The frequency and severity of metabolic acidosis related to topiramate.

Objective We planned a cross-sectional analysis to determine the frequency and severity of metabolic acidosis in patients taking topiramate while awaiting craniotomy. Methods Eighty patients (18 - 65 years) taking topiramate to control seizures while awaiting elective craniotomy were enrolled. Any signs of metabolic acidosis or topiramate-related side effects were investigated. Blood chemistry levels and arterial blood gases, including lactate, were obtained. The severity of metabolic acidosis was defined according to base excess levels as mild or moderate. Results Blood gas analysis showed that 71% ( n = 57) of patients had metabolic acidosis. The frequency of moderate metabolic acidosis was 56% ( n = 45), while that of mild metabolic acidosis was 15% ( n = 12). A high respiratory rate was reported in only 10% of moderately acidotic patients. Conclusions In patients receiving topiramate, baseline blood gas analysis should be performed preoperatively to determine the presence and severity of metabolic acidosis.

Predictors of refractoriness in a Turkish status epilepticus data bank.

Refractory status epilepticus (RSE) is known to constitute approximately 10-50% of all cases of status epilepticus (SE) and is associated with significant morbidity and mortality. In the present study, data from a prospectively collected SE database were analyzed. Patients with RSE (defined as a SE episode requiring a second line of intravenous treatment following intravenous phenytoin) were compared with patients with nonrefractory SE (NRSE); 290 episodes of SE were identified, of which 108 (38%) were defined as RSE. Univariate analysis revealed that age, female gender, SE type, SE duration, and acute etiology were associated with refractoriness, whereas electroencephalographic patterns were not. Nonconvulsive SE, which is probably associated with delays in treatment initiation, was a predictor of RSE, although it was not retained as a predictor in multivariate analysis. In the latter analysis, female gender (odds ratio: 1.815, 95% CI: 1.053-3.126) and acute etiology (odds ratio: 0.619, 95% CI: 0.429-0.894) were shown to be the only significant independent predictors of refractoriness.

Glycine transporter-1 expression in the rat model of cortical dysplasia.

OBJECTIVE: Glycine transporter-1 (GLYT1) is an early marker of neural development and involved in the excitatory transmission in cortex. The study was designed to investigate the expression of GLYT1 in different parts of the brain by immunohistochemistry in the rat cortical dysplasia model. METHODS: On postnatal day 0, one freeze lesion was carried out on ten rats between bregma and lambda on the skull in the right hemisphere for 5 seconds. Six weeks later, rats were transcardially perfused with fixative and then their brains were removed for both hamotoxylin-eosine (H&E) staining for histopathology and immunohistochemistry staining for glial fibrillary acidic protein (GFAP) for astrocytic activity and GLYT1 in the cortical dysplastic region and other rostral brain regions involving epileptogenesis such as hippocampus, pyriform cortex, amygdala, thalamus and substantia nigra. RESULTS: GFAP immunoreactivity showed clusters of glial cells in the area of the microgyrus. Dense GLYT1 expression was localized to superficial layer of microgyric cortex and around the microgyrus. GLYT1 immunoreactivity was not detected in the other rostral regions. DISCUSSION: GLYT1 stained superficial structures might correspond to immature neuron and higher concentrations of GLYT1 around microgyrus might be correlated with increased excitatory mechanisms in these regions.

Multiway analysis of epilepsy tensors.

MOTIVATION: The success or failure of an epilepsy surgery depends greatly on the localization of epileptic focus (origin of a seizure). We address the problem of identification of a seizure origin through an analysis of ictal electroencephalogram (EEG), which is proven to be an effective standard in epileptic focus localization. SUMMARY: With a goal of developing an automated and robust way of visual analysis of large amounts of EEG data, we propose a novel approach based on multiway models to study epilepsy seizure structure. Our contributions are 3-fold. First, we construct an Epilepsy Tensor with three modes, i.e. time samples, scales and electrodes, through wavelet analysis of multi-channel ictal EEG. Second, we demonstrate that multiway analysis techniques, in particular parallel factor analysis (PARAFAC), provide promising results in modeling the complex structure of an epilepsy seizure, localizing a seizure origin and extracting artifacts. Third, we introduce an approach for removing artifacts using multilinear subspace analysis and discuss its merits and drawbacks. RESULTS: Ictal EEG analysis of 10 seizures from 7 patients are included in this study. Our results for 8 seizures match with clinical observations in terms of seizure origin and extracted artifacts. On the other hand, for 2 of the seizures, seizure localization is not achieved using an initial trial of PARAFAC modeling. In these cases, first, we apply an artifact removal method and subsequently apply the PARAFAC model on the epilepsy tensor from which potential artifacts have been removed. This method successfully identifies the seizure origin in both cases.