Quality of life in people with epilepsy: The associations of anti-seizure medications and biopsychosocial variables.

People with epilepsy, on average, experience lower quality of life (QOL) than healthy controls. This study examined the associations between specific anti-seizure medications, biopsychosocial factors, and QOL in people with epilepsy. Analysis of covariance revealed that individuals taking three or more anti-seizure medications had significantly lower QOL than those taking levetiracetam. Findings also demonstrated that when examining biopsychosocial factors as predictors of QOL in hierarchical regression, anxiety, depression, and daytime sleepiness were significant predictors of QOL. Once these factors were entered into the model, number of medications was no longer significant. The final model predicted 59.6% of the variance in QOL. In clinical settings, providers should take a patient-centered approach that includes regular assessment of QOL and an emphasis on good psychological care for those coping with anxiety, depression, and sleep difficulty. These findings underscore the importance of addressing psychological health and sleep factors within the epilepsy population.

Efficacy of supplemental MCT oil on seizure reduction of adult drug-resistant epilepsy - a single-center open-label pilot study.

OBJECTIVE: We set out to determine whether adding medium chain triglyceride (MCT) oil as a dietary supplement to standard diet in adult subjects with intractable epilepsy in a U.S. neurology clinical practice was associated with a reduction in number of seizures. We secondarily aimed to determine whether subjects experienced any side effects and whether there was a presence of urinary ketones while using MCT oil as a dietary supplement. METHODS: Adult patients with intractable epilepsy were recruited at standard of care clinical visits with their epileptologist. Once enrolled, subjects were instructed to supplement their diet with MCT oil as tolerated twice daily for three months (including a 1-2 week titration period, followed by a 1-2 week tapering off window) while keeping a seizure diary to record total number of seizures, presence of urinary ketones, and any side effects. RESULTS: Our data although limited by small sample size, shows that there is an estimated 42% reduction (p < 0.0001) in the rate of seizures. The MCT oil supplementation was well tolerated by most subjects except for minor GI side effects like nausea and loose stools. Most subjects developed ketones in their urine at some point during the trial. CONCLUSIONS: MCT oil supplementation reduced seizure frequency in study participants. The reported side effects included mild nausea, stomachache, loose stools. A placebo-controlled study will be more informative.

Quantitative Electroencephalography as a Biomarker for Cognitive Dysfunction in Parkinson's Disease.

Background: Quantitative electroencephalography (qEEG) has been suggested as a biomarker for cognitive decline in Parkinson's disease (PD). Objective: Determine if applying a wavelet-based qEEG algorithm to 21-electrode, resting-state EEG recordings obtained in a routine clinical setting has utility for predicting cognitive impairment in PD. Methods: PD subjects, evaluated by disease stage and motor score, were compared to healthy controls (N = 20 each). PD subjects with normal (PDN, MoCA 26-30, N = 6) and impaired (PDD, MoCA ≤ 25, N = 14) cognition were compared. The wavelet-transform based time-frequency algorithm assessed the instantaneous predominant frequency (IPF) at 60 ms intervals throughout entire recordings. We then determined the relative time spent by the IPF in the four standard EEG frequency bands (RTF) at each scalp location. The resting occipital rhythm (ROR) was assessed using standard power spectral analysis. Results: Comparing PD subjects to healthy controls, mean values are decreased for ROR and RTF-Beta, greater for RTF-Theta and similar for RTF-Delta and RTF-Alpha. In logistic regression models, arithmetic combinations of RTF values [e.g., (RTF-Alpha) + (RTF-Beta)/(RTF-Delta + RTF-Theta)] and RTF-Alpha values at occipital or parietal locations are most able to discriminate between PD and controls. A principal component (PC) from principal component analysis (PCA) using RTF-band values in all subjects is associated with PD status (p = 0.004, ß = 0.31, AUC = 0.780). Its loadings show positive contribution from RTF-Theta at all scalp locations, and negative contributions from RTF-Beta at occipital, parietal, central, and temporal locations. Compared to cognitively normal PD subjects, cognitively impaired PD subjects have lower median RTF-Alpha and RTF-Beta values, greater RTF-Theta values and similar RTF-Delta values. A PC from PCA using RTF-band values in PD subjects is associated with cognitive status (p = 0.002, ß = 0.922, AUC = 0.89). Its loadings show positive contributions from RTF-Theta at all scalp locations, negative contributions from RTF-Beta at central locations, and negative contributions from RTF-Delta at central, frontal and temporal locations. Age, disease duration and/or sex are not significant covariates. No PC was associated with motor score or disease stage. Significance: Analyzing standard EEG recordings obtained in a community practice setting using a wavelet-based qEEG algorithm shows promise as a PD biomarker and for predicting cognitive impairment in PD.

