engleski

Discovery of Characteristics of Patients with Increased Level of Inflammation

This paper is a study on knowledge discovery for the prediction of characteristics of older patients with increased level of inflammation. The etiology of inflammation is thought to be multifactorial and associated with the development of chronic aging diseases. Chronic low grade inflammation, expressed by slightly elevated serum concentrations of the inflammatory marker C-reactive protein (CRP), has been showed to be associated with increased frailty and overall and specific cardiovascular and noncardiovascular mortality. However, it has not been discovered before which conditions, taken all at once, are associated with elevated systems level of inflammation. To answer this question, we used the group of older primary health care attenders, burdened with multiple chronic conditions and described their health status by many aspects. The dataset was composed of 61 low-cost health parameters, many of which were data from patient health records. To predict the characteristics of patients with increased level of inflammation, we used a Linear Regression model and compared the results with some classfication algorithms. In this way, we selected 11 relevant predictors of inflammation and explained their meaning according to the existing knowledge. We could realise that many of them represent the components of the highly conserved functional network in which inflammation is the intermediate mechanism, linking these components together. These components include the metabolic, the neuroendocrine and the immune system, proposed as influencing each other during the development of age-related chronic diseases. We have also identified some new components, represented by the parameters indicating inflammation-mediated locomotor system disorders and the pituitary hormone prolactin serum concentration variations. This model, resulted from the knowledge discovery procedure, can be used to provide guidelines for further research on chronic low grade inflammation and for more practical purposes, to help physicians recognizing older persons who are at increased risk for frailty and death.

Chronic low-grade inflammation ; C-reactive protein (CRP) ; Aging diseases ; Knowledge discovery ; Biomedical data mining ; Linear regression

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