Unraveling the shared genetics of common epilepsies and general cognitive ability.

PURPOSE: Cognitive impairment is prevalent among individuals with epilepsy, and increasing evidence indicates that genetic factors can underlie this relationship. However, the extent to which epilepsy subtypes differ in their genetic relationship with cognitive function, and information about the specific genetic variants involved remain largely unknown. METHODS: We investigated the genetic relationship between epilepsies and general cognitive ability (COG) using complementary statistical tools, including linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR). We analyzed genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), as well as specific subtypes. We functionally annotated the identified loci using several biological resources and validated the results in independent samples. RESULTS: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for MiXeR analysis. We quantified extensive genetic overlap between COG and epilepsy types, but with varying negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 3.62 × 10-7; 'all epilepsy': p = 2.58 × 10-3). CONCLUSION: Our study further dissects the substantial genetic basis shared between epilepsies and COG and identifies novel shared loci. An improved understanding of the genetic relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

Advancing EEG prediction with deep learning and uncertainty estimation.

Deep Learning (DL) has the potential to enhance patient outcomes in healthcare by implementing proficient systems for disease detection and diagnosis. However, the complexity and lack of interpretability impede their widespread adoption in critical high-stakes predictions in healthcare. Incorporating uncertainty estimations in DL systems can increase trustworthiness, providing valuable insights into the model's confidence and improving the explanation of predictions. Additionally, introducing explainability measures, recognized and embraced by healthcare experts, can help address this challenge. In this study, we investigate DL models' ability to predict sex directly from electroencephalography (EEG) data. While sex prediction have limited direct clinical application, its binary nature makes it a valuable benchmark for optimizing deep learning techniques in EEG data analysis. Furthermore, we explore the use of DL ensembles to improve performance over single models and as an approach to increase interpretability and performance through uncertainty estimation. Lastly, we use a data-driven approach to evaluate the relationship between frequency bands and sex prediction, offering insights into their relative importance. InceptionNetwork, a single DL model, achieved 90.7% accuracy and an AUC of 0.947, and the best-performing ensemble, combining variations of InceptionNetwork and EEGNet, achieved 91.1% accuracy in predicting sex from EEG data using five-fold cross-validation. Uncertainty estimation through deep ensembles led to increased prediction performance, and the models were able to classify sex in all frequency bands, indicating sex-specific features across all bands.

Sensitivity and specificity of the Salzburg EEG criteria for nonconvulsive status epilepticus.

OBJECTIVE: The Salzburg EEG criteria for nonconvulsive status epilepticus (NCSE) have been proposed as consensus criteria for NCSE. We aimed to perform an independent study of their diagnostic accuracy. METHODS: A prospective study was carried out at Oslo University Hospital, including all consecutive patients ≥15 years old who were referred for an EEG with an explicit or implicit question of NCSE from February 2020 to February 2022. Two independent EEG readers scored the included EEGs according to the Salzburg criteria and blinded to the clinical data. The reference standard was defined as the clinical diagnosis the patient received based on all available clinical and paraclinical data. Diagnostic accuracy in identifying "certain/possible NCSE" was assessed by calculating sensitivity, specificity, positive predictive value, and negative predictive value with their 95% confidence intervals. RESULTS: In total, 469 patients/EEGs were included in the study. The prevalence of NCSE according to the reference standard was 11% (n = 53). The criteria showed a sensitivity of 94% (95% CI: 92-96%), a specificity of 77% (95% CI: 73-81%), a positive predictive value of 34% (95% CI: 30-39%), and a negative predictive value of 99% (95% CI: 98-100%). False positives for "certain NCSE" (n = 16) included many serial seizures and stimulus-induced rhythmic and periodic discharges (SIRPIDs), as well as a focal cortical dysplasia. False positives for "possible NCSE" (n = 79) were mainly represented by different encephalopathies and postictality. INTERPRETATION: The low specificity of the Salzburg criteria calls for refinement before implementation into daily clinical practice.

Risk of epilepsy after traumatic brain injury: a nationwide Norwegian matched cohort study.