Factors Affecting Cognition and Depression in Adult Patients with Epilepsy.

BACKGROUND AND PURPOSE: Epilepsy patients are more likely to experience depressive symptoms and cognitive impairment compared to individuals in the general population. As the reasons for this are not definitively known, we sought to determine what factors correlate most strongly with cognition and a screening test for depression in epilepsy patients. METHODS: Our study population included 379 adult patients diagnosed with epilepsy or seizure in our neurology clinic. We collected detailed demographic and clinical data during patient visits using structured clinical documentation support tools that we have built within our commercial electronic medical records system (Epic), including a depression score (Neurological Disorders Depression Inventory for Epilepsy, NDDIE) and cognition score test measures (specifically in this study, Mini-Mental State Examination [MMSE]). Medication, age, gender, body mass index, duration of epilepsy, seizure frequency, current number of anti-epileptic medications, years of education were assessed in relation to baseline score as well as change in score from initial visit to first annual follow-up. RESULTS: Of the analyzed factors, two statistically significant associations were found after correction for multiple testing. Male gender and lower anti-seizure medication count were associated with better mood, as assessed by NDDIE score, at initial visit. Specifically, male gender was associated with a 1.3 decrease in NDDIE and for each additional anti-seizure medication, there was an associated 1.2 increase in NDDIE. CONCLUSIONS: However, these factors were not associated with change in NDDIE score from initial to first annual follow-up visit. These findings, although interesting, are preliminary. Additionally, these findings were based on a homogenous (mainly Caucasian) clinic-based population and detailed information on previous medication use was lacking. Further work is needed to replicate these findings and to understand any mechanisms that may explain these associations.

Structured clinical documentation in the electronic medical record to improve quality and to support practice-based research in epilepsy.

OBJECTIVE: Using the electronic medical record (EMR) to capture structured clinical data at the point of care would be a practical way to support quality improvement and practice-based research in epilepsy. METHODS: We describe our stepwise process for building structured clinical documentation support tools in the EMR that define best practices in epilepsy, and we describe how we incorporated these toolkits into our clinical workflow. RESULTS: These tools write notes and capture hundreds of fields of data including several score tests: Generalized Anxiety Disorder-7 items, Neurological Disorders Depression Inventory for Epilepsy, Epworth Sleepiness Scale, Quality of Life in Epilepsy-10 items, Montreal Cognitive Assessment/Short Test of Mental Status, and Medical Research Council Prognostic Index. The tools summarize brain imaging, blood laboratory, and electroencephalography results, and document neuromodulation treatments. The tools provide Best Practices Advisories and other clinical decision support when appropriate. The tools prompt enrollment in a DNA biobanking study. We have thus far enrolled 231 patients for initial visits and are starting our first annual follow-up visits and provide a brief description of our cohort. SIGNIFICANCE: We are sharing these EMR tools and captured data with other epilepsy clinics as part of a Neurology Practice Based Research Network, and are using the tools to conduct pragmatic trials using subgroup-based adaptive designs.

Can diffusion-weighted imaging be used as a tool to predict seizures in patients with PLEDS?

