With keen interest we read Ooi et al.'s recent publication,1 and we congratulate the authors on their impressive work. The authors show that machine-learning models incorporating advanced quantitative MRI features (e.g., cortical folding and interhemispheric asymmetry) meaningfully improve seizure recurrence predictions after a first seizure compared with clinical features alone (AUC 0.65 vs. 0.57), in a carefully selected cohort of adult patients with nondiagnostic MRI and EEG. Importantly, by excluding patients with epileptogenic MRI findings (and epileptiform EEG abnormalities), the authors avoid incorporation bias—the methodological error of using predictor variables that directly define the outcome, which can artificially inflate model performance.2, 3 This makes the study particularly compelling, as it offers insight into novel imaging-based predictors beyond traditional clinical and demographic variables, which are known to have limited predictive value.4, 5 Because MRI and EEG findings are an integral part of clinical decision-making in practice5-8 previously published models have included them as predictors.9, 10 One of these models,10 as mentioned by Ooi et al.,1 included patients with epileptogenic MRI lesions known to be associated with the outcome (seizure recurrence), and the high discriminatory ability of that model may be attributed to this.1 Similarly, our model published in 2018 on childhood epilepsy prediction showed that including EEG findings—including epileptiform EEG abnormalities—as a predictor substantially increased model performance compared to clinical features alone (AUC 0.86 vs. 0.67).9 Since the presence of epileptiform EEG or epileptogenic MRI findings after a first seizure is often considered sufficient for an epilepsy diagnosis, including them as predictors is methodologically suboptimal.2, 5, 11 We therefore agree with Ooi et al.'s approach of excluding patients with these diagnostic features when assessing the added predictive value of potential new diagnostic or prognostic biomarkers. In this letter we seek to point out these contrasting modeling strategies—specifically, the choice to include or exclude diagnostic features—and to encourage researchers and clinicians to explicitly balance the risk of incorporation bias against clinical applicability. Excluding diagnostically decisive features during model development inevitably limits a model's ability to capture the full range of relevant information. However, it also produces more realistic predictions, enabling discovery of new biomarkers.12 We advocate for broader dialogue to harmonize study designs in first-seizure research, and echo Ooi et al.'s view that integrating novel biomarkers13 may meaningfully advance clinical prediction models. We thank the authors for their important contribution to the field. None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Dravet syndrome (DS) is a drug-resistant developmental and epileptic encephalopathy, often requiring three or more antiseizure medications (ASMs). Consequently, the therapeutic landscape is highly complex, combining DS-specific agents (stiripentol, STP; cannabidiol, CBD; fenfluramine, FFA), non-specific ASMs, and non-pharmacologic options such as dietary therapy or neuromodulation. In addition, recognition of patients' changing needs across the lifespan, together with the essential contribution of caregiver education to effective treatment oversight-including awareness of potential drug-drug interactions and adverse events-emphasizes the value of an integrated and forward-looking approach. A consensus initiative was developed to guide clinicians in the management of patients with DS, with a particular focus on STP-containing regimens. Based on a literature review and clinical vignette discussions, a nominal group of five international DS experts developed 38 statements across six themes: (i) general principles, (ii) guiding physicians to empower families, (iii) STP as add-on to specific and non-specific Dravet ASMs, (iv) FFA in regimens containing STP, (v) CBD in regimens containing STP, and (vi) patient follow-up during treatment initiation. Statements were scored on a 9-point Likert scale (1 = strongly disagree, 9 = strongly agree) first by the nominal group and then by an international panel of 59 DS clinicians. Consensus was defined as ≥75% rating ≥7 and/or a median ≥8. Thirty-four of the 38 statements (89%) reached consensus among both the nominal group and the international panel; one did not reach consensus in either, and three reached consensus only among the nominal group. Both panels agreed on the importance of involving families in treatment decisions and follow-up, as well as on key aspects of polytherapy management, including ASM initiation, treatment adjustments, and adverse event management. This international consensus integrates evidence and clinical expertise to establish shared principles that address a long-standing gap in the polytherapeutic management of Dravet syndrome. Dravet syndrome is a rare and severe form of epilepsy that begins in early childhood, with seizures that often persist throughout life. Because the disease is highly drug resistant, most patients are treated with polytherapy, making clinical management complex for clinicians. This consensus brings together published evidence and expert experience to provide practical guidance on the management of polytherapy in Dravet syndrome, supporting clinicians in optimizing patient care.

