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Medication Use and the Risk of Newly Diagnosed Diabetes in Patients with Epilepsy: A Data Mining Application on a Healthcare Database
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Medication Use and the Risk of Newly Diagnosed Diabetes in Patients with Epilepsy: A Data Mining Application on a Healthcare Database
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Medication Use and the Risk of Newly Diagnosed Diabetes in Patients with Epilepsy: A Data Mining Application on a Healthcare Database
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Journal Article
Medication Use and the Risk of Newly Diagnosed Diabetes in Patients with Epilepsy: A Data Mining Application on a Healthcare Database
2020
Overview
Epilepsy is a common neurological disorder that affects millions of people worldwide. Patients with epilepsy generally require long-term antiepileptic therapy and many of them receive polypharmacy. Certain medications, including older-generation antiepileptic drugs, have been known to predispose patients to developing diabetes. Although data mining techniques have become widely used in healthcare, they have seldom been applied in this clinical problem. Here, the authors used association rule mining to discover drugs or drug combinations that may be associated with newly diagnosed diabetes. Their findings indicate in addition to the most common culprits such as phenytoin and valproic acid, prescriptions containing carbamazepine, oxcarbazepine, or lamotrigine may be related to the development of newly diagnosed diabetes. These mined rules are useful as guidance to both clinical practice and future research.