It is unclear which patients with PLEDs will have associated seizures and therefore will need to be treated aggressively with antiepileptic medications. We present a prospective observational study of ten consecutive non-anoxic patients with PLEDs based on continuous 24-hour EEG monitoring. According to the EEG, five of the patients had seizures associated with PLEDs and five had PLEDs but no seizures. The aetiology included: neoplasm (n=1), cortical dysplasia (n=1), acute head trauma (n=1), encephalomalacia related to healed abscess (n=1), intra-parenchymal haemorrhage (n=1), and no structural lesion (n=5). All patients underwent brain MRI using diffusion-weighted imaging (DWI). We found that the five patients who had seizures with PLEDs on continuous EEG had restricted diffusion on DWI. In contrast, the five patients who had PLEDs but no seizures on continuous EEG did not show a restricted diffusion pattern on DWI. We will continue to prospectively assess DWI findings in this group of patients and encourage other centres to also review similar data. If our observation is replicated, this would indicate that restricted diffusion on brain MRI may be a useful marker to identify patients with PLEDs on their EEG who are likely to have associated seizures.

Low dose verapamil as an adjunct therapy for medically refractory epilepsy - An open label pilot study.

Previous studies using verapamil as an adjunct therapy to anti-seizure medications have used doses ranging from 120 to 240mg per day. However, despite showing promising results, there was an increased incidence of side effects. The aim of this study is to assess the efficacy and tolerability of low dose verapamil (20mg p.o. tid) as adjunct therapy to patient's anti-seizure medications irrespective of the type or etiology of the epilepsy. In an open-label pilot study we enrolled 20 adult patients with history of epilepsy who continued to have a minimum of 2 seizures a month despite being on or having tried maximum tolerated doses of 3 or more standard antiepileptic drugs under the supervision of an epileptologist. 10 of the 19 patients (53%) who continued in the study had >50% reduction in seizure frequency. 2 of the patients (10%) had <50% seizure reduction. The remaining 7 patients (37%) had no reduction in their seizures. There was no discontinuation due to adverse events. P-Glycoprotein is a prototypical drug transporter that has been strongly implicated in drug resistance in epilepsy. Verapamil at a relatively low dose was well tolerated compared to previous studies which used up to 240mg per day and seems to have contributed to a statistically significant improvement in seizure control in patients with medically refractory epilepsy, especially in patients with Lennox-Gastaut syndrome. A randomized double blind controlled study at this low dose with larger sample size may be more informative.

Seizure prediction using EEG spatiotemporal correlation structure.

A seizure prediction algorithm is proposed that combines novel multivariate EEG features with patient-specific machine learning. The algorithm computes the eigenspectra of space-delay correlation and covariance matrices from 15-s blocks of EEG data at multiple delay scales. The principal components of these features are used to classify the patient's preictal or interictal state. This is done using a support vector machine (SVM), whose outputs are averaged using a running 15-minute window to obtain a final prediction score. The algorithm was tested on 19 of 21 patients in the Freiburg EEG data set who had three or more seizures, predicting 71 of 83 seizures, with 15 false predictions and 13.8 h in seizure warning during 448.3 h of interictal data. The proposed algorithm scales with the number of available EEG signals by discovering the variations in correlation structure among any given set of signals that correlate with seizure risk.

Dynamics of frequency flow in epileptic brain during extra-temporal partial and idiopathic generalized epilepsy.

Temporal lobe epilepsy has been known to be associated with buildup of 4-7 Hz activity preceded by attenuation near the seizure focus. Using a wavelet based algorithm, we recently showed that for the patients with temporal lobe epilepsy, frequency flow on the scalp EEG builds up to 5-12 Hz range just prior to and during the initial stages of the seizure. Here we present frequency flow analysis on EEG of patients with extra-temporal partial epilepsy and patients with idiopathic generalized epilepsy (IGE) to investigate any characteristic frequency flow patterns in these patients. We found that frequency flow in these patients also stays sustained in the 5-12 Hz range for longer periods of time just prior to and during the initial stages of the seizure compared to their respective baseline interictal recordings. The 5-12 Hz frequency flow was seen uniformly in all the channels in patients with IGE although it was seen most prominently adjacent to the seizure focus and to a lesser extent in other channels in patients with partial epilepsy.

Wavelet based algorithm for the estimation of frequency flow from electroencephalogram data during epileptic seizure.

