Epilepsia最新文献

Objective: This study was undertaken to test whether the postinjury plasma concentration of phosphorylated neurofilament heavy chain (pNF-H), a marker of axonal injury, is a prognostic biomarker for the development of posttraumatic epilepsy.

Methods: Tail vein plasma was sampled 48 h after traumatic brain injury (TBI) from 143 rats (10 naïve, 21 controls, 112 with lateral fluid percussion injury) to quantify pNF-H by enzyme-linked immunosorbent assay. During the 6th postinjury month, rats underwent 30 days of continuous video-electroencephalographic monitoring to detect unprovoked seizures and evaluate epilepsy severity. Somatomotor (composite neuroscore) and spatial memory (Morris water maze) testing and quantitative T₂ magnetic resonance imaging were performed to assess comorbidities and lesion severity.

Results: Of the 112 TBI rats, 25% (28/112) developed epilepsy (TBI+) and 75% (84/112) did not (TBI-). Plasma pNF-H concentrations were higher in TBI+ rats than in TBI- rats (p < .05). Receiver operating characteristic curve analysis indicated that plasma pNF-H concentration distinguished TBI+ rats from TBI- rats (area under the curve [AUC] = .647, p < .05). Differentiation was stronger when comparing TBI+ rats exhibiting severe epilepsy (≥3 seizures/month) with all other TBI rats (AUC = .732, p < .01). Plasma pNF-H concentration on day 2 (D2) distinguished TBI+ rats with seizure clusters from other TBI rats (AUC = .732, p < .05). Higher plasma pNF-H concentration on D2 after TBI correlated with lower neuroscores on D2 (p < .001), D6 (p < .001), and D14 (p < .01). Higher pNF-H concentration on D2 correlated with greater T₂ signal abnormality volume on D2 (p < .001) and D7 (p < .01) and larger cortical lesion area on D182 (p < .01). Plasma pNF-H concentration on D2 did not correlate with Morris water maze performance on D37-D39.

Significance: Plasma pNF-H is a promising clinically translatable prognostic biomarker for the development of posttraumatic epilepsy with frequent seizures or seizure clusters.

Objective: Patients with traumatic brain injury (TBI) often present with seizures (functional and/or epileptic), but treatments for patients with TBI and seizures are limited. We examined treatment phase and 1-year post-enrollment outcomes following neurobehavioral therapy (NBT) for patients with TBI + functional seizures (FS) and TBI + epilepsy.

Methods: In this multicenter, prospective, three-group, nonrandomized, controlled trial, with 1-year post-enrollment follow-up, three cohorts of adults were recruited: TBI + video-electroencephalography (EEG)-confirmed FS (n = 89), TBI + EEG-confirmed epilepsy (n = 29), and chart/history-confirmed TBI without seizures (n = 75). Exclusion criteria were recent psychotic or self-injurious behavior, current suicidal ideation, pending litigation or long-term disability, active substance use disorder, and inability to participate in study procedures. TBI + FS and TBI + epilepsy groups completed NBT for seizures, an evidence-based, 12-session, multimodal psychotherapy, whereas TBI without seizures participants received standard medical care. The primary outcome was change in seizure frequency; secondary outcomes were changes in mental health, TBI-related symptoms, disability, and quality of life.

Results: Reductions in average monthly seizures occurred during treatment in TBI + FS participants (p = .002) and were significant from baseline (mean = 16.75; 95% confidence interval [CI] = 11.44-24.53) to 12 months post-enrollment (mean = 7.28, 95% CI = 4.37-12.13, p = .002, d = .38). Monthly seizures decreased during treatment in TBI + epilepsy participants (p = .002); reductions were not statistically significant from baseline (mean = 2.38, 95% CI = 1.12-5.04) to 12-month postenrollment (mean = .98, 95% CI = .40-2.42, p = .07, d = .22). Regarding treatment-phase changes in secondary outcome measures, TBI + FS participants improved significantly on 10 of 19 variables (52.6%), TBI + epilepsy participants improved on five of 19 (26.3%), and TBI-only comparisons improved on only one of 19 (5.3%).

Significance: NBT benefited patients with TBI + FS and TBI + epilepsy. Improvements were demonstrated at 1 year post-enrollment in those with TBI + FS. NBT may be a clinically useful treatment for patients with seizures.

Objective: Epilepsy raises critical challenges to accurately localize the epileptogenic zone (EZ) to guide presurgical planning. Previous research has suggested that interictal spikes overlapping with high-frequency oscillations, referred to here as pSpikes, serve as a reliable biomarker for EZ estimation, but there remains a question as to whether and to how pSpikes perform as compared to other types of epileptic spikes. This study aims to address this question by investigating the source imaging capabilities of pSpikes alongside other spike types.

