease management efforts. In the process, South Carolina can move from a leader in cardiovascular disease to a model of cardiovascular health.
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A physiologically based mathematical model was built to describe the pharmacodynamic effects in response to the administration of intravenous (iv) dihydropyridine drugs in healthy volunteers. This model incorporates a limited number of hemodynamic variables, namely, mean arterial blood pressure (MAP), cardiac output (CO) or heart rate (HR), stroke volume (SV), and total peripheral resistance (TPR), into a closed-loop system supposed to represent essential features of the cardiovascular regulation. We also defined an additional auxiliary control variable (U) which is thought to represent primarily the role of the baroreceptor reflex. It was assumed that the variable U was related to MAP changes through both deviation- and rate-sensitive mechanisms. Other model parameters are the baseline levels for MAP, CO (or HR), and TPR, as well as time constants to account for further temporal aspects of the regulation. Finally, TPR was assumed to be linked to the plasma concentrations of dihydropyridine drugs via a conventional pharmacokinetic/pharmacodynamic (PK/PD) model, relying upon an effect compartment and a linear, hyperbolic, or sigmoidal relationship between the reduction in TPR and the drug concentrations at the effect site. The model characteristics were explored by studying the influence of various parameters, including baseline levels and deviation- and rate-sensitive control parameters, on the hemodynamic responses to a fictive constant rate i.v. infusion of a vasodilator drug. Attempts were also made to mimic literature data with nifedipine, following i.v. administration under both constant and exponentially decreasing infusion rates. The applicability of the model was demonstrated by fitting hemodynamic data following i.v. infusion of nicardipine to healthy volunteers, under experimental conditions similar to those described above for nifedipine. The effect model for the action of nicardipine on TPR, combined with the physiological model including a feedback control loop, allowed an adequate quantitative description of time profiles for both cardiac output and mean arterial pressure. The suggested model is a useful tool for integrated data analysis of hemodynamic responses to vasodilator drugs in healthy volunteers. Computer simulations suggest that a graded variation of a few model parameters--including baseline levels of TPR and MAP and the deviation-sensitive parameter of the arterial pressure control--would also be able to account for the pattern of hemodynamic response observed in hypertensive patients, which is qualitatively different to that seen in normotensive subjects. Extrapolation of drug response from the healthy volunteer to the hypertensive patient is allowed by our model. Its usefulness for an early evaluation of drug efficacy during drug development is under current investigation.
Cardiovascular health is currently assessed through a variety of hemodynamic parameters, many of which can only be determined by invasive measurement often requiring hospitalization. A noninvasive method of evaluating several of these parameters such as systemic vascular resistance (SVR), maximum left ventricular elasticity (E(LV)), end diastolic volume (VED), and cardiac output, is presented. The method has three elements: (1) a distributed model of the human cardiovascular system (Ozawa et aL, Ann. Biomed. Eng. 29:284-297, 2001) to generate a solution library that spans the anticipated range of parameter values, (2) a method for establishing the multidimensional relationship between features computed from the arterial blood pressure and/or flow traces (e.g., mean arterial pressure, pulse amplitude, mean flow velocity) and the critical hemodynamic parameters, and (3) a parameter estimation method that yields the best fit between measured and computed data. Sensitivity analyses were used to determine the critical parameters, and the influence of fixed model parameters. Using computer-generated brachial pressure and velocity profiles (which can be measured noninvasively), the error associated with this method was found to be less than 3% for SVR, and less than 10% for E(LV) and V(ED). Simulations were also performed to test the ability of the approach to predict changes in SVR and E(LV) from an initial base line state.
Further results of the model study "Brandenburg 74" carried out on 5,129 inhabitants of a district of the city are presented and it is proved that in programmed diagnostics during the basic medical care sufficiently well carriers of results are recognized. The great numbers of consultations in the general-medical surgeries and the numerous mass examinations render a good basis for the early diagnosis of cardiovascular diseases which above all is to be based on anamnestic data. Clinical findings and the measuring of blood pressure. It is demanded to develop a preventive programme and to test it in order to yield better results concerning the health state of the inhabitants.
