Epilepsy & behavior : E&B
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Epilepsy & behavior : E&B · Jul 2019
Prediction of antiepileptic drug treatment outcomes of patients with newly diagnosed epilepsy by machine learning.
The objective of this study was to build a supervised machine learning-based classifier, which can accurately predict the outcomes of antiepileptic drug (AED) treatment of patients with newly diagnosed epilepsy. ⋯ Our XGBoost-based machine learning classifier accurately predicts the most probable AED treatment outcome of a patient after he/she finishes all the standard examinations for the epilepsy disease. The classifier's prediction result could help disease guide counseling and eventually improve treatment strategies.
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Epilepsy & behavior : E&B · Jul 2019
Comparative StudyQuality of life after switching to generic levetiracetam - A prospective comparative study.
Improved quality of life (QoL) is one of the most important objectives in the treatment of epilepsy. Recent prospective, clinical studies proved no significant differences between brand antiepileptic drugs (AEDs) and their generic equivalents in terms of seizure control, pharmacokinetics, or safety. In this study, we focused on possible changes in QoL and adverse events in connection with generic substitution of levetiracetam (LEV). ⋯ We found reduced seizure worries over time among people with epilepsy allocated to either generic switch or continued treatment with brand LEV. We hypothesize that the nurse-led structured follow-up had an impact on seizure worries and switchback rates because of reduced nocebo effects. Further studies on generic AED substitution, focusing on psychological outcome measures, are warranted to test this supposition.