Martin Hardmeier

Intravenous levetiracetam: Treatment experience with the first 50 critically ill patients

Levetiracetam (LEV) is a broad-spectrum antiepileptic drug with no known interactions and a favorable profile of adverse events. These properties make it a good candidate for use in critically ill patients. An intravenous formulation of LEV was recently approved. The present study retrospectively assesses the safety and efficacy of LEV in the first 50 critically ill patients treated with intravenous LEV. Indications for use were seizure prophylaxis, acute symptomatic seizures, and all forms of status epilepticus. There were no major adverse effects, although less prominent changes may have been masked by the already severely compromised condition of these patients. Two patients (4%) had transiently lowered platelet counts (55,000 and 82,000, respectively). Efficacy, defined as cessation of seizure activity or prevention of its recurrence, was observed in 41 of 50 patients (82%). Antiepileptic treatment of critically ill patients with LEV seems to be effective and safe according to the data for this small cohort, but this observation warrants further prospective investigation in a larger number of patients.

Rate of brain atrophy in relapsing MS decreases during treatment with IFNβ-1a

Objective: To determine the time course of brain atrophy during treatment with once-weekly IM interferon β-1a (IFNβ-1a). Methods: The MRI cohort (n = 386) of the European IFNβ-1a dose comparison study in relapsing multiple sclerosis (MS) was analyzed. In addition to baseline and three annual scans, a frequent subgroup (n = 138) had two scans before treatment initiation and scans at months 4, 5, 6, 10, and 11. Brain parenchymal fraction (BPF), a normalized measure of whole-brain atrophy, and volume of Gd-enhancing lesions (T1Gd) and T2 hyperintense lesions (T2LL) were evaluated. Results: BPF decrease was −0.686% (first year), −0.377% (second year), and −0.378% (third year). Analysis of the frequent subgroup showed that 68% of the first-year BPF decrease occurred during the first 4 months of treatment. This change was paralleled by a drop in T1Gd and T2LL. In the frequent subgroup, an annualized atrophy rate was determined by a regression slope for the pretreatment period and from month 4 of treatment onward. Annualized pretreatment rate (−1.06%) was significantly higher than the under-treatment rate (−0.33%). Conclusions: In the first year of treatment with anti-inflammatory agents, atrophy measurements are possibly confounded by resolution of inflammatory edema or more remote effects of previous damage to the CNS. The atrophy rate reduction observed after treatment month 4 may reflect a beneficial but partial effect of interferon β-1a and was sustained over the 3-year study period.

Reproducibility of functional connectivity and graph measures based on the phase lag index (PLI) and weighted phase lag index (wPLI) derived from high resolution EEG.

Functional connectivity (FC) and graph measures provide powerful means to analyze complex networks. The current study determines the inter-subject-variability using the coefficient of variation (CoV) and long-term test-retest-reliability (TRT) using the intra-class correlation coefficient (ICC) in 44 healthy subjects with 35 having a follow-up at years 1 and 2. FC was estimated from 256-channel-EEG by the phase-lag-index (PLI) and weighted PLI (wPLI) during an eyes-closed resting state condition. PLI quantifies the asymmetry of the distribution of instantaneous phase differences of two time-series and signifies, whether a consistent non-zero phase lag exists. WPLI extends the PLI by additionally accounting for the magnitude of the phase difference. Signal-space global and regional PLI/wPLI and weighted first-order graph measures, i.e. normalized clustering coefficient (gamma), normalized average path length (lambda), and the small-world-index (SWI) were calculated for theta-, alpha1-, alpha2- and beta-frequency bands. Inter-subject variability of global PLI was low to moderate over frequency bands (0.12<CoV<0.28), higher for wPLI (0.25<CoV<0.55) and very low for gamma, lambda and SWI (CoV<0.048). TRT was good to excellent for global PLI/wPLI (0.68<ICC<0.80), regional PLI/wPLI (0.58<ICC<0.77), and fair to good for graph measures (0.32<ICC<0.73) except wPLI-based lambda in alpha1 (ICC = 0.12). Inter-electrode distance correlated very weakly with inter-electrode PLI (−0.06<rho<0) and weakly with inter-electrode wPLI (−0.22<rho<−0.18). Global PLI/wPLI and topographic connectivity patterns differed between frequency bands, and all individual networks showed a small-world-configuration. PLI/wPLI based network characterization derived from high-resolution EEG has apparently good reliability, which is one important requirement for longitudinal studies exploring the effects of chronic brain diseases over several years.