Doppler echocardiographic determination of pressure half-time has been proposed as a method of assessing the severity of aortic regurgitation. To evaluate this method, we assessed the relation between pressure half-time and simulated aortic regurgitant flow under various conditions in two models of the cardiovascular system. In a hydromechanical model we assessed the influence of total peripheral resistance and arterial compliance on the pressure half-time as measured by continuous wave Doppler echocardiography. In a computer model that used the half-time of the pressure gradient between the aorta and the left ventricle as an expression of pressure half-time, we assessed the influence of total peripheral resistance and arterial compliance and also the influence of left ventricular compliance on pressure half-time. In both models, although we found an inverse relation between regurgitant orifice area and pressure half-time, changing total peripheral resistance and arterial compliance (but not left ventricular compliance) within the physiologic range significantly altered the pressure half-times. We concluded that the influence of total peripheral resistance and arterial compliance limits the usefulness of Doppler echocardiographic determination of pressure half-time as a method of assessing the severity of aortic regurgitation.
When establishing a rabbit model for cardiovascular research in our laboratory we have used midazolam in combination with fentanyl/fluanisone (MFF) and nitrous oxide as anaesthesia. In this study we focused on the effect of the anaesthetic regimen on cardiovascular parameters during open-chest surgery in 12 rabbits. Rabbits were tranquillized by intramuscular injection of fentanyl/fluanisone (0.2 ml/kg of the drug that contained 10 mg/ml fentanyl and 0.2 mg/ml fluanisone). After an intraperitoneal injection of midazolam (4 mg/kg) and additional i.m. injection of fentanyl/fluanisone (0.1 ml/kg) the rabbits were tracheotomized and ventilated on a respirator delivering a gas mixture of 50% N2O, 47.5% O2, and 2.5% CO2. The femoral vein and artery were cannulated and then rabbits received a supply of MFF intravenously. The chest was opened by midline sternotomy and the left ventricle was instrumented with piezo-electric crystals for measurement of regional left ventricular function and with a pressure catheter to measure left ventricular pressure. Radiolabelled microspheres were used to assess cardiac output and left ventricular tissue blood flow. Blood gas analysis showed no difference in the values of pH, pCO2 and pO2 between the open-chest and the closed-chest states. Mean aortic pressure was 74 +/- 4 mmHg in the closed-chest state and 65 +/- 4 mmHg in the open-chest state. Tissue blood flow showed that the left ventricle was well perfused, and mean tissue blood flow values varied between 1.80 and 2.36 ml/min.g. We conclude that the anaesthetic regimen used is easy to control. It is well tolerated in rabbits and is suitable for studies on myocardial contraction in rabbits.
The aim of this study was to assess the impact of cardiovascular risk factors on the modelling of atherosclerotic coronary arteries. One hundred consecutive patients who underwent coronary angioplasty were studied by endocoronary ultrasonography at the site of dilatation. At the site of the treated stenosis of the dilated arteries there was either compensatory widening or positive modelling (PM), or focal contraction or negative modelling (NM) if the total surface area (TSA) of the artery at the site of dilatation was greater or smaller than the total surface area of the proximal or distal reference segments. PM was observed in 53 cases (53%) and NM in 47 cases (47%). Lesions with NM had smaller TSA (13.7 +/- 5.8 versus 20.8 +/- 6.4 mm2, p < 0.0001) and a smaller atheromatous plaque (11.8 +/- 5.6 versus 19.1 +/- 6.5 mm2, p < 0.0001) than lesions with PM. Cardiovascular risk factors such as hypercholesterolaemia, smoking and hypertension were not predictive of either form of arterial modelling and there was no relationship between the cardiovascular risk factors and the qualitative appearances of the plaque studied.
Assessment of cardiovascular risk is widely proposed as a basis for taking management decisions about patients presenting with hypertension or hypercholesterolemia. Our aim was to critically assess the use of risk equations derived from epidemiological studies for the purpose of identifying high-risk patients. Risk equations were retrieved from the MEDLINE database and then applied to a data set of 118 patients. This data set was an evaluation study of the clinical value of the World Health Organization 1993 hypertension guidelines for the decision to treat mild hypertensive patients. We calculated agreement: 1) between equations and 2) between equations and the decision to treat taken by the physician. Most models were not applicable to our population, mainly because the original population had a narrow age range or comprised only males. Between-model agreement was better for the lower and upper risk quintiles than for the three other risk quintiles (0.58, 0.33, 0.34, 0.45, 0.70, from the lower to the upper risk quintile). When using an arbitrary threshold for defining high-risk patients (i.e. > 2% per year), we observed a huge variation of the proportion of patients classified at high risk (from 0 to 17%). There was a poor agreement between risk models and the decision to treat taken by the physician. These results suggest that risk-based guidelines should be validated before their diffusion.
