Caffeinated beverages and decreased seizure control

AbstractSeizure control is often affected by seizure threshold lowering behaviours. In this case report, the authors address excessive caffeine ingestion from tea with increased seizure frequency. When decaffeinated beverages were substituted for the tea, seizure frequency returned to baseline. Similar findings occurred when the patient was re-challenged. The authors recommend avoidance of excessive caffeine in patients with epilepsy

Support Feature Machine for Classification of Abnormal Brain Activity ∗ ABSTRACT

In this study, a novel multidimensional time series classification technique, namely support feature machine (SFM), is proposed. SFM is inspired by the optimization model of support vector machine and the nearest neighbor rule to incorporate both spatial and temporal of the multi-dimensional time series data. This paper also describes an application of SFM for detecting abnormal brain activity. Epilepsy is a case in point in this study. In epilepsy studies, electroencephalograms (EEGs), acquired in multidimensional time series format, have been traditionally used as a gold-standard tool for capturing the electrical changes in the brain. From multi-dimensional EEG time series data, SFM was used to identify seizure pre-cursors and detect seizure susceptibility (pre-seizure) periods. The empirical results showed that SFM achieved over 80 % correct classification of per-seizure EEG on average in 10 patients using 5-fold cross validation. The proposed optimization model of SFM is very compact and scalable, and can be implemented as an online algorithm. The outcome of this study suggests that it is possible to construct a computerized algorithm used to detect seizure pre-cursors and warn of impending seizures through EEG classification. Categories and Subject Descriptors I.5.4 [Pattern Recognition]: Applications—signal processing, waveform analysi

Sustained Efficacy and Long-term Safety of Oxcarbazepine: One-year Open-label Extension of a Study in Refractory Partial Epilepsy

Purpose: To evaluate the long-term efficacy, tolerability, and safety of oxcarbazepine (OXC) in medically refractory partial epilepsy. Methods: This study is the open-label extension phase that followed a multicenter, randomized, double-blind, dose-response clinical study of OXC monotherapy in patients with medically refractory partial epilepsy. We analyzed the efficacy, tolerability, and safety of OXC during the first 48 weeks of open-label therapy. To evaluate efficacy, we compared the change in seizure frequency throughout the 48 weeks of treatment with OXC with the baseline seizure frequency that preceded the double-blind phase of the core study by an intent-to-treat and completer analysis. Safety and tolerability were evaluated by using an intent-to-treat analysis. Results: Of the 87 patients enrolled in the double-blind study, 76 patients participated in the open-label extension phase. Fifty-five (72%) patients completed 48 weeks of open-label treatment on a median OXC dose of 2,400 mg/day. Based on an intent-to-treat analysis, the median reduction in seizure frequency was 47% (p = 0.0054) ; the 50 and 75% responder rates were 46.1 and 25.0%, respectively, with 6.6% of patients remaining seizure free. The completer analysis yielded comparable efficacy results. OXC was well tolerated, with 13% of patients exiting because of adverse events. The six most common adverse events, irrespective of their causal relation to OXC, were dizziness, headache, fatigue, diplopia, nausea, and rash. For the most part, these adverse events tended to be transient. Conclusions: The efficacy of OXC is sustained with good safety and tolerability profiles during long-term treatment of patients with medically refractory partial epilepsy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65657/1/j.1528-1157.2003.54102.x.pd

Optimisation and data mining techniques for the screening of epileptic patients

Identifying abnormalities or anomalies by visual inspection on neurophysiologic signals such as ElectroEncephaloGrams (EEGs), is extremely challenging. We propose a novel Multi-Dimensional Time Series (MDTS) classification technique, called Connectivity Support Vector Machines (C-SVMs) that integrates brain connectivity network with SVMs. To alter noise in EEG data, Independent Component Analysis based on the Unbiased Quasi Newton Method was applied. C-SVM achieved 94.8% accuracy classifying subjects compared to 69.4% accuracy with standard SVMs. It suggests that C-SVM can be a rapid, yet accurate, technique for online differentiation between epileptic and normal subjects. It may solve other classification MDTS problems too

Efficacy and Tolerability of the New Antiepileptic Drugs, I: Treatment of New-Onset Epilepsy: Report of the TTA and QSS Subcommittees of the American Academy of Neurology and the American Epilepsy Society

Purpose: To assess the evidence demonstrating efficacy, tolerability, and safety of seven new antiepileptic drugs [AEDs; gabapentin (GBP), lamotrigine (LTG), topiramate (TPM), tiagabine (TGB), oxcarbazepine (OXC), levetiracetam (LEV), and zonisamide (ZNS), reviewed in the order in which these agents received approval by the U.S. Food and Drug Administration] in the treatment of children and adults with newly diagnosed partial and generalized epilepsies. Methods: A 23-member committee, including general neurologists, pediatric neurologists, epileptologists, and doctors in pharmacy, evaluated the available evidence based on a structured literature review including MEDLINE, Current Contents , and Cochrane Library for relevant articles from 1987 until September 2002, with selected manual searches up to 2003. Results: Evidence exists, either from comparative or dose-controlled trials, that GBP, LTG, TPM, and OXC have efficacy as monotherapy in newly diagnosed adolescents and adults with either partial or mixed seizure disorders. Evidence also shows that LTG is effective for newly diagnosed absence seizures in children. Evidence for effectiveness of the new AEDs in newly diagnosed patients with other generalized epilepsy syndromes is lacking. Conclusions: The results of this evidence-based assessment provide guidelines for the prescription of AEDs for patients with newly diagnosed epilepsy and identify those seizure types and syndromes for which more evidence is necessary.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65231/1/j.0013-9580.2004.06204.x.pd