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1.
Pract Neurol ; 2024 Jun 27.
Artículo en Inglés | MEDLINE | ID: mdl-38937091

RESUMEN

Pregnancy and the postpartum period are potentially high-risk periods for women with epilepsy and their babies. All women with epilepsy should have the opportunity for preconception counselling with the aim of reducing risk, optimising outcomes for the potentially developing fetus and enabling informed decision-making. This article provides an evidence-based framework for preconception counselling discussion, including the review of diagnosis and of current antiseizure medication, the risk to the fetus in relation to antiseizure medication and maternal seizures, maternal morbidity, SUDEP risk, folic acid supplements, contraception, breastfeeding and safety advice.

2.
Epilepsia ; 62(2): 492-503, 2021 02.
Artículo en Inglés | MEDLINE | ID: mdl-33501642

RESUMEN

OBJECTIVE: The study aim was to compare interictal encephalographic (EEG) functional network topology between people with well-controlled idiopathic generalized epilepsy (WC-IGE) and drug-resistant IGE (DR-IGE). METHODS: Nineteen participants with WC-IGE, 18 with DR-IGE, and 20 controls underwent a resting state, 64-channel EEG. An artifact-free epoch was bandpass filtered into the frequency range of high and low extended alpha. Weighted functional connectivity matrices were calculated. Mean degree, degree distribution variance, characteristic path length (L), clustering coefficient, small world index (SWI), and betweenness centrality were measured. A Kruskal-Wallis H-test assessed effects across groups. Where significant differences were found, Bonferroni-corrected Mann-Whitney pairwise comparisons were calculated. RESULTS: In the low alpha band (6-9 Hz), there was a significant difference in L at the three-group level (p < .0001). This was lower in controls than both WC-IGE and DR-IGE (p < .0001 for both), with no difference in L between WC-IGE and DR-IGE. Mean degree (p = .031), degree distribution variance (p = .032), and SWI (p = .023) differed across the three groups in the high alpha band (10-12 Hz). Mean degree and degree distribution variance were lower in WC-IGE than controls (p = .029 for both), and SWI was higher in WC-IGE compared with controls (p = .038), with no differences in other pairwise comparisons. SIGNIFICANCE: IGE network topology is more regular in the low alpha frequency band, potentially reflecting a more vulnerable structure. WC-IGE network topology is different from controls in the high alpha band. This may reflect drug-induced network changes that have stabilized the WC-IGE network by rendering it less likely to synchronize. These results are of potential importance in advancing the understanding of mechanisms of epilepsy drug resistance and as a possible basis for a biomarker of DR-IGE.


Asunto(s)
Encéfalo/fisiopatología , Epilepsia Refractaria/fisiopatología , Epilepsia Generalizada/fisiopatología , Adolescente , Adulto , Anticonvulsivantes/uso terapéutico , Epilepsia Refractaria/tratamiento farmacológico , Electroencefalografía , Epilepsia Generalizada/tratamiento farmacológico , Femenino , Humanos , Masculino , Persona de Mediana Edad , Vías Nerviosas , Adulto Joven
3.
Epilepsy Behav ; 112: 107427, 2020 11.
Artículo en Inglés | MEDLINE | ID: mdl-32949965