Cognitive dysfunction in early multiple sclerosis: altered centrality derived from resting-state functional connectivity using magneto-encephalography.

Background Cognitive dysfunction in multiple sclerosis (MS) is frequent. Insight into underlying mechanisms would help to develop therapeutic strategies. Objective To explore the relationship of cognitive performance to patterns of nodal centrality derived from magneto-encephalography (MEG). Methods 34 early relapsing-remitting MS patients (median EDSS 2.0) and 28 age- and gender-matched healthy controls (HC) had a MEG, a neuropsychological assessment and structural MRI. Resting-state functional connectivity was determined by the synchronization likelihood. Eigenvector Centrality (EC) was used to quantify for each sensor its connectivity and importance within the network. A cognition-score was calculated, and normalized grey and white matter volumes were determined. EC was compared per sensor and frequency band between groups using permutation testing, and related to cognition. Results Patients had lower grey and white matter volumes than HC, male patients lower cognitive performance than female patients. In HC, EC distribution showed highest nodal centrality over bi-parietal sensors (“hubs”). In patients, nodal centrality was even higher bi-parietally (theta-band) but markedly lower left temporally (upper alpha- and beta-band). Lower cognitive performance correlated to decreased nodal centrality over left temporal (lower alpha-band) and right temporal (beta-band) sensors, and to increased nodal centrality over right parieto-temporal sensors (beta-band). Network changes were most pronounced in male patients. Conclusions Partial functional disconnection of the temporal regions was associated with cognitive dysfunction in MS; increased centrality in parietal hubs may reflect a shift from temporal to possibly less efficient parietal processing. To better understand patterns and dynamics of these network changes, longitudinal studies are warranted, also addressing the influence of gender.

Reliability of fully automated versus visually controlled pre- and post-processing of resting-state EEG

OBJECTIVE To compare the reliability of a newly developed Matlab® toolbox for the fully automated, pre- and post-processing of resting state EEG (automated analysis, AA) with the reliability of analysis involving visually controlled pre- and post-processing (VA). METHODS 34 healthy volunteers (age: median 38.2 (20-49), 82% female) had three consecutive 256-channel resting-state EEG at one year intervals. Results of frequency analysis of AA and VA were compared with Pearson correlation coefficients, and reliability over time was assessed with intraclass correlation coefficients (ICC). RESULTS Mean correlation coefficient between AA and VA was 0.94±0.07, mean ICC for AA 0.83±0.05 and for VA 0.84±0.07. CONCLUSION AA and VA yield very similar results for spectral EEG analysis and are equally reliable. AA is less time-consuming, completely standardized, and independent of raters and their training. SIGNIFICANCE Automated processing of EEG facilitates workflow in quantitative EEG analysis.

Slowing of EEG background activity in Parkinson's and Alzheimer's disease with early cognitive dysfunction

Background: Slowing of the electroencephalogram (EEG) is frequent in Parkinson’s (PD) and Alzheimer’s disease (AD) and correlates with cognitive decline. As overlap pathology plays a role in the pathogenesis of dementia, it is likely that demented patients in PD show similar physiological alterations as in AD. Objective: To analyze distinctive quantitative EEG characteristics in early cognitive dysfunction in PD and AD. Methods: Forty patients (20 PD- and 20 AD patients with early cognitive impairment) and 20 normal controls (NC) were matched for gender, age, and education. Resting state EEG was recorded from 256 electrodes. Relative power spectra, median frequency (4–14 Hz), and neuropsychological outcome were compared between groups. Results: Relative theta power in left temporal region and median frequency separated the three groups significantly (p = 0.002 and p < 0.001). Relative theta power was increased and median frequency reduced in patients with both diseases compared to NC. Median frequency was higher in AD than in PD and classified groups significantly (p = 0.02). Conclusion: Increase of theta power in the left temporal region and a reduction of median frequency were associated with presence of AD or PD. PD patients are characterized by a pronounced slowing as compared to AD patients. Therefore, in both disorders EEG slowing might be a useful biomarker for beginning cognitive decline.

