Psychiatric Comorbidity in Chronic Epilepsy: Identification, Consequences, and Treatment of Major Depression

Hermann, Bruce P.; Seidenberg, Michael; Bell, Brian

doi:10.1111/j.1528-1157.2000.tb01522.x

Cited by 330 publications

(180 citation statements)

References 67 publications

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“…This may be a bidirectional effect: depression may lead to low income and unemployment, and unemployment may lead to depression 46 In addition, uncontrolled seizures may be a risk factor for depression and suicide behavior. 47 Seizure control has consistently been found to be a predictor of depression 48,49 as indicated by our findings. High seizure frequency was the only aspect that was related to suicide ideation before and after epilepsy surgery.…”

Section: Discussionsupporting

confidence: 68%

Screening symptoms of depression and suicidal ideation in people with epilepsy using the Beck depression inventory

Salgado

Nogueira

Yasuda

et al. 2012

J. epilepsy clin. neurophysiol.

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Objective: To measure the severity of symptoms of depression and suicidal ideation in people with epilepsy (PWE) before and after epilepsy surgery using the Beck Depression Inventory (BDI). We aimed to determine the factors associated to depression in PWE. Methods: PWE, regardless of epilepsy type, seizure type, duration or frequency of seizures, and AEDs were investigated. The sample (n=468) was divided into two groups: preoperatory (n=346) and pos-operatory (n=122). Results: Before epilepsy surgery female gender, unemployment and high seizure frequency were associated factors for the occurrence of symptoms of depression. After epilepsy surgery, the only factor associated to high level of depression symptoms was the lack of seizure remission. Suicidal ideation was associated to seizure frequency before and after epilepsy surgery. Conclusion: Our results confirm the generally held view that depression is common in PWE and provide further insight to the association of depression with certain socio-demographic and seizure-related factors before and after epilepsy surgery.Keywords: epilepsy, seizures, depression, suicidal ideation. RESUMO Rastreamento de sintomas de depressão e ideação suicida em pessoas com epilepsia usando o inventário de depressão de BeckObjetivo: Avaliar a gravidade dos sintomas de depressão e ideação suicida em pessoas com epilepsia (PCE), antes e após o tratamento cirúrgico utilizando o Inventário de Depressão de Beck (BDI). Nosso objetivo foi determinar os fatores associados à depressão em PCE. Métodos: PCE, independentemente do tipo de epilepsia, tipo de crises, duração ou frequência das crises, e DAEs, foram investigados. Os pacientes (n=468) foram divididos em dois grupos: pré-operatório (n=346) e de pós-operatório (n=122). Resultados: Antes do tratamento cirúrgico, o sexo feminino, o desemprego e a alta frequência de crises foram fatores associados à ocorrência de sintomas de depressão. Após a cirurgia de epilepsia, o único fator associado ao alto nível de sintomas de depressão foi a falta de remissão de crises. Ideação suicida foi associada à frequência de crises antes e após a cirurgia de epilepsia. Conclusão: Nossos resultados confirmam a opinião generalizada de que a depressão é comum nas PCE e proporcionam mais evidência para a associação de depressão com alguns fatores sócio demográficos e relacionados às crises antes e após o tratamento cirúrgico das epilepsias.Unitermos: epilepsia, crises epilépticas, depressão, ideação suicida.

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Section: Discussionsupporting

confidence: 68%

Screening symptoms of depression and suicidal ideation in people with epilepsy using the Beck depression inventory

Salgado

Nogueira

Yasuda

et al. 2012

J. epilepsy clin. neurophysiol.

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“…The prevalence of lifetime-to-date major depression among patients with epilepsy ranged from 8 to 48 per cent [4]. A history of depression was seven times more frequent in patients newly diagnosed with epilepsy than among age-and sex-matched controls in a population-based case-control study [5].…”

Section: Introductionmentioning

confidence: 99%

Kindling epileptogenesis in immature rats leads to persistent depressive behavior

Mazarati¹,

Shin²,

Auvin³

et al. 2007

Epilepsy & Behavior

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Depression is a frequent comorbidity in epilepsy patients. A variety of biological factors may underlie epilepsy-associated depression. We examined whether kindling-induced chronic increase in seizure susceptibility is accompanied by behavioral symptoms of depression. Three week-old Wistar rats underwent rapid kindling -84 initially subconvulsant electrical stimulations of ventral hippocampus delivered every five minutes -followed by depression-specific behavioral tests performed two and four weeks later. Kindled animals exhibited sustained increase in the immobility time in the forced swim test and the loss of taste preference towards calorie-free saccharin, as compared to controls. Initial loss of preference towards the intake of calorie-containing sucrose was followed by the increased consumption at four weeks. At both time points, animals exhibited enhanced seizure susceptibility upon test stimulations of the hippocampus. We conclude that neuronal plastic changes associated with kindling state are accompanied by the development of depressive behavior.

