Epilepsia最新文献

Objective: Systematic reviews and meta-analyses (SRMAs) are critical for synthesizing evidence and guiding clinical and public health decision-making. This study aims to evaluate the reliability, validity and reproducibility of the International League Against Epilepsy (ILAE) Commission on Epidemiology Risk of Bias Tool by comparing it against the Newcastle-Ottawa Scale (NOS) to inform whether the ILAE tool may serve as a valid alternative in epilepsy-focused evidence syntheses.

Methods: This study was planned a priori on three consecutive SRMAs. We assessed 54 observational studies included in these SRMAs focused on psychiatric comorbidities in persons with epilepsy. Eligible studies had ≥30 participants per group and validated criteria for diagnosing epilepsy and psychiatric conditions. Two independent raters scored all studies using both tools. The ILAE tool comprises six specific domains: (1) Source of Study Population; (2) Completeness (Sensitivity) of Epilepsy Case-Finding; (3) Sensitivity of Comorbidity Determination; (4) Accuracy of Epilepsy Diagnosis; (5) Accuracy of Comorbidity Diagnosis; and (6) Representativeness of Study Sample. Test-retest reproducibility used intraclass correlation coefficient (ICC). Correlation used Spearman's rho. Agreement used weighted kappa. Bland-Altman analysis reported mean difference.

Results: There was a strong positive correlation between NOS scores and ILAE ratings (Spearman's rho = 0.80, 95% confidence interval [CI] 0.68-89, p < 0.001). Cohen's weighted kappa was 0.68 (95% CI 0.37-0.92, p < 0.001). Bland-Altman mean difference was 0.09 with limits from -0.48 to 0.67, showing good agreement between tools. The ILAE tool showed excellent test-retest reproducibility (ICC 0.90, 95% CI 0.83-0.94).

Significance: The ILAE tool demonstrated strong reliability and substantial agreement with the NOS while offering epilepsy specific rigor in diagnostic accuracy, sensitivity, case finding and representativeness. The ILAE tool offers a reliable, conceptually relevant, field-specific alternative for quality assessment in epilepsy SRMAs.

Objective: Genetic testing has become a routine part of clinical epilepsy care. Family history is an indication for genetic testing, but the diagnostic yield, predictors of a genetic diagnosis, and association with familial patterns are not well understood.

Methods: This was a retrospective cohort study of genetic testing performed at pediatric and adult epilepsy genetics clinics. Eligible patients (probands) had epilepsy and one or more first-degree relatives or two or more other relatives with epilepsy. Genetic testing strategies were patient specific, reflecting real-world clinical practice. Familial patterns were classified based on affected relatives of the proband. Diagnostic variants were tested in the proband's parents when possible.

Results: We studied 484 probands and their families. A genetic diagnosis was identified in 99 of 484 (20%). Predictors of a genetic diagnosis were presence of neurodevelopmental disorder (X²(1) = 9.6, p = .002) and earlier age at seizure onset (Mann-Whitney U test, p < .001). The likelihood of a genetic diagnosis was not associated with epilepsy type, drug resistance, brain magnetic resonance imaging (MRI) findings, number of affected first-degree relatives, total number of affected relatives, or having an affected parent with epilepsy. Among those with genetic diagnoses, variant segregation matched the familial pattern of affected individuals in 79%. The other 21% of families had unexpected segregation, including de novo variants in patients with affected ancestors and inherited variants in patients with no known affected ancestors.

Significance: Familial epilepsy has a substantial rate of genetic diagnosis and is an appropriate indication for genetic testing. Pedigree-related factors did not influence the likelihood of genetic diagnosis, suggesting that all families can be considered for genetic testing, independent of inheritance patterns and number of affected relatives. Familial patterns can help interpret genetic test results, while also revealing the complexities of incomplete penetrance and independent epilepsy etiologies in families.

