Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events

Applied Clinical Informatics
P Yildirim

Abstract

Ciprofloxacin is one of the main drugs to treat bacterial infections. Bacterial infections can lead to high morbidity, mortality, and costs of treatment in the world. In this study, an analysis was conducted using the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database on the adverse events of ciprofloxacin. The aim of this study was to explore unknown associations among the adverse events of ciprofloxacin, patient demographics and adverse event outcomes. A search of FDA AERS reports was performed and some statistics was highlighted. The most frequent adverse events and event outcomes of ciprofloxacin were listed, age and gender specific distribution of adverse events are reported, then the apriori algorithm was applied to the dataset to obtain some association rules and objective measures were used to select interesting ones. Furthermore, the results were compared against classical data mining algorithms and discussed. The search resulted in 6 531 reports. The reports included within the dataset consist of 3 585 (55.8%) female and 2 884 (44.1%) male patients. The mean age of patients is 54.59 years. Preschool child, middle aged and aged groups have most adverse events reports in all groups. P...Continue Reading

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Citations

Jan 31, 2017·Pharmacology & Therapeutics·Daniel F CarrMunir Pirmohamed
Jul 22, 2017·Journal of Pharmaceutical Health Care and Sciences·Haruna HatahiraMitsuhiro Nakamura
Dec 24, 2018·Journal of Pharmaceutical Health Care and Sciences·Haruna HatahiraMitsuhiro Nakamura
Jul 16, 2021·JGH Open : an Open Access Journal of Gastroenterology and Hepatology·Mohamed Kadry TaherDaniel Krewski

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