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“…Organic etiology for these psychiatric symptoms seem likely, and there are several results that suggest ongoing interictal brain abnormalities in the epileptic brain (42). This apparent association between behavioural and psychiatric 8 Arch Neurosci.…”

Section: Discussionmentioning

confidence: 99%

“…In clinical context, it could be expected that this in coordination could be reflected in both psychiatric and cognitive dysfunction as observed in patients with MTLE (40,41). Medial temporal lobe epilepsy (MTLE) is commonly recognized due to psychiatric and cognitive comorbidities and clinical factors whose quality of life impact exceeds the seizures themselves (41)(42)(43).…”

Section: Discussionmentioning

confidence: 99%

Multiscaled Complexity Analysis of EEG Epileptic Seizure Using Entropy-Based Techniques

et al. 2018

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Objectives: The most common chronic disorder due to sudden change in the electrical activity of the brain is known as epilepsy. It causes millions of deaths every year and is the second major disorder after stroke. The epileptic process involves an abnormal synchronized firing of neurons usually characterized by recurrent seizures, which are highly complex, nonlinear and non-stationary in nature. Even between seizures, the epileptic brain is different from normal and pathological conditions. The classical methods fail to analyse the full dynamics in detecting epileptic seizure. The aim of this research was to quantify the dynamics of EEG signals between seizures and seizure-free intervals using entropy based complexity measures at multiple temporal scales. The complexity of epileptic seizure intervals is reduced because of degradation of structural and functional components. Thus, complexity measures are more robust to fully analyse the dynamics of these signals. Methods:The publicly available data comprise of three different groups of EEG signals: 1, Healthy subjects; 2, Epileptic subjects during seizure-free intervals (interictal EEG); and 3, Epileptic subjects during seizure (ictal EEG); each of 100 EEG channel sample at 174 Hz were taken to quantify the dynamics in these signals. To analyse the improved understanding of the epileptic process, complexity-based techniques of Multiscale Sample Entropy (MSE) and Wavelet Entropy (Wentropy) including Shannon, log energy, and threshold, and sure and norm developed in Matlab 2015a, were employed to distinguish these conditions. Mann-WhitneyWilcoxon (MWW) test was used to find significant differences among various groups at 0.05 significance level. Moreover, the area under the curve (AUC) was computed by developing multi-receiver operating curve (ROC) in Matlab 2015a to find the maximum separation to distinguish these conditions. Results: The complexity of healthy and epileptic subjects (including both in the presence of seizures and without seizure) was computed using MSE and Wentropy at multiple temporal scales. The healthy subjects exhibited higher complexity than the epileptic subjects. Likewise, the complexity of ictal (seizure subjects) was higher than the interictal (without seizures). To distinguish healthy subjects (Set O) from epileptic (Set S) subjects, the highest separation was obtained using wavelet norm 1.1 (AUC = 0.999) followed by wavelet Shannon (AUC = 0.9944), MSE (AUC = 0.9727) and wavelet threshold (AUC = 0.942). Conclusions: Optimal results using MSE were obtained at smaller scales whereas the wavelet entropies gave optimal results mostly at higher temporal scales. Moreover, the highest separation in form of AUC was obtained using the Wentropy method with norm parameter 1.1 to distinguish healthy (eye open) and epileptic seizure (ictal state) subjects followed by wavelet Shannon and MSE.

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Psychiatric Comorbidity in Chronic Epilepsy: Identification, Consequences, and Treatment of Major Depression

Cited by 330 publications

References 67 publications

Screening symptoms of depression and suicidal ideation in people with epilepsy using the Beck depression inventory

Screening symptoms of depression and suicidal ideation in people with epilepsy using the Beck depression inventory

Kindling epileptogenesis in immature rats leads to persistent depressive behavior

Multiscaled Complexity Analysis of EEG Epileptic Seizure Using Entropy-Based Techniques

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