Objective: Executive dysfunction, affective symptoms, and unemployment are prevalent in patients with epilepsy, yet the relation between these variables remains poorly understood. The present study examined: (1) The relationship between epilepsy-related variables, affective symptoms, and executive functions (EFs); and (2) how these variables may be associated with participation in employment or education.

Methods: Retrospective study including 559 patients admitted to the Norwegian National Centre for Epilepsy. EFs was assessed using EpiTrack, and affective symptoms were evaluated with the 7-item Generalized Anxiety Disorder (GAD-7) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E).

Results: Impaired EFs were observed in half of the patients, and were associated with a higher antiseizure medication (ASM) load, even after adjusting for variables related to disease severity. Approximately 36% of the patients reported symptoms indicating major depression and 19% reported symptoms indicating generalized anxiety. Half of the sample was unemployed, and these patients showed poorer EFs than those engaged in employment or education (F(3, 530) = 12.29, p < .001, ηp² = .07), with no group differences in seizure frequency, anxiety, or depressive symptoms.

Significance: In patients at a tertiary epilepsy center, executive dysfunction is prevalent along with heightened symptoms of depression and anxiety. Executive dysfunction is associated with a higher ASM load as well as increased likelihood of unemployment. Our findings suggest that job retention may depend on more than the burden of epilepsy alone, with executive functioning playing a critical role. These findings emphasize the importance of monitoring EF during treatment adjustments and support minimizing total ASM load whenever possible to promote better functional outcomes.

Objective: Epileptic seizures are generated in cerebral networks that propagate ictal and interictal activity. The structure of cerebral networks underpinning epileptic activity can be inferred from diffusion-weighted magnetic resonance imaging (DWI). However, publicly available DWI data in individuals with epilepsy are scarce, and processing is technically challenging due to scan-specific artifacts, limiting research progress.

Methods: Here, we release raw DWI data from 216 individuals with epilepsy and 98 healthy controls. Subject identifiers align with our previous data release (IDEAS), which includes T1-weighted and FLAIR magnetic resonance imaging, surgical details, and long-term seizure outcomes after surgery. Preprocessing reduced distortions and artifacts, and fully processed data include diffusion metric maps in native and template space. We also provide parcellated structural connectomes using multiple atlases and connectivity measures.

Results: To illustrate the utility of these IDEAS II data, we replicated ENIGMA consortium findings, observing widespread reductions of fractional anisotropy, particularly ipsilateral to the area of seizure onset. We further demonstrate localized abnormality, and network connectivity using streamline tractography in a patient who subsequently underwent temporal lobe resection.

Significance: This open dataset offers a comprehensive resource to advance research on structural connectivity and surgical outcomes in epilepsy.

Seizures, when prolonged or repeated, leading to status epilepticus (SE), represent a medical emergency, requiring prompt treatment. In these conditions, the use of continuous midazolam (MDZ) infusion is often reserved for established or refractory SE and considered an anesthesiologic treatment, while evidence on its early use in non-intensive settings is still limited. To verify this approach in daily practice, we retrospectively collected data on about 42 episodes of pediatric SE or acute repetitive seizures (ARSs), treated with continuous MDZ infusion in non-intensive setting. Collected data include demographical information, previous history of epilepsy, instrumental examinations (electroencephalography [EEG] and brain magnetic resonance imaging [MRI]), comorbidities, anti-seizure medications (ASMs), information about the event, other treatments (first- and second-line), information about MDZ infusion, and need for other third-line treatment and/or intensive care unit (ICU) transfer. Infusion durations and rates varied widely, but in most cases (38/42) low dose (<.23 mg/kg/h) were employed. The treatment was effective in 84.2% of cases, achieving both clinical and EEG response. No adverse events (AEs) were reported. The need for a second-line treatment (particularly levetiracetam [LEV] and phenobarbital [PB]) was associated with a worse outcome. Another third-line treatment was needed in 9.5% of cases. Patients (21.4%) were transferred to ICU; a higher risk of ICU admission was reported in patients with precipitating factors (infection, surgery, hypertension and suboptimal anti-seizure medication [ASM] serum levels), and those receiving MDZ infusion at higher rates and/or co-treated with PB. Overall, our study suggests that low-dose continuous MDZ infusion is an effective and safe strategy for treatment of pediatric SE and ARSs in non-intensive settings.

