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Discovery Challenge – ECML/PKDD2004 September 20, 2004, Pisa, Italy Atherosclerosis Marie Tomečková EuroMISE Centre – Cardio Institute of Computer Science,

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Presentation on theme: "Discovery Challenge – ECML/PKDD2004 September 20, 2004, Pisa, Italy Atherosclerosis Marie Tomečková EuroMISE Centre – Cardio Institute of Computer Science,"— Presentation transcript:

1 Discovery Challenge – ECML/PKDD2004 September 20, 2004, Pisa, Italy Atherosclerosis Marie Tomečková EuroMISE Centre – Cardio Institute of Computer Science, Academy of Sciences of the CR, Prague, The Czech Republic Supported by the project LN00B107 of the Ministry of Education of the Czech Republic

2 Atherosclerosis a total complicated disease of the vessels in all organism a dynamic process, it begins in childhood and adolescence and continues for the whole life opinions on the origin and progress of the disease are developing interaction and influence of genetic predisposition and exterior environment the influence of so-called risk factors is still regarded On the other hand – there some so-called protective factors

3 Risk factors of atherosclerosis non-affectable: sex, age, family history affectable: factors of life style physical activity smoking reaction on stress blood pressure, metabolic factors - level of lipids and glucose, homocystein many other factors: coagulopathies, infections, inflammation, factors changing the function of endothelium, social and psychological factors combinations, clustering and interactivity: Reaven´s syndrom

4 STULONG (acronym) LONGitudinal twenty years lasting STUdy of risk factors of atherosclerosis The study was realized in the years 1975-2000 on the 2nd Dept. of Internal Medicine, 1st Faculty of Medicine of Charles University, Prague, the Czech Republic The data were transferred to the electronic form by the European Centre of Medical Informatics, Statistisc, and Epidemiology of Charles University and Academy of Sciences of the Czech Republic

5 STULONG Main aims of the study: To determine prevalence of the risk factors of atherosclerosis in middle-aged men To follow up the development of the risk factors To asses the possibilities and the influence of the complex intervention on the incidence and values of the risk factors and on the cardiovascular mortality

6 Population: urban population of middle-aged men (centre of Prague) 2370 men have been invited 1417 men have been examined, the respondence was 59% Middle-aged men – it is the population mostly threatened by the atherosclerosis and by its consequenses

7 Definition of risk factors blood pressure  160/95 mm Hg cholesterol  260 mg% (6,7 mmol/l) smoking  15 cigarettes/day obesity  15% above optimal weight positive family history prematured death on the atherosclerotic diseases (parents, siblings)

8 STULONG - analysis Statistical - descriptive statistics - logistic regression - survival analysis Data mining - different methods - resulting in different conclusions

9 Basic characteristics of men in STULONG (risk group - at least 1 RF, without the disease)) Prevalence of risk factors at the entry RFn% hypercholesterolemia29034.2 hypertension28734.0 smoking54363.3 !!! obesity19623.0 positive family history21625.3

10 Prevalence of risk factors in risk group

11 Basic characteristics of men in STULONG (risk group, age 46.1±3.6) means (±) Nr of RF1.72.0 cholesterol (mmol/l) 6.255.4 systolic blood pressure (mm Hg) 134.467.3 diastolic blood pressure (mm Hg) 85.347.5 Nr of cig/day9.425.0 Brocca index (%)106.847.4

12 Mortality depending on the number of RF (atherosclerotic cardiovascular diseases)

13 Survival analysis N1 RF2 RF3 RF4 RF 10. year 99 %98 %93 % 91 % 20. year 97 %89 %84 %80 %63 %

14 The relative risk of death caused by atheroslcerotic CVD

15 Discovery Challenges Atherosclerosis – growing number of the papers 2002 – Helsinki …….…5 papers 2003 – Cavtat …………9 papers 2004 – Pisa ………….. 11 papers

16 Four data files for analysis – data mining  Entry - attributes obtained from entry examination – 1417 men – 244 attributes of each men  Control – attributes recorded during the follow up (changing of the social and health status, values of follow risk factors, therapy …) – 10 600 investigations – each with 66 attributes  Letter – additional information collected at the end of the study by the postal questionnaire (men, who disscharged the following) - 403 men – 62 attributes of each men  Death – date and cause of death – 389 men

17 Four groups of analytic questions Related to  the entry examination  the long - term observation – follow-up  the postal questionnaire – at the end of the study  the relations concerning entry examination, control examination, and death

18 Approaches to solve the analytic questions – 1: given in the past Discovery Challenges Univariated and bivariated data analysis Assiciation rules SDS rules (Set Differs of Set) Trend analysis Time windows analysis ROC analysis Disciminate function

19 Approaches to solve the analytic questions – 2: Fuzzy approximate dependencies, fuzzy logic Functional dependencies Inductive logic programming technigue Explicit relations The selection of the strongest emerging patterns Genetic approach Approach to generate a mathematical algebraic model

20 Analytic guestions - some results Protective influence of number of the visits Protective influence of the beer drinking, but not of the wine drinking Correlation of Body Mass Index with the skin foldes – very good discrimination of the three basic groups of men (normal, risk, pathological)

21 Further use and publications of the STULONG data are possible only under the condition of the following explicit quotation: „The study (STULONG) was realized at the 2nd Department of Internal Medicine, 1st Faculty of Medicine of Charles University and University Hospital, Prague 2, Czech Republic (head Prof. M. Aschermann, MD, SDr, FECS), under the supervision of Prof. F. Boudík, MD, SDr, with the collaboration of M. Tomečková, MD, PhD, and Ass. Prof. J. Bultas, MD, PhD. The data were transferred to the electronic form by the European Centre of Medical Informatics, Statistisc, and Epidemiology of Charles University and Academy of Sciences of Czech Republic (head Prof. RNDr J. Zvárová, SDr).” At present time, the data analysis is supported by the project Nr. LN 00B 107 of the Ministry of Education of the CR.

22 Thank you for your effort in the STULONG data set analysis and for your attention Marie Tomečková EuroMISE Centre – Cardio Pod Vodárenskou věží 2 182 07 Prague, The Czech Republic tomeckova@euromise.cz http://www.euromise.cz


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