SYSTEMS DYNAMICS FOR PREVENTING CORONARY ARTERY DISEASE AND MYOCARDIAL INFARCTION

摘要

A systems dynamics computer simulation model was devised to simulate the course of patients' cardiovascular health and disease, beginning at birth and predicting time in months at which eventual coronary artery occlusion and myocardial infarction (MI) would occur. The model was developed on a cohort of 44 patients admitted with acute myocardial infarction. Eleven were Hispanic, the remainder were non-Hispanic whites. Data were available on cholesterol, systolic and diastolic blood pressure, sex, menstrual status, triglyceride levels, HDL and LDL cholesterol levels, glucose levels, age at initial myocardial infarction, total levels of creatine kinase (CK) and the myocardial band of creatine kinase (CK-MB). Twenty-one cases were used as a learning sample. Then 23 cases were predicted using the model. When the group was divided in half, into early MI's and later MI's, the computer model achieved 88% correct classification. In conventional multivariate statistical analysis, age, systolic and diastolic blood pressure predicted 9.3% of the variance of age at initial MI. A Myocardial Risk Score was developed which consisted of (1000/age at MI)*CK. The higher the score, the earlier the infarct and the greater the total CK (reflecting greater severity). Hispanics had significantly lower scores, with 23.3% of the variance predicted by race pack-years of smoking and sex. The computer model is proposed as an interactive, dynamic health education and research tool.