RESUMEN

INTRODUCTION: Idiopathic generalized epilepsies (IGE) are characterized by generalized interictal epileptiform discharges (IEDs) on a normal background electroencephalography (EEG). However, the yield of IEDs can be low. Approximately 20% of patients with IGE fail to achieve seizure control with antiepileptic drug (AED) treatment. Currently, there are no reliable prognostic markers for early identification of drug-resistant epilepsy (DRE). We examined spectral power of the interictal EEG in patients with IGE and healthy controls, to identify potential diagnostic and prognostic biomarkers of IGE. METHODS: A 64-channel EEG was recorded under standard conditions in patients with well-controlled IGE (WC-IGE, n = 19), drug-resistant IGE (DR-IGE, n = 18), and age-matched controls (n = 20). After preprocessing, fast Fourier transform was performed to obtain 1D frequency spectra for each EEG channel. The 1D spectra (averaged over channels) and 2D topographic maps (averaged over canonical frequency bands) were computed for each participant. Power spectra in the 3 cohorts were compared using one-way analysis of variance (ANOVA), and power spectra images were compared using T-contrast tests. A post hoc analysis compared peak alpha power between the groups. RESULTS: Compared with controls, participants with IGE had higher interictal EEG spectral power in the delta band in the midline central region, in the theta band in the midline, in the beta band over the left hemisphere, and in the gamma band over right hemisphere and left central regions. There were no differences in spectral power between cohorts with WC-IGE and DR-IGE. Peak alpha power was lower in WC-IGE and DR-IGE than controls. CONCLUSIONS: Electroencephalography spectral power analysis could form part of a clinically useful diagnostic biomarker for IGE; however, it did not correlate with response to AED in this study.


Asunto(s)
Epilepsia Generalizada , Anticonvulsivantes/uso terapéutico , Electroencefalografía , Epilepsia Generalizada/diagnóstico , Epilepsia Generalizada/tratamiento farmacológico , Humanos , Pronóstico , Convulsiones/tratamiento farmacológico
4.
Epilepsy Behav ; 106: 107013, 2020 05.
Artículo en Inglés | MEDLINE | ID: mdl-32193094

RESUMEN

The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.


Asunto(s)
Encéfalo/diagnóstico por imagen , Encéfalo/fisiopatología , Epilepsia Generalizada/diagnóstico por imagen , Epilepsia Generalizada/fisiopatología , Red Nerviosa/diagnóstico por imagen , Red Nerviosa/fisiopatología , Mapeo Encefálico/métodos , Electroencefalografía/métodos , Femenino , Humanos , Imagen por Resonancia Magnética/métodos , Magnetoencefalografía/métodos , Masculino , Modelos Teóricos
5.
Brain Commun ; 3(3): fcab196, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34514400

RESUMEN

Despite an increasing number of drug treatment options for people with idiopathic generalized epilepsy (IGE), drug resistance remains a significant issue and the mechanisms underlying it remain poorly understood. Previous studies have largely focused on potential cellular or genetic explanations for drug resistance. However, epilepsy is understood to be a network disorder and there is a growing body of literature suggesting altered topology of large-scale resting networks in people with epilepsy compared with controls. We hypothesize that network alterations may also play a role in seizure control. The aim of this study was to compare resting state functional network structure between well-controlled IGE (WC-IGE), drug resistant IGE (DR-IGE) and healthy controls. Thirty-three participants with IGE (10 with WC-IGE and 23 with DR-IGE) and 34 controls were included. Resting state functional MRI networks were constructed using the Functional Connectivity Toolbox (CONN). Global graph theoretic network measures of average node strength (an equivalent measure to mean degree in a network that is fully connected), node strength distribution variance, characteristic path length, average clustering coefficient, small-world index and average betweenness centrality were computed. Graphs were constructed separately for positively weighted connections and for absolute values. Individual nodal values of strength and betweenness centrality were also measured and 'hub nodes' were compared between groups. Outcome measures were assessed across the three groups and between both groups with IGE and controls. The IGE group as a whole had a higher average node strength, characteristic path length and average betweenness centrality. There were no clear differences between groups according to seizure control. Outcome metrics were sensitive to whether negatively correlated connections were included in network construction. There were no clear differences in the location of 'hub nodes' between groups. The results suggest that, irrespective of seizure control, IGE interictal network topology is more regular and has a higher global connectivity compared to controls, with no alteration in hub node locations. These alterations may produce a resting state network that is more vulnerable to transitioning to the seizure state. It is possible that the lack of apparent influence of seizure control on network topology is limited by challenges in classifying drug response. It is also demonstrated that network topological features are influenced by the sign of connectivity weights and therefore future methodological work is warranted to account for anticorrelations in graph theoretic studies.

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