Background: Post-traumatic epilepsy (PTE) is a well-known complication of traumatic brain injury (TBI). Although several risk factors have been identified, prediction of PTE is difficult. Changing demographics and advances in TBI treatment may affect the risk of PTE. Our aim was to provide an up-to-date estimate of the incidence of PTE by linking multiple nationwide registers. Methods: Patients with TBI admitted to hospital 2015-2018 were identified in the Norwegian Trauma Registry and matched to trauma-free controls on sex and birth year according to a matched cohort design. They were followed up for epilepsy in nationwide registers 2015-2020. Cumulative incidence of epilepsy in TBI patients and controls was estimated taking competing risks into account. Analyses stratified by the Abbreviated Injury Scale (AIS) severity score, Glasgow Coma Scale score and age were conducted for the TBI group. Occurrence of PTE in different injury types was visualized using UpSet plots. Results: In total, 8,660 patients and 84,024 controls were included in the study. Of the patients, 3,029 (35%) had moderate to severe TBI. The cumulative incidence of epilepsy in the TBI group was 3.1% (95% Confidence Interval [CI] 2.8-3.5%) after 2 years and 4.0% (3.6-4.5%) after 5 years. Corresponding cumulative incidences in the control group were 0.2% (95% CI 0.2-0.3%) and 0.5% (0.5-0.6%). The highest incidence was observed in patients with severe TBI according to AIS (11.8% [95% CI 9.7-14.4%] after 2 years and 13.2% [10.8-16.0%] after 5 years) and in patients >40 years of age. Conclusion: Patients with TBI have significantly higher risk of developing epilepsy compared to population controls. However, PTE incidence following moderate-severe TBI was notably lower than what has been reported in several previously published studies.

Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology.

Background and Objectives: Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. Methods: We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. Results: The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. Discussion: Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.

Antiseizure medication and SUDEP - a need for unifying methodology in research.

The risk of sudden unexpected death in epilepsy (SUDEP) increases with the frequency of generalized tonic-clonic seizures. Carbamazepine (CBZ) and lamotrigine (LTG) have been suggested to increase the risk. However, the prevailing viewpoint is that the choice of antiseizure medication (ASM) does not influence the occurrence. We have explored the approach to addressing this question in relevant studies to evaluate the validity of the conclusions reached. A systematic search was performed in PubMed to identify all controlled studies on SUDEP risk in individuals on CBZ or LTG. Studies were categorized according to whether idiopathic generalized epilepsy (IGE) or females were considered separately, and whether data were adjusted for seizure frequency. Eight studies on CBZ and six studies on LTG were identified. For CBZ, one study showed a significantly increased risk of SUDEP without adjustment for seizure frequency. Another study found significantly increased risk after statistical adjustment for seizure frequency and one study found increased risk with high blood levels. Five other studies found no increase in risk. For LTG, one study showed a significantly increased risk in patients with IGE as opposed to focal epilepsy, and another study showed a significantly increased risk in females. None of the subsequent studies on LTG and none of the studies on CBZ considered females with IGE separately. Taken together the available studies suggest that LTG, and possibly CBZ, may increase occurrence of SUDEP when used in females with IGE. Additional studies with sub-group analysis of females with IGE are needed.

Unraveling the shared genetics of common epilepsies and general cognitive ability.

Objective: Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods: We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples. Results: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3). Significance: Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

Treating status epilepticus in adults. / Behandling av status epilepticus hos voksne.

This clinical review examines the treatment of status epilepticus, a condition in which epileptic seizures are prolonged and pose a significant risk of brain damage and death. International guidelines recommend the use of benzodiazepines as first-line treatment, and these should be administered promptly and in appropriate doses. Second-line treatment involves the use of high-dose anti-seizure medications to stop and prevent seizures. If seizure activity persists, general anaesthesia should be administered as soon as possible. All neurological hospital departments should have established and rehearsed protocols for treating status epilepticus.

Sustained effort network for treatment of status epilepticus/European academy of neurology registry on adult refractory status epilepticus (SENSE-II/AROUSE).