Objective: This study evaluated the efficacy, safety, and tolerability of soticlestat as adjunctive therapy in children and young adults with Dravet syndrome (DS).

Methods: SKYLINE (NCT04940624) was a multicenter, randomized, double-blind, placebo-controlled, phase 3 trial that enrolled patients with DS aged 2-21 years with uncontrolled convulsive seizures (≥4/month despite adequate treatment). Participants received oral soticlestat 300 mg (weight adjusted) or matching placebo twice daily. The total study duration was 16 weeks, comprising 4-week dose titration and 12-week maintenance treatment periods. The primary endpoint was a comparison of monthly convulsive seizure frequency between baseline and the titration/maintenance periods. Key secondary endpoints included several modified Caregiver and Clinical Global Impression of Improvement (GI-I) scales for DS.

Results: One hundred forty-four participants were randomized (71 placebo, 73 soticlestat) with a mean (SD) age of 10.3 (5.0) years; 72 (50%) were male, and 117 (81.3%) were receiving ≥3 antiseizure medications. Median change from baseline in convulsive seizure frequency over the full treatment period was -8.64% with placebo (n = 71) and -22.16% with soticlestat (n = 73), a difference of -15.64% (p = .061); in the maintenance treatment period, these changes were -11.99% with placebo and -23.29% with soticlestat, a difference of -14.29% (p = .089). The proportion of participants with ≥50% reduction in convulsive seizures was 9.9% with placebo and 27.4% with soticlestat (nominal p = .008). Soticlestat showed clinically meaningful results in the Caregiver and Clinical GI-I, and Clinical GI-I Seizure Intensity and Duration scales over the 16-week treatment period (all nominal p-values ≤ .004). The most commonly reported treatment-emergent adverse events related to study drug were somnolence, change in seizure presentation, decreased appetite, and insomnia.

Significance: Although statistical significance was narrowly missed, soticlestat showed a numerical benefit over placebo for convulsive seizure decrease. Clinically meaningful benefits across multiple secondary endpoints were observed. No new safety concerns emerged.

Objective: There is a growing synergy between the lines of research on cycles in epilepsy and seizure forecasting. It has been conjectured, for instance, that incorporating information about significant seizure cycles into forecasting algorithms can lead to a better-than-chance forecasting performance. However, significance and better-than-chance are each typically evaluated against only a single null hypothesis, for example, that forecasts are generated by a Poisson process. We here argue that this should be considered only a first step. Our objective is to demonstrate the importance of testing complementary null hypotheses that represent alternative chance models.

Methods: To ensure controlled conditions, we use synthetic data generated from simple mathematical models. Samples drawn from gamma distributions are used to generate sequences of random seizure times and random forecasts. We then determine the strength of cycles as a function of the cycle duration and calculate the sensitivity and fraction of time under alarm obtained for the random forecasting algorithm. In both analyses, we apply numerical, surrogate-based null-hypothesis testing methods. In the latter case, this includes a straightforward approach to correcting for multiple testing on nonindependent data.

Results: Counterintuitively, the random seizure-time sequences contain multiple prominent cycles, which are judged highly significant by the Rayleigh test. Moreover, randomly forecasting random seizure times results in a sensitivity of 79% at a fraction of time under alarm of only 42%, clearly outperforming a Poisson-like predictor. In both cases, however, the flexibility and versatility of surrogate-based null-hypothesis tests allow us to successfully reveal that all results can be explained by chance models.

Significance: Before reaching conclusions on real cycles in epilepsy, the forecastability of seizures, and genuine capacity of forecasting algorithms, it is essential to test and reject several complementary null hypotheses. Many conclusions might not withstand such rigorous tests, allowing the community to focus on those that do.