Ketogenic dietary therapies (KDTs) are the treatment of choice for Glut1 Deficiency Syndrome (Glut1DS), providing dietary ketones as an alternative fuel to the brain and effectively controlling seizures. Recent evidence indicates insufficient seizure control in Glut1DS patients despite adequate KDT and ketosis. Fifty-three patients, diagnosed with Glut1DS and treated by KDT, were followed in a single-center outpatient clinic from 2000 to 2023. Epilepsy, present in 44 patients, was analyzed for seizure control, EEG changes, and potential correlations to clinical and genetic features. Epilepsy response to KDT was defined as a >90% seizure reduction on KDT monotherapy. On KDT monotherapy 27/44 (61%) patients became >90% seizure free, rated as responders. 17/44 were non-responders. Within this group, 10/17 patients responded to KDT plus antiseizure comedication. In 7 patients, KDT plus antiseizure comedication failed to control seizures. No correlations of seizure control to gender, age at start or type of KDT, or SLC2A1 variants were observed. In responders (n = 27), EEG epileptic activity, evident in 15/27 patients, improved on KDT in 5 patients. In non-responders (n = 17), EEG epileptic activity was evident in 14/17 and improved on KDT in 9 patients. EEG background slowing prior to KDT normalized in KDT in all responders (4/27), but in none of the non-responders (4/17). Epilepsy is a dominant feature of Glut1DS. KDT provides efficient seizure control, but failure to control epilepsy is more common than expected. KDT epilepsy response did not correlate with seizure type, clinical, or genetic features, emphasizing the complexity of this entity. Add-on antiseizure medication can be effective in some patients, without individual drug superiority. Epileptic activity on EEG did not prove a good marker for outcome, but reversible EEG background slowing on KDT might be predictive for favorable seizure control. Impaired glucose transport into the brain causes a brain energy crisis termed Glut1 Deficiency. Ketogenic diets mimic fasting, provide ketones as an alternative fuel, and effectively restore brain function. In our study, this worked for ca. 60% of patients. To our surprise, epilepsy persisted in about 40% of patients despite ketogenic diets for reasons unknown. Additional medication against epilepsy randomly helped in some patients. We analyzed many parameters without finding obvious explanations. Electrical brain activity improvement on ketogenic diets might be a future marker for efficient seizure control.

Treatment selection for infantile epileptic spasms syndrome (IESS) is complex and multifaceted, and currently no electroencephalogram (EEG) biomarkers can guide this decision by predicting treatment response. We tested the predictive value of phase-amplitude coupling (PAC) as IESS patients are known to have elevated PAC. We analyzed retrospective EEG recordings from 40 IESS patients, before and after treatment, and 20 healthy controls. Patients were classified as responders (n = 25) or nonresponders (n = 15) based on short-term treatment outcomes. We measured PAC in each EEG using modulation index (MI) and mean vector length (MVL) and analyzed the relationship between pre- and posttreatment values and the ability of pretreatment values to predict response. MI and MVL values decreased with treatment in almost all subjects. However, nonresponders had significantly higher pretreatment MI than responders (p < 0.05), suggesting utility for predicting treatment response. Logistic regression modeling suggested that a 0.5-unit decrease in ln(MI), which is approximately one IQR of the pretreatment ln(MI) values, results in a 3.5-fold increase in odds of positive treatment response. MI reflects short-term treatment response and is a candidate predictive EEG biomarker for IESS. MI may offer individualized insights for treatment selection and management strategies for IESS. We examined brain activity in infants with infantile epileptic spasms syndrome (IESS) to predict which infants' seizures would stop with standard medication. Specifically, we measured coupling between slow and fast brain waves in both healthy infants and those with IESS. Infants for whom medication failed had stronger coupling, even before the treatment was started, while those with weaker coupling (more similar to healthy infants) were more likely to have their seizures stop after treatment. These findings suggest that brain wave coupling could help doctors predict which infants will need more aggressive treatment.