Methods: A total of 2819 interictal spikes from 76-channel scalp electroencephalography (EEG) were analyzed in a cohort of 24 drug-resistant focal epilepsy patients. All patients received surgical resection, and 16 were declared seizure-free based on at least 1 year of postoperative follow-up. A recently developed electrophysiological source imaging algorithm-fast spatiotemporal iteratively reweighted edge sparsity (FAST-IRES)-was used for source imaging of the detected interictal spikes. The performance of 217 pSpikes was compared with 772 nSpikes (spikes with irregular high-frequency activations), 1830 rSpikes (spikes with no high-frequency activity), and all 2819 aSpikes (all interictal spikes).

Results: The localization and extent estimation using pSpikes are concordant with the clinical ground truth; using pSpikes yields the best performance compared with nSpikes, rSpikes, and conventional spike imaging (aSpikes). For multiple spike type seizure-free patients, the mean localization error for pSpike imaging was 6.8 mm, compared with 15.0 mm for aSpikes. The sensitivity, precision, and specificity were .41, .67, and .93 for pSpikes compared with .32, .48, and .93 for aSpikes.

Significance: These results demonstrate the merits of noninvasive EEG source localization, and that (1) pSpike is a superior biomarker, outperforming conventional spike imaging for the localization of epileptic sources, and especially those with multiple irritative zones; and (2) FAST-IRES provides accurate source estimation that is highly concordant with clinical ground truth, even in situations of single spike analysis with low signal-to-noise ratio.

Objective: To estimate the minimum clinically important difference (MCID) for the parent-reported 55-item Quality of Life in Childhood Epilepsy Questionnaire (QOLCE-55) and its shortened 16-item version, QOLCE-16.

Methods: Data came from 74 children with epilepsy (CWE) (ages 4-10, mean age = 8 [SD = 1.8]) enrolled in the Making Mindfulness Matter in Epilepsy (M3-E) trial, a pilot, parallel randomized-controlled trial of a mindfulness-based intervention. Both anchor-based and distribution-based methods were used to estimate MCID values for the QOLCE-55 and QOLCE-16. For the anchor-based approach, the Patient Centered Global Ratings of Change (PCGRC) scale and linear regression analysis were used to estimate the MCID. For the distribution-based approach, .5 SD of the health-related quality of life (HRQOL) change score distribution was used to estimate the MCID.

Results: For the QOLCE-55, the MCID obtained using an anchor-based approach was 10 points and using a distribution-based method was 6 points. For the QOLCE-16, the MCID obtained using an anchor-based method was 13 points and using a distribution-based method was 7 points.

Significance: This is the first study to estimate MCID values for the QOLCE-55 and the QOLCE-16. It has been well documented that CWE are at risk of experiencing psychological, behavioral, and cognitive impairments, which can negatively impact their HRQOL. Reporting MCID values for the QOLCE-55 and QOLCE-16 is important in determining whether changes in HRQOL observed are meaningful to CWE themselves, as a key factor in shaping the nature of epilepsy care delivered.

Objective: People with epilepsy (PwE) suffer from progressive brain atrophy, which is reflected as neuroaxonal loss on the retinal level. This study aims to provide initial insight into the longitudinal dynamics of the retinal neuroaxonal loss and possible driving factors.

Methods: PwE and healthy controls (HC; 18-55 years of age) underwent spectral domain optical coherence tomography at baseline and 7.0 ± 1.5 and 6.7 ± 1.0 months later, respectively. The change in retinal thickness/volume and annualized percentage change (APC) were calculated for the peripapillary retinal nerve fiber layer (pRNFL), the macular RNFL (mRNFL), the ganglion cell inner plexiform layer (GCIP), the inner nuclear layer, and the total macular volume (TMV). Group comparisons and multiple linear models with stepwise backward selection were performed to evaluate associations with demographic and clinical parameters.

Results: PwE (n = 44, 21 females, mean age = 35.6 ± 10.9 years) revealed a significant decrease in the pRNFL, mRNFL, GCIP, and TMV thickness or volume in the study interval. When compared to HC (n = 56, 37 females, mean age = 32.7 ± 8.3 years), the APC of the pRNFL (-.98 ± 3.13%/year) and the GCIP (-1.24 ± 2.56%/year) were significantly more pronounced in PwE (p = .01 and p = .046, respectively). Of note, atrophy of the mRNFL was significantly influenced by the number of antiseizure medications (ASMs; p = .047) and increasing age of PwE (p = .03). Contradictory results, however, were revealed for the impact of seizures.

Significance: In epilepsy, progression of retinal neuroaxonal loss was already detectable at short-term follow-up. PwE who receive a high number of ASMs seem to be at risk for accelerated neuroaxonal loss, stressing the importance of well-considered and effective antiseizure therapy.