BACKGROUND: Status Epilepticus (SE) is a common neurological emergency associated with a high rate of functional decline and mortality. Large randomized trials have addressed the early phases of treatment for convulsive SE. However, evidence regarding third-line anesthetic treatment and the treatment of nonconvulsive status epilepticus (NCSE) is scarce. One trial addressing management of refractory SE with deep general anesthesia was terminated early due to insufficient recruitment. Multicenter prospective registries, including the Sustained Effort Network for treatment of Status Epilepticus (SENSE), have shed some light on these questions, but many answers are still lacking, such as the influence exerted by distinct EEG patterns in NCSE on the outcome. We therefore initiated a new prospective multicenter observational registry to collect clinical and EEG data that combined may further help in clinical decision-making and defining SE. METHODS: Sustained effort network for treatment of status epilepticus/European Academy of Neurology Registry on refractory Status Epilepticus (SENSE-II/AROUSE) is a prospective, multicenter registry for patients treated for SE. The primary objectives are to document patient and SE characteristics, treatment modalities, EEG, neuroimaging data, and outcome of consecutive adults admitted for SE treatment in each of the participating centers and to identify factors associated with outcome and refractoriness. To reach sufficient statistical power for multivariate analysis, a cohort size of 3000 patients is targeted. DISCUSSION: The data collected for the registry will provide both valuable EEG data and information about specific treatment steps in different patient groups with SE. Eventually, the data will support clinical decision-making and may further guide the planning of clinical trials. Finally, it could help to redefine NCSE and its management. TRIAL REGISTRATION: NCT number: NCT05839418.

Stress biomarkers in adult patients with drug-resistant epilepsy on a modified Atkins diet: A prospective study.

OBJECTIVE: Ketogenic diets like the modified Atkins diet (MAD) are increasingly used in patients with refractory epilepsy. For epilepsy patients, stress is a well-known seizure-precipitating factor. New possibilities for measuring biomarkers of stress are now available. The purpose of this study was to investigate the impact of MAD on endocrine stress biomarkers. METHODS: Forty-nine patients with drug-resistant epilepsy were investigated at baseline and after 12 weeks on MAD. Cortisol and cortisol-binding globulin (CBG) were measured and free cortisol index (FCI) calculated. We also measured metanephrine, normetanephrine, and methoxytyramine, all markers of epinephrine, norepinephrine, and dopamine, respectively. Changes were analyzed according to sex and antiseizure medications. The different markers at baseline and after 12 weeks of MAD treatment were correlated with seizure frequency and weight loss, respectively. RESULTS: The change in total cortisol was modest after 12 weeks on the diet (from 432.9 nmol/L (403.1-462.7)) to 422.6 nmol/L (384.6-461.0), P = 0.6). FCI was reduced (from 0.39 (0.36-0.42) to 0.34 (0.31-0.36), P = 0.001). CBG increased during the study (from 1126.4 nmol/L (1074.5-1178.3) to 1272.5 nmol/L (1206.3-1338.7), P < 0.001). There were no changes in the metanephrines after 12 weeks on the diet. The decrease in FCI was significant only in women, and only observed in patients using nonenzyme-inducing ASMs. We did not find any correlation between cortisol, CBG, or FCI levels and seizure frequency. SIGNIFICANCE: After being on MAD for 12 weeks, FCI decreased significantly. The reduction in FCI may reflect reduced stress, but it may also be an effect of increased CBG. The reasons behind these alterations are unknown. Possibly, the changes may be a result of a reduction in insulin resistance and thyroid hormone levels. Treatment with MAD does not seem to influence "fight or flight" hormones.

Biological rhythms and epilepsy treatment.

Approximately one-third of patients with epilepsy are drug-refractory, necessitating novel treatment approaches. Chronopharmacology, which adjusts pharmacological treatment to physiological variations in seizure susceptibility and drug responsiveness, offers a promising strategy to enhance efficacy and tolerance. This narrative review provides an overview of the biological foundations for rhythms in seizure activity, clinical implications of seizure patterns through case reports, and the potential of chronopharmacological strategies to improve treatment. Biological rhythms, including circadian and infradian rhythms, play an important role in epilepsy. Understanding seizure patterns may help individualize treatment decisions and optimize therapeutic outcomes. Altering drug concentrations based on seizure risk periods, adjusting administration times, and exploring hormone therapy are potential strategies. Large-scale randomized controlled trials are needed to evaluate the efficacy and safety of differential and intermittent treatment approaches. By tailoring treatment to individual seizure patterns and pharmacological properties, chronopharmacology offers a personalized approach to improve outcomes in patients with epilepsy.

