Jože Drinovec

Modeling the influence of risk factors and chronic diseases on the development of strokes and peripheral arterial-vascular disease

Abstract Several chronic diseases and risky lifestyles have become an important social burden in many countries around the world, a problem which should not be underestimated. The situation is even more worrying when we take into account their influence on serious health complications that can threaten patients’ lives or significantly reduce their quality of life. The presented modeling-and-simulation study enables us to estimate the number of patients with type-2 diabetes, hypercholesterolemia and hypertension, obese and smoking people and the influence of these conditions on the development of strokes and peripheral arterial-vascular diseases. In addition, an estimate of treatment costs makes it possible to evaluate the social burden and provide information about the potential savings resulting from treating intensive chronic diseases.

MODELLING OF THE RISK FACTORS AND CHRONIC DISEASESTHAT INFLUENCE THE DEVELOPMENT OF SERIOUS HEALTHCOMPLICATIONS

BACKGROUND Some chronic diseases, like diabetes type 2 and hypertension, and risk factors, such asobesity, hypercholesterolemia, and smoking, are strongly correlated with the potentialdevelopment of serious health complications that can threaten a patient’s life or significantly influence the quality of life, while at the same time representing an enormous economic burden. Such complications include, for example, stroke, coronary heart disease,peripheral arterial vascular disease, end-stage renal disease and congestive heart failure. METHODS For a quantitative evaluation of the mentioned patient groups, the age distribution andan estimation of the treatment expenses a dynamic mathematical model was developed,where special attention was devoted to its structure, as it should enable the sequentialconstruction and representation of different forms of data information. The model wasrealized in the Matlab program package with the Simulink Toolbox.

Efficacy analysis of a body-mass-reduction treatment using mathematical modelling

Obesity was categorized as a chronic disease by the World Health Organization (WHO) in 1997 because the problem had reached at pandemic level and presented a serious risk factor with respect to people who have been developing type-2 diabetes, hyperdyslipidaemia and hypertension. These four risk factors tend to accelerate the development of cardiovascular diseases. As a result, obesity has also become a significant social and economic burden. An important observation with regard to the population exhibiting increased body mass is the fact that they would like to decrease their weight, although they are frequently not successful. In this paper, a modelling-and-simulation approach is used for the presentation, analysis and explanation of the reasons that have an important influence on the treatment’s efficacy. The presented modelling results are based on the observation and treatment experiences of patients in a specialized institution over a period of 15 years, where each year around 100 new patients enter the treatment programme. The introduction of the motivation principle in the model structure allows strong support for the actions of the therapeutic team in a closed-loop manner, as the checking of different scenarios for the individual patient is easily realized. The efficacy of the treatment can, in this way, be significantly improved. In the past 6 years, which mainly involved open-loop treatments, the dropout rate was 70%. After the introduction of proposed closed-loop approach, this was reduced to 27% in the past year. As a consequence, the effect on body-mass control was significantly improved.

USAGE OF MODELLING AND SIMULATION IN MEDICINE AND PHARMACY

BACKGROUND Modelling and simulation have become established methodology in explanation, analysisand prediction of systems operation and can therefore be met practically in all scientificdisciplines including medicine and pharmacy. In spite of the fact that even in these twoareas the nature of problems can differ drastically, developed methodology enables theusage of similar and systematically organised design techniques, where the cooperationwith problem experts is of crucial importance. CONCLUSIONS In the paper some aspects regarding modelling and simulation in medicine and pharmacyare described. First in the introduction the basic terminology and reasons for using modellingand simulation as problem – solving techniques are given. Further, the main methodologies,including cyclic modelling activities, approaches in model construction and modelrepresentations are presented. The section is ending with experimental part of model solving, where the main attention is devoted to the continuous simulation. Presented ideasare illustrated through several simple and comprehensible examples which can frequentlybe met in the field of medicine and pharmacy. At the end also one more complex problem isintroduced where predictive capabilities of modelling were illustrated for the study of influenceof obesity to five different diseases, where also existing cross-couplings were takeninto account. Modelling results have enabled economic evaluation of obesity treatmentand the prediction of needed hospitalization and expenses regarding the absence from thework. Modelling and simulation can also in medicine and pharmacy explain and throwlight upon complex clinical and therapeutic circumstances which can not be obtainedfrom the clinical and experimental research data