OBJECTIVE: EEG data during temporal lobe seizures have been reported to show lateralized buildup of theta activity. However the exact dynamics of the theta activity and its clinical significance are not known. In this work we present an approach using wavelets to study the frequency flow dynamics of this buildup. METHODS: We employ continuous wavelet transform to obtain a time frequency representation of the EEG signal. Using a ridge extraction algorithm, the instantaneous frequency is estimated from the normalized scalogram. RESULT: We found that prior to the seizure onset, frequency flow builds up to 5-12 Hz range and the duration for which the frequency remains in this range gradually increases soon after the seizure onset. We also observed buildup at the adjacent regions. Such buildup characteristics are not seen during baseline conditions of the same patients. CONCLUSIONS: Simultaneous buildup of frequency at the temporal and the adjacent regions indicates that during seizure the neuronal interactions propagate over large regions of the brain. SIGNIFICANCE: Given that activity in the 5-12 Hz frequency range is seen often in the more alert state, our findings suggest that the brain might be in a transient alert state prior to the epileptic seizure.

Frequency flow dynamics of epileptic brain.

Epilepsy affects 1%-2% of the general population, almost 50% of whom are medically refractory and poses a huge burden. A device can possibly be designed for responsive brain stimulation of the epileptogenic focus for seizure control but optimal seizure detection patterns and stimulus parameters are not yet determined. To explore the possibility of identifying a signature prior to the seizure, we studied the dynamic evolution of frequency from electroencephalography (EEG) of three patients with partial epilepsy using the method of frequency flow. We found that prior to seizure, the frequency flow dynamics exhibit a buildup of 5-12 Hz activity which remains high during the initial stage of the seizure with a characteristic time constant and may be used for seizure detection and/or anticipation. We conclude that dynamics of frequency flow in the 5-12 Hz range can be a potential marker for the detection and/or the anticipation of the seizure in temporal lobe epilepsy.

Latency to first spike in the EEG of epilepsy patients.

BACKGROUND: Routine EEGs in individuals with epilepsy have interictal spikes in 56% of cases. The availability of prolonged EEG has changed the use of EEG in the assessment of epilepsy. OBJECTIVE: To determine the time to first epileptiform activity on EEG in patients with epilepsy. This data will help optimize the duration of electrographic assessment for interictal activity in epileptic individuals. METHODS: 46 consecutive patients aged 10 years or older with epilepsy were evaluated. Individuals with seizures in the prior 24h or with acute symptomatic seizures were excluded. Continuous EEG (for 1-7 days) was analyzed to find the first definite epileptiform activity and the latency assessed. RESULTS: 37% of the patients had epileptiform activity in the first 20min of the continuous recording (duration of a routine EEG). 89% had epileptiform activity within 24h. The yield drops beyond 24h. 8% of the individuals had no epileptiform activity even after 72h. CONCLUSIONS: The study suggests the need to consider a change in EEG strategy to assess interictal epileptiform activity. The greatest probability of capturing an interictal abnormality within 20min was in individuals with generalized epilepsy. In individuals with suspected epilepsy in whom electrographic interictal spike confirmation is deemed necessary, after a first nonspecific or normal routine EEG, a 24h EEG should be the next step in the electrographic assessment. This study suggests that there may not be much benefit in monitoring for durations longer than 24h, unless capturing a seizure is the intent.

New-onset acute symptomatic seizure in a neurological intensive care unit.