Reliable evaluation of functional connectivity and graph theory measures in source-level EEG: How many electrodes are enough?

OBJECTIVE: Using EEG to characterise functional brain networks through graph theory has gained significant interest in clinical and basic research. However, the minimal requirements for reliable measures remain largely unaddressed. Here, we examined functional connectivity estimates and graph theory metrics obtained from EEG with varying electrode densities. METHODS: EEG was recorded with 128 electrodes in 33 participants. The high-density EEG data were subsequently subsampled into three sparser montages (64, 32, and 19 electrodes). Four inverse solutions, four measures of functional connectivity, and five graph theory metrics were tested. RESULTS: The correlation between the results obtained with 128-electrode and the subsampled montages decreased as a function of the number of electrodes. As a result of decreased electrode density, the network metrics became skewed: mean network strength and clustering coefficient were overestimated, while characteristic path length was underestimated. CONCLUSIONS: Several graph theory metrics were altered when electrode density was reduced. Our results suggest that, for optimal balance between resource demand and result precision, a minimum of 64 electrodes should be utilised when graph theory metrics are used to characterise functional brain networks in source-reconstructed EEG data. SIGNIFICANCE: Characterisation of functional brain networks derived from low-density EEG warrants careful consideration.

Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders.

Psychiatric disorders and common epilepsies are heritable disorders with a high comorbidity and overlapping symptoms. However, the causative mechanisms underlying this relationship are poorly understood. Here we aimed to identify overlapping genetic loci between epilepsy and psychiatric disorders to gain a better understanding of their comorbidity and shared clinical features. We analysed genome-wide association study data for all epilepsies (n = 44 889), genetic generalized epilepsy (n = 33 446), focal epilepsy (n = 39 348), schizophrenia (n = 77 096), bipolar disorder (n = 406 405), depression (n = 500 199), attention deficit hyperactivity disorder (n = 53 293) and autism spectrum disorder (n = 46 350). First, we applied the MiXeR tool to estimate the total number of causal variants influencing the disorders. Next, we used the conjunctional false discovery rate statistical framework to improve power to discover shared genomic loci. Additionally, we assessed the validity of the findings in independent cohorts, and functionally characterized the identified loci. The epilepsy phenotypes were considerably less polygenic (1.0 K to 3.4 K causal variants) than the psychiatric disorders (5.6 K to 13.9 K causal variants), with focal epilepsy being the least polygenic (1.0 K variants), and depression having the highest polygenicity (13.9 K variants). We observed cross-trait genetic enrichment between genetic generalized epilepsy and all psychiatric disorders and between all epilepsies and schizophrenia and depression. Using conjunctional false discovery rate analysis, we identified 40 distinct loci jointly associated with epilepsies and psychiatric disorders at conjunctional false discovery rate <0.05, four of which were associated with all epilepsies and 39 with genetic generalized epilepsy. Most epilepsy risk loci were shared with schizophrenia (n = 31). Among the identified loci, 32 were novel for genetic generalized epilepsy, and two were novel for all epilepsies. There was a mixture of concordant and discordant allelic effects in the shared loci. The sign concordance of the identified variants was highly consistent between the discovery and independent datasets for all disorders, supporting the validity of the findings. Gene-set analysis for the shared loci between schizophrenia and genetic generalized epilepsy implicated biological processes related to cell cycle regulation, protein phosphatase activity, and membrane and vesicle function; the gene-set analyses for the other loci were underpowered. The extensive genetic overlap with mixed effect directions between psychiatric disorders and common epilepsies demonstrates a complex genetic relationship between these disorders, in line with their bi-directional relationship, and indicates that overlapping genetic risk may contribute to shared pathophysiological and clinical features between epilepsy and psychiatric disorders.