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A human performance model has been developed and described [9] which portrays the human circulatory, thermo regulatory and energy-exchange systems as an intercoupled set. In this model, steady state or static relationships are used to describe oxygen consumption and blood flow. For example, heart rate (HTRT) is calculated as a function of the oxygen and the thermo-regulatory requirements of each body compartment, using the steady state work values of cardiac output (CO, sum of all compartment blood flows) and stroke volume (SV, assumed maximal after 40% maximal oxygen consumption): HTRT=CO/SV. The steady state model has proven to be an acceptable first approximation, but the inclusion of transient characteristics are essential in describing the overall systems' adjustment to exercise stress. In the present study, the dynamic transient characteristics of heart rate, stroke volume and cardiac output were obtained from experiments utilizing step and sinusoidal forcing of work. The gain and phase relationships reveal a probable first order system with a six minute time constant, and are utilized to model the transient characteristics of these parameters. This approach leads to a more complex model but a more accurate representation of the physiology involved. The instrumentation and programming essential to these experiments are described.
A model can be defined as an abstraction of reality which accounts for those properties ofa phenomenon that are pertinent to the purpose of the model. Models are used in anesthesia to understand the various physiologic, pharmacological and physical processes that occur during anesthesia. Indeed, many different types of models that comply with our definition can be distinguished. Early models consisted of electrical models of the arterial blood dynamics and cardiovascular system. Physical models of drug uptake and distribution have been developed to explain the kinetics of volatile anesthetics in the body. The goal of this paper is to introduce the reader to some of the types of models that been used to facilitate education and research in anesthesia. These examples will elucidate the steps involved in developing a model and the various types of models that have proven useful.
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BACKGROUND: Cardiovascular disease risk can be estimated in part on the basis of the plasma lipoprotein profile. Analysis of lipoprotein subclasses improves the risk evaluation, but the traditional methods are very time-consuming. Novel, rapid, and productive methods are therefore needed. METHODS: We obtained plasma samples from 103 fasting people and determined the plasma lipoprotein subclass profiles by an established ultracentrifugation-based method. Proton nuclear magnetic resonance (NMR) spectra were obtained from replicate samples on a 600 MHz NMR spectrometer. From the ultracentrifugation-based reference data and the NMR spectra, we developed partial least-squares (PLS) regression models to predict cholesterol and triglyceride (TG) concentrations in plasma as well as in VLDL, intermediate-density lipoprotein (IDL), LDL, 3 LDL fractions, HDL, and 3 HDL subclasses. RESULTS: The correlation coefficients (r) between the plasma TG and cholesterol concentrations measured by the 2 methods were 0.98 and 0.91, respectively. For LDL- and HDL-cholesterol concentrations, r = 0.90 and 0.94, respectively. For cholesterol concentrations in the LDL-1, LDL-2, and LDL-3 fractions, r = 0.74, 0.78, and 0.69, respectively, and for HDL subclasses HDL(2b), HDL(2a), and HDL(3), cholesterol concentrations were predicted with r = 0.92, 0.94, and 0.75, respectively. TG concentrations in VLDL, IDL, LDL, and HDL were predicted with correlations of 0.98, 0.85, 0.77, and 0.74, respectively. The cholesterol and TG concentrations in the main lipoprotein fractions and in LDL fractions and HDL subclasses predicted by the PLS models were 94%-100% of the concentrations obtained by ultracentrifugation. CONCLUSION: NMR-based PLS regression models are appropriate for use in research in which analyses of the plasma lipoprotein profile, including LDL and HDL subclasses, are required in large numbers of samples.
A lumped parameter model of the human foetal circulation primarily based on blood velocity data derived from the Doppler analysis was developed in this study. It consists of two major parts, the heart and the foetal vascular circulation. The heart model accounts for both ventricular and atrial contractility. The circulation was divided into 19 compliant vascular compartments in order to describe all of the clinically monitored sites. The model parameters refer to the final gestation period and were derived either from literature on foetal sheep circulation or from anatomical dimension monitoring of the human foetus. No control mechanism is incorporated into the model. The model was validated by comparing several index values of simulated velocity curves to those of the experimental Doppler waveforms. The mean and maximum percentual errors in the estimation of the experimental results by the model are 7.7% and 20.1%, respectively. Velocity and pressure tracings of the foetal circulation were investigated, as well as regional blood flow rate distribution.
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