Evaluation of seizure treatment in anti-LGI1, anti-NMDAR, and anti-GABABR encephalitis

Objective This nationwide cohort study evaluates seizure responses to immunotherapy and antiepileptic drugs (AEDs) in patients with anti-leucine-rich glioma-inactivated 1 (LGI1), anti-NMDA receptor (NMDAR), and anti-gamma-aminobutyric-acid B receptor (GABABR) encephalitis. Methods Anti-LGI1, anti-NMDAR, and anti-GABABR encephalitis patients with new-onset seizures were included. Medical information about disease course, AEDs and immunotherapies used, effects, and side effects were collected. Outcome measures were (1) seizure freedom while using AEDs or immunotherapy, (2) days to seizure freedom from start of AEDs or immunotherapy, and (3) side effects. Results Of 153 patients with autoimmune encephalitis (AIE) (53 LGI1, 75 NMDAR, 25 GABABR), 72% (n = 110) had epileptic seizures, and 89% reached seizure freedom. At least 53% achieved seizure freedom shortly after immunotherapy, and 14% achieved seizure freedom while using only AEDs (p < 0.0001). This effect was similar in all types (p = 0.0001; p = 0.0005; p = 0.013, respectively). Median time to seizure freedom from AEDs start was 59 days (interquartile range [IQR] 27–160), and 28 days from start of immunotherapy (IQR 9–71, p < 0.0001). Side effects were psychotic behavior and suicidal thoughts by the use of levetiracetam, and rash by the use of carbamazepine. Carbamazepine was more effective than levetiracetam in reducing seizures in anti-LGI1 encephalitis (p = 0.031). Only 1 patient, of 86 surviving patients, developed epilepsy after resolved encephalitis. Conclusion Epilepsy after resolved encephalitis was rare in our cohort of patients with AIE treated with immunotherapy. In addition, seizure freedom is achieved faster and more frequently after immunotherapy. Therefore, AEDs should be considered as add-on treatment, and similar to treatment of other encephalitis symptoms, immunotherapy is crucial

Antibodies Contributing to Focal Epilepsy Signs and Symptoms Score

Objective: Diagnosing autoimmune encephalitis (AIE) is difficult in patients with less fulminant diseases such as epilepsy. However, recognition is important, as patients require immunotherapy. This study aims to identify antibodies in patients with focal epilepsy of unknown etiology, and to create a score to preselect patients requiring testing. Methods: In this prospective, multicenter cohort study, adults with focal epilepsy of unknown etiology, without recognized AIE, were included, between December 2014 and December 2017, and followed for 1 year. Serum, and if available cerebrospinal fluid, were analyzed using different laboratory techniques. The ACES score was created using factors favoring an autoimmune etiology of seizures (AES), as determined by multivariate logistic regression. The model was externally validated and evaluated using the Concordance (C) statistic. Results: We included 582 patients, with median epilepsy duration of 8 years (interquartile range = 2–18)

Mortality after primary intracerebral hemorrhage in relation to post-stroke seizures

Contains fulltext : 182353.pdf (publisher's version ) (Open Access)Seizures after intracerebral hemorrhage are repeatedly seen. Whether the development of seizures after intracerebral hemorrhage affects survival in the long term is unknown. This study aims to determine the relation between seizures (i.e., with and without anti-epileptic therapy) and long-term mortality risk in a large patient population with intracerebral hemorrhage. We retrospectively included patients with a non-traumatic ICH in all three hospitals in the South Limburg region in the Netherlands between January 1st 2004 and December 31st 2009, and we assessed all-cause mortality until March 14th 2016. Patient who did not survive the first seven days after intracerebral hemorrhage were excluded from analyses. We used Cox multivariate analyses to determine independent predictors of mortality. Of 1214 patients, 783 hemorrhagic stroke patients fulfilled the inclusion criteria, amongst whom 37 (4.7%) patients developed early seizures (within 7 days after hemorrhage) and 77 (9.8%) developed late seizures (more than 7 days after hemorrhage). Seizure development was not significantly related to mortality risk after correction for conventional vascular risk factors and hemorrhage severity. However, we found a small but independent relation between the use of anti-epileptic drugs and a lower long-term mortality (HR = 0.32, 95% CI 0.11-0.91). In our large population, seizures and epilepsy did not relate independently to an increased mortality risk after hemorrhage

Treatment with Diazepam in Acute Stroke Prevents Poststroke Seizures: A Substudy of the EGASIS Trial

Objective: The frequency of seizures after stroke is high, with a severe impact on the quality of life. However, little is known about their prevention. Therefore, we investigated whether early administration of diazepam prevents the development of seizures in acute stroke patients. Methods: We performed a substudy of the EGASIS trial, a multicenter double-blind, randomized trial in which acute stroke patients were treated with diazepam or placebo for 3 days. Follow-up was after 2 weeks and 3 months. The occurrence of seizures was registered prospectively as one of the prespecified secondary outcomes. Results: 784 EGASIS patients were eligible for this substudy (389 treated with diazepam [49.6%] and 395 treated with placebo [50.4%]). Seizures were reported in 19 patients (2.4% of the total patient group). Seizures occurred less frequently in patients treated with diazepam (1.5 vs. 3.3% in the placebo group); however, this difference was only statistically significant in patients with a cortical anterior circulation infarction (0.9% in the diazepam group vs. 4.6% in the placebo group, incidence rate ratio 0.20, 95% CI: 0.05-0.78, p = 0.02, NNT = 27). Conclusion: We found that a 3-day treatment with diazepam after acute cortical anterior circulation stroke prevents the occurrence of seizures in the first 3 months following stroke. (c) 2021 The Author(s) Published by S. Karger AG, Base

