Application of data mining for examining polypharmacy and adverse effects in cardiology patients.
This article comments upon the use of data mining tools to examine clinical data. Many cardiovascular patients have co-morbid diseases that put them at risk for polypharmacy, or severe adverse reactions from the interactions of multiple medications. Clinical trials typically use too few patients with stringent inclusion/exclusion criteria that prevent an examination of the issue of polypharmacy. However, clinical data collected in the course of patient treatment can be used in conjunction with data mining to find meaningful results.
Jewish Hospital Heart and Lung Institute, Louisville, KY 40202, USA. pcerrito@louisville.edu
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D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions; D006331:Heart Diseases / Q000150:complications*; D006801:Humans; D014481:United States; D014486:United States Food and Drug Administration