OBJECTIVE: New-onset acute symptomatic seizures can be the presenting feature of acute neurological diseases. The etiological spectrum of new-onset acute symptomatic seizures and outcome may be different in developing countries when compared to developed countries. AIM: To study the clinical profile of new-onset acute symptomatic seizures as the first presenting event in patients with acute neurological illness in a neurological intensive care unit (NICU) in a developing country. SETTINGS AND DESIGN: Prospective study in a NICU in a tertiary care hospital. MATERIALS AND METHODS: Consecutive patients with acute symptomatic new-onset seizure admitted to NICU in a tertiary care hospital over a period of 28 months. The etiology was determined by neuroimaging and appropriate investigations including cerebrospinal fluid examination. RESULTS: Of the 3,151 admissions, 66 (2.1%) were related to new-onset acute symptomatic seizures as the first presentation. The mean age was 49.07 + 20.20 years. Tonic-clonic, generalized tonic-clonic or partial seizure with or without secondary generalization were the seizure type. At presentation 52 (79%) patients had single seizure, 10 (15%) patients had seizure clusters and four (6%) patients presented with status epilepticus (SE). The major etiological risk factors were central nervous system (CNS) infections (32%), metabolic disorders (32%) and cerebrovascular diseases (21%). In the NICU 10 (15%) patients had early seizure recurrence and three (4.5%) developed SE. Of these 13 patients, in nine (69%) patients the pathology was infection-related and the other commonality was involvement of cortical gray matter. Factors associated with seizure recurrence or SE were focal cerebral lesions involving cortical gray matter or diffuse cerebral pathology, meningoencephalitis. In 69% of these patients the pathology was infection-related. There were only two deaths, both in patients with SE and related to the underlying etiology. CONCLUSION: The risk of seizure recurrence and SE after the first acute symptomatic seizure is likely to be high in patients with acute focal cerebral lesions and diffuse CNS infections. The commonality in both the pathologies is cortical gray matter involvement.

Nonconvulsive status epilepticus in a neurological intensive care unit: profile in a developing country.

PURPOSE: Nonconvulsive status epilepticus (NCSE) is an under-recognized cause of altered mental status. There are hardly any reported data on NCSE in developing countries. MATERIAL AND METHODS: Prospectively 210 consecutive patients with altered mental status admitted to neurological intensive care unit (NICU) of a tertiary care center in south India were studied for the frequency of NCSE. All patients were evaluated initially with 60-min emergent EEG (EmEEG) and subsequently by continuous EEG (cEEG) monitoring. RESULTS: Of the 210 with altered mental status admitted to NICU, the diagnosis of NCSE was established in 22 (10.5%) patients, in 12 (55%) patients with 60-min EmEEG and in 10 (45%) after cEEG monitoring for 12 to 48 hours. Of the 22 patients with NCSE, 32% had subtle motor phenomena, these were not an initial presenting features, but were apparent during cEEG recording. Acute medical or neurologic etiology was the risk factor in 68% of patients. Central nervous system (CNS) infections and cortical sino-venous thrombosis (CSVT), respectively, accounted for 23% and 14% of the etiologies. Intravenous midazolam terminated NCSE in 19 patients and valproate in 2. Of the 15 patients with acute symptomatic NCSE, 4 (18%) had poor prognosis (3 deaths and one persistent vegetative state). The etiological risk factors in the 9 (41%) patients with excellent outcome included epilepsy (3), remote symptomatic (2), cryptogenic (1), and metabolic and drugs (3). CONCLUSIONS: The frequency of NCSE in the current study was comparable with those in prior reports from developed countries. CNS infections accounted for about a fifth of the etiology. Outcome was excellent in patients with nonacute symptomatic NCSE. Initial 60-min EmEEG may be performed in establishing the diagnosis of NCSE, but almost half of patients with NCSE will be missed with this approach.

Cerebral activation during vagus nerve stimulation: a functional MR study.

PURPOSE: To study the short-term effects of vagus nerve stimulation (VNS) on brain activation and cerebral blood flow by using functional magnetic resonance imaging (fMRI). METHODS: Five patients (three women, two men; mean age, 35.4 years) who were treated for medically refractory epilepsy with VNS, underwent fMRI. All patients had a nonfocal brain MRI. The VNS was set at 30 Hz, 0.5-2.0 mA for intervals of activation of 30 s on and 30 s off, during which the fMRI was performed. Statistical parametric mapping (SPM) was used to determine significant areas of activation or inhibition during vagal nerve stimulation (p < 0.05). RESULTS: VNS-induced activation was detected in the thalami bilaterally (left more than right), insular cortices bilaterally, ipsilateral basal ganglia and postcentral gyri, right posterior superior temporal gyrus, and inferomedial occipital gyri (left more than right). The most robust activation was seen in the thalami (left more than right) and insular cortices. CONCLUSIONS: VNS-induced thalamic and insular cortical activation during fMRI suggests that these areas may play a role in modulating cerebral cortical activity, and the observed decrease in seizure frequency in patients who are given VNS may be a consequence of this increased activation.