The occurrence of seizures after ischemic stroke does not influence long-term mortality; a 26-year follow-up study

Objective: Epileptic seizures are a common complication after stroke. The relation between occurrence of seizures after stroke and long-term mortality remains elusive. We aimed to assess whether seizures in an early or late phase after ischemic stroke are an independent determinant of long-term mortality. Methods: We prospectively included and followed 444 ischemic stroke patients with a first-ever supratentorial brain infarct for at least 2 years after their stroke regarding the occurrence of seizures. The final follow-up for mortality is from April 2015 (follow-up duration 24.5–27.8 years, mean 26.0 years, SD 0.9 years). We compared patients with early-onset seizures with all seizure-free patients, whereas the patients with late-onset seizures were compared with the 1-week survivors without any seizures. We used Cox-regression analyses to correct for possible confounding factors. Results: Kaplan–Meier analysis showed significantly higher mortality for the patients with early-onset seizures (p = 0.002) but after correction for known risk factors for (long term) mortality early-onset seizures had no independent influence on long-term mortality (HR 1.09; 95% CI 0.64–1.85). In patients with late-onset seizures, no significant influence from late-onset seizures on long-term mortality was found (univariate p = 0.717; multivariate HR 0.81; 95% CI 0.54–1.20). Conclusion: Both early-onset and late-onset seizures do not influence long-term mortality after ischemic stroke

Acute Hospital Admissions Because of Health Care-Related Adverse Events: A Retrospective Study of 5 Specialist Departments

BACKGROUND: Health care-related adverse events (HCRAEs), which should not be confused with (blameworthy) medical errors, are common; they can lead to hospital admissions and can have grave consequences. Although they are sometimes potentially preventable, information is lacking on HCRAEs leading to admission to different departments. AIM: This study aimed to gain insight into the incidence, type, severity, and preventability of HCRAEs (including adverse drug events) leading to hospitalization to the departments of internal medicine, surgery, orthopedics, neurology, and neurosurgery. Further, we explore if there are differences regarding these HCRAEs between these departments. METHODS: We retrospectively evaluated the medical records of all patients admitted through the emergency department (ED) in a 6-month period to the departments of internal medicine, surgery, orthopedics, neurology, and neurosurgery. All patients admitted because of HCRAEs were included. RESULTS: More than one-fifth (21.8%; range 12.0%-47.8%) of all admissions to the 5 departments were due to a HCRAE. Half (49.9%) of these HCRAEs were medication-related and 30.5% were procedure-related. In 6.5% of patients, the HCRAE led to permanent disability and another 4.4% of patients died during hospitalization. HCRAEs treated by internists and neurologists were usually medication-related, whereas HCRAEs treated by surgeons, orthopedic surgeons, and neurosurgeons were usually procedure-related. CONCLUSION: Hospital admissions to different departments are often caused by HCRAEs, which sometimes lead to permanent disability or even death. Gaining insight into similarities and differences in HCRAEs occurring in different specialties is a starting point for improving clinical outcomes

Metabolic and functional MR biomarkers of antiepileptic drug effectiveness: a review

As a large number of patients with epilepsy do not respond favorably to antiepileptic drugs (AEDs), a better understanding of treatment failure and the cause of adverse side effects is required. The working mechanisms of AEDs also alter neurotransmitter concentrations and brain activity, which can be measured using MR spectroscopy and functional MR imaging, respectively. This review presents an overview of clinical research of MR spectroscopy and functional MR imaging studies to the effects of AEDs on the brain. Despite the scarcity of studies associating MR findings to the effectiveness of AEDs, the current research shows clear potential regarding this matter. Several GABAergic AEDs have been shown to increase the GABA concentration, which was related to seizure reductions, while language problems due to topiramate have been associated with altered activation patterns measured with functional MR imaging. MR spectroscopy and functional MR imaging provide biomarkers that may predict individual treatment outcomes, and enable the assessment of mechanisms of treatment failure and cognitive side effects

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest.In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group.The sensitivity, specificity, and AUC (mean +/- SD) of the regression model including metrics from both modalities were 74 +/- 19%, 82 +/- 18%, and 0.75 +/- 0.12, respectively. Positive and negative predictive values (mean SD) of the regression model with both EEG and fMRI features are 84 +/- 14% and 78 +/- 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05).Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample. (C) 2020 The Author(s). Published by Elsevier Inc

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest.In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group.The sensitivity, specificity, and AUC (mean +/- SD) of the regression model including metrics from both modalities were 74 +/- 19%, 82 +/- 18%, and 0.75 +/- 0.12, respectively. Positive and negative predictive values (mean SD) of the regression model with both EEG and fMRI features are 84 +/- 14% and 78 +/- 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05).Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample. (C) 2020 The Author(s). Published by Elsevier Inc