Power spectra for screening parkinsonian patients for mild cognitive impairment

Mild cognitive impairment in Parkinsons disease (PD‐MCI) is diagnosed based on the results of a standardized set of cognitive tests. We investigate whether quantitative EEG (qEEG) measures could identify differences between cognitively normal PD (PD‐CogNL) and PD‐MCI patients.

Quantitative EEG and apolipoprotein E-genotype improve classification of patients with suspected Alzheimer's disease

OBJECTIVE To establish a model for better identification of patients in very early stages of Alzheimers disease, AD (including patients with amnestic MCI) using high-resolution EEG and genetic data. METHODS A total of 26 patients in early stages of probable AD and 12 patients with amnestic MCI were included. Both groups were similar in age and education. All patients had a comprehensive neuropsychological examination and a high resolution EEG. Relative band power characteristics were calculated in source space (LORETA inverse solution for spectral data) and compared between groups. A logistic regression model was calculated including relative band-power at the most significant location, ApoE status, age, education and gender. RESULTS Differences in the delta band at 34 temporo-posterior source locations (p<.01) between AD and MCI groups were detected after correction for multiple comparisons. Classification slightly increased when ApoE status was added (p=.06 maximum likelihood test). Adjustment of analyses for the confounding factors age, gender and education did not alter results. CONCLUSIONS Quantitative EEG (qEEG) separates between patients with amnestic MCI and patients in early stages of probable AD. Adding information about Apo ε4 allele frequency slightly enhances diagnostic accuracy. SIGNIFICANCE qEEG may help identifying patients who are candidates for possible benefit from future disease modifying treatments.

Correlation of EEG Slowing with Cognitive Domains in Nondemented Patients with Parkinson's Disease

Background: Cognitive deficits in Parkinsons disease (PD) are heterogeneous and can be classified into cognitive domains. Quantitative EEG is related to and predictive of cognitive status in PD. In this cross-sectional study, the relationship of cognitive domains and EEG slowing in PD patients without dementia is investigated. Methods: A total of 48 patients with idiopathic PD were neuropsychologically tested. Cognitive domain scores were calculated combining Z-scores of test variables. Slowing of EEG was measured with median EEG frequency. Linear regression was used for correlational analyses and to control for confounding factors. Results: EEG median frequency was significantly correlated to cognitive performance in most domains (episodic long-term memory, rho = 0.54; overall cognitive score, rho = 0.47; fluency, rho = 0.39; attention, rho = 0.37; executive function, rho = 0.34), but not to visuospatial functions and working memory. Conclusion: Global EEG slowing is a marker for overall cognitive impairment in PD and correlates with impairment in the domains attention, executive function, verbal fluency, and episodic long-term memory, but not with working memory and visuospatial functions. These disparate effects warrant further investigations.

Adaptation of antiretroviral therapy in human immunodeficiency virus infection with central nervous system involvement

The authors describe a patient with known human immunodeficiency virus (HIV)-1 infection who presented with two generalized seizures and was found to have extensive white matter disease and a left/bilateral temporo-occipital focal slowing on electroencephalography (EEG). There were no magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF) indications for opportunistic infection. Plasma viremia was controlled, whereas viral replication was uncontrolled in CSF. CSF-specific genotype-guided adaptation of the antiretroviral therapy in order to optimize central nervous system (CNS) penetration resulted in clinical improvement and normalization of MRI and EEG. Our case report illustrates the importance of individualized antiretroviral therapy in HIV infected patients with neurological complications.