The potential role of DNA methylation as preventive treatment target of epileptogenesis.

Pharmacological therapy of epilepsy has so far been limited to symptomatic treatment aimed at neuronal targets, with the result of an unchanged high proportion of patients lacking seizure control. The dissection of the intricate pathological mechanisms that transform normal brain matter to a focus for epileptic seizures-the process of epileptogenesis-could yield targets for novel treatment strategies preventing the development or progression of epilepsy. While many pathological features of epileptogenesis have been identified, obvious shortcomings in drug development are now believed to be based on the lack of knowledge of molecular upstream mechanisms, such as DNA methylation (DNAm), and as well as a failure to recognize glial cell involvement in epileptogenesis. This article highlights the potential role of DNAm and related gene expression (GE) as a treatment target in epileptogenesis.

Early post-traumatic seizures in hospitalized patients with traumatic brain injury.

OBJECTIVES: Early post-traumatic seizures (EPTS) are a well-known complication of traumatic brain injury (TBI). EPTS increase the risk of secondary brain injury and may cause significant challenges during the period of critical care. Routine use of prophylactic anti-seizure medication is controversial due to conflicting reports on efficacy and risk of adverse effects. The purpose of this study was to expand the understanding of EPTS by examining incidence and risk factors in hospitalized patients with TBI. MATERIAL & METHODS: Adult patients with TBI and evidence of intracranial injury admitted to Oslo University Hospital between 2015 and 2019 were identified from the Oslo TBI Registry - Neurosurgery. Demographic and clinical data including occurrence of seizures were retrieved from the registry. The patients did not receive routine seizure prophylaxis. Univariate and multivariable logistic regression analyses were used to investigate risk factors associated with EPTS. RESULTS: 103 of 1827 patients (5.6%) had new-onset seizures within the first week after TBI. The following factors were in multivariable analyses associated with EPTS; alcohol abuse (odds ratio [OR] 3.6, 95% CI 2.3-5.7, p < .001), moderate and severe brain injury (OR 2.2, 95% CI 1.3-3.8, p = .004 and OR 2.1, 95% CI 1.2-3.6, p = .012), brain contusion (OR 1.6, 95% CI 1.0-2.4, p = .046) and subdural hematoma (OR 1.6, 95% CI 1.0-2.6, p = .052). CONCLUSION: In our material, EPTS occurred in 5.6% of hospital-admitted TBI-patients. Alcohol abuse was the most significant risk factor, followed by moderate and severe brain injury. The results of this study contribute to the discussion about preventive treatment of EPTS in certain risk groups.

ANT-DBS in epilepsy shows no effect on selected neuropsychiatric tests.

OBJECTIVES: Deep brain stimulation of the anterior thalamic nucleus (ANT-DBS) is an established option in treatment-resistant epilepsy and obtained FDA approval in 2018. Increased psychiatric comorbidity is well known in epilepsy. The main objective of this study was to investigate possible neuropsychiatric treatment-related changes in patients receiving ANT-DBS. MATERIALS AND METHODS: Bilateral ANT electrodes were implanted in 18 adult patients with refractory epilepsy in a randomized, double-blinded study. Immediately after implantation, patients were randomized to stimulation ON (n = 8) or OFF (n = 10) for the first 6 months (blinded phase). During the next six months (open phase), both groups received active stimulation. Neuropsychiatric assessment was conducted before implantation (T1), at the end of the blinded period (T2), and 1 year after implantation (T3). RESULTS: Comparing preoperative status (T1) and 12 months (T3), postoperative outcome in all patients did not show significant differences between the two groups for any of the applied tests. Groupwise comparisons across the two first time points (the blinded period, representing the randomized controlled trial) showed no significant differences between the two groups in any of the neuropsychiatric parameters studied. Comparing test results after 6 months of stimulation in both groups (sum of ON group T1 to T2 and OFF group T2 to T3) did not show significant changes for any of the psychiatric assessments. CONCLUSIONS: Our results indicate that ANT-DBS has limited effect concerning psychiatric issues. Subjective side effects were, however, reported in individual patients.