Objective: Health state utilities are required to obtain quality adjusted life years, a common metric that informs clinical decision-making at individual, group, and health policy levels. Health state utilities are different from health-related quality of life, and their distribution across patients with epilepsy, as well as the factors that impact them, have not been studied in depth. We aimed to describe the distribution of health state utilities in people with epilepsy and the impact of different combinations of clinical and demographic factors on health state evaluation.

Methods: We performed a retrospective analysis of patients' data prospectively collected in the Calgary Comprehensive Epilepsy Program registry. Patient-reported health state utilities were measured using the 5-level EuroQol 5-Dimension scale (EQ-5D-5L) completed at their initial assessment. EQ-5D-5L index scores were derived via the time trade-off approach based on Canadian norms, and their distribution across different health states and patient characteristics was obtained. The Tobit regression model was used to evaluate the determinants of EQ-5D-5L index scores.

Results: Of 1446 patients included in this analysis, 724 (50.5%) were female. The median (interquartile range) Canada-normed EQ-5D-5L index score was .87 (.71-.91). Patients with significantly lower health utilities were more likely to be female (p = .008), to be older (p = .034), to be unmarried (p = .013), to have failed to achieve 1-year seizure freedom (p < .001), to have no postsecondary education (p = .028), to be depressed (p < .001), to have antiseizure medication side effects (p = .001), to be unemployed (p < .001), and to be unable to drive (p < .001). A look-up table of health utilities based on combinations of clinical-demographic characteristics was produced.

Significance: Health utility estimates for combinations of different health states in people with epilepsy attending specialty clinics are now available. These can help guide clinical decision-making in routine clinical practice, economic evaluations of treatment interventions, and health care policies.

Objective: Wearable nonelectroencephalographic biosignal recordings captured from the wrist offer enormous potential for seizure monitoring. However, signal quality remains a challenging factor affecting data reliability. Models trained for seizure detection depend on the quality of recordings in peri-ictal periods in performing a feature-based separation of ictal periods from interictal periods. Thus, this study aims to investigate the effect of epileptic seizures on signal quality, ensuring accurate and reliable monitoring.

Methods: This study assesses the signal quality of wearable data during peri-ictal phases of generalized tonic-clonic and focal to bilateral tonic-clonic seizures (TCS), focal motor seizures (FMS), and focal nonmotor seizures (FNMS). We evaluated accelerometer (ACC) activity and the signal quality of electrodermal activity (EDA) and blood volume pulse (BVP) data. Additionally, we analyzed the influence of peri-ictal movements as assessed by ACC (ACC activity) on signal quality and examined intraictal subphases of focal to bilateral TCS.

Results: We analyzed 386 seizures from 111 individuals in three international epilepsy monitoring units. BVP signal quality and ACC activity levels differed between all seizure types. We found the largest decrease in BVP signal quality and increase in ACC activity when comparing the ictal phase to the pre- and postictal phases for TCS. Additionally, ACC activity was strongly negatively correlated with BVP signal quality for TCS and FMS, and weakly for FNMS. Intraictal analysis revealed that tonic and clonic subphases have the lowest BVP signal quality and the highest ACC activity.

Significance: Motor elements of seizures significantly impair BVP signal quality, but do not have significant effect on EDA signal quality, as assessed by wrist-worn wearables. The results underscore the importance of signal quality assessment methods and careful selection of robust modalities to ensure reliable seizure detection. Future research is needed to explain whether seizure detection models' decisions are based on signal responses induced by physiological processes as opposed to artifacts.

Objective: Epilepsy surgery is a treatment option for patients with seizures that do not respond to pharmacotherapy. The histopathological characterization of the resected tissue has an important prognostic value to define postoperative seizure outcome in these patients. However, the diagnostic classification process based on microscopic assessment remains challenging, particularly in the case of focal cortical dysplasia (FCD). Imaging mass spectrometry is a spatial omics technique that could improve tissue phenotyping and patient stratification by investigating hundreds of biomolecules within a single tissue sample, without the need for target-specific reagents.

Methods: An in situ proteomic technique called matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is here investigated as a potential new tool to expand conventional diagnosis on standard paraffin brain tissue sections. Unsupervised and region of interest-based MALDI-MSI analyses of sections from 10 FCD type IIb (FCDIIb) cases were performed, and the results were validated by immunohistochemistry.

Results: MALDI-MSI identified distinct histopathological features and the boundaries of the dysplastic lesion. The capability to visualize the spatial distribution of well-known diagnostic markers enabling multiplex measurements on single tissue sections was demonstrated. Finally, a fingerprint list of potential discriminant peptides that distinguish FCD core from peri-FCD tissue was generated.

Significance: This is the first study that explores the potential application of MALDI-MSI in epilepsy postsurgery fixed tissue, by utilizing the well-characterized FCDIIb features as a model. Extending these preliminary analyses to a larger cohort of patients will generate spectral libraries of molecular signatures that discriminate tissue features and will contribute to patient phenotyping.