Cardiac Structure and Function in Epilepsy Patients with Drug-Resistant Convulsive Seizures.

High frequency of convulsive seizures and long-lasting epilepsy are associated with an increased risk of sudden unexpected death in epilepsy (SUDEP). Structural changes in the myocardium have been described in SUDEP victims. It is speculated that these changes are secondary to frequent convulsive seizures and may predispose to SUDEP. The aim of this cross-sectional study was to investigate the impact of chronic drug-resistant epilepsy on cardiac function and structure in patients with a high frequency of convulsive seizures. We consecutively included 21 patients (17 women, 4 men) aged 18-40 years, with at least 10 years with epilepsy and a minimum of six convulsive seizures in the last year and without a history of status epilepticus or nonepileptic events. A complete clinical examination, resting 12-lead electrocardiogram, 72-h Holter monitoring, and echocardiography were recorded in all patients. Ten patients were assessed by 3-Tesla cardiac magnetic resonance imaging. Echocardiography and MRI data were compared with those from age- and sex-matched healthy control individuals. No significant changes in cardiac structure or function were found among patients with chronic drug-resistant epilepsy and high frequency of convulsive seizures. However, we cannot exclude that there are subgroups of patients who are more prone to epilepsy-associated cardiac alterations.

Prediction of Long-term Survival After Status Epilepticus Using the ACD Score.

Importance: Early prediction of long-term mortality in status epilepticus is important given the high fatality rate in the years after diagnosis. Objective: To improve prognostication of long-term mortality after status epilepticus diagnosis. Design, Settings, and Participants: This retrospective, multicenter, multinational cohort study analyzed adult patients who were diagnosed with and treated for status epilepticus at university hospitals in Odense, Denmark, between January 1, 2008, and December 31, 2017, as well as in Oslo, Norway; Marburg, Germany; and Frankfurt, Germany. They were aged 18 years or older and had first-time, nonanoxic status epilepticus. A new scoring system, called the ACD score, for predicting 2-year (long-term) mortality after hospital discharge for status epilepticus was developed in the Danish cohort and validated in the German and Norwegian cohorts. The ACD score represents age at onset, level of consciousness at admission, and duration of status epilepticus. Data analysis was performed between September 1, 2019, and March 31, 2020. Exposures: Long-term follow-up using data from national and local civil registries in Denmark, Norway, and Germany. Main Outcomes and Measures: The predefined end point was 2-year survival for all patients and for a subgroup of patients with status epilepticus causes that were not damaging or were less damaging to the brain. Neurological deficits before and after onset, demographic characteristics, etiological categories of status epilepticus, comorbidities, survival, time points, treatments, and prognostic scores for different measures were assessed. Results: A total of 261 patients (mean [SD] age, 67.2 [14.8] years; 132 women [50.6%]) were included, of whom 145 patients (mean [SD] age, 66.3 [15.0] years; 78 women [53.8%]) had status epilepticus causes that were not damaging or were less damaging to the brain. The validation cohort comprised patients from Norway (n = 139) and Germany (n = 906). At hospital discharge, 29.8% of patients (n = 64 of 215) had new moderate to severe neurological deficits compared with baseline. New neurological deficits were a major predictor of 2-year survival after hospital discharge (odds ratio, 5.1; 95% CI, 2.2-11.8); this association was independent of etiological category. Nonconvulsive status epilepticus in coma and duration of status epilepticus were associated with development of new neurological deficits, and a simple 3-factor score (ACD score) combining these 2 risk factors with age at onset was developed to estimate survival after status epilepticus diagnosis. The ACD score had a linear correlation with 2-year survival (Pearson r2 = 0.848), especially in the subset of patients with a low likelihood of brain damage. Conclusions and Relevance: This study found that age, long duration, and nonconvulsive type of status epilepticus in coma were associated with the development of new neurological deficits, which were predictors of long-term mortality. Accounting for risk factors for new neurological deficits using the ACD score is a reliable method of prediction of long-term outcome in patients with status epilepticus causes that were not damaging or were less damaging to the brain.