First seizure events are common and may exert an immediate and profound impact on people's lives. Less understood are their long-term consequences. This prospective, longitudinal study aimed to measure and compare psychosocial and health-related work productivity trajectories following first seizure events of various etiologies. Adults with first seizure events were recruited from five epilepsy centers in Australia and the US between 2020 and 2023. Participants completed questionnaires covering health-related quality of life (HRQOL; EQ-5D-5L, QOLIE-31), anxiety and depressive symptomatology (HADS), and productivity (WPAI) within 6 weeks of their first seizure event, and 6- and 12 months later. One hundred ninety-six participants (median age 42 years, 55.6% male) met inclusion criteria. 101 (51.5%) had newly-diagnosed epilepsy, 46 (23.4%) had acute symptomatic seizures, and 49 (25.0%) had syncope (seizure mimic). Compared to baseline, at 12-month follow-up, the acute symptomatic seizure group showed significant improvement in EQ-5D-5L utility (p = 0.001). The newly diagnosed epilepsy and acute symptomatic seizure groups both demonstrated improved QOLIE-31 scores over 12 months (acute symptomatic seizure p = 0.025; newly diagnosed epilepsy p < 0.001). The newly diagnosed epilepsy group showed significant reductions in absenteeism (p < 0.001), presenteeism (p < 0.001), overall work impairment (p < 0.001), and activity impairment (p = 0.002). The acute symptomatic seizure group had a significant reduction in informal care needs (p < 0.001). Anxiety and depressive symptomatology remained unchanged across all groups. HRQOL improved for people with acute symptomatic seizures and newly diagnosed epilepsy over time, but anxiety and depressive symptomatology remained unchanged. Future studies may explore interventions to improve screening and treatment of anxiety and depression for people following first seizure events. This study investigated changes in quality of life, anxiety and depressive symptomatology, and health-related work productivity over a 12-month period for adults with first seizure events. Participants reported improvements in quality of life, reduced sick days, increased productivity at work, and less need for informal care. Concerningly, there was no change in their anxiety and depressive symptoms. The findings of this study may prompt first seizure clinicians to regularly screen patients for anxiety and depressive disorders, and treat these appropriately.

Human telomerase reverse transcriptase (hTERT) is a key determinant of telomere maintenance and cellular aging. Oxidative stress plays a role in neurodegenerative processes by causing cellular damage through increased reactive oxygen species. Our study aimed to reveal the relationship between hTERT and oxidative stress in the pathophysiology of epilepsy. The study included 45 individuals diagnosed with epilepsy and 55 healthy controls. hTERT concentration, total oxidant status (TOS), total antioxidant status (TAS), superoxide dismutase (SOD), and thiol-disulfide homeostasis were measured in serum samples. A significant decrease in hTERT levels, an increase in oxidative stress markers (TOS, OSI), and a decrease in antioxidant levels (TAS, SOD), and total and native thiol levels were determined in epilepsy patients. In addition, a significant and negative correlation was found between hTERT and native thiol. Our study suggested that the interaction between oxidative stress and hTERT levels in the pathophysiology of epilepsy may play an important role in seizure generation and progressive neural damage. This study will form the basis for further research and guide the identification of potential biomarkers for treating epilepsy. We measured the levels of a protective protein that helps preserve chromosomes and several markers of cell stress in people with epilepsy and healthy volunteers. People with epilepsy showed lower levels of this protective protein, weaker antioxidant defenses, and higher oxidative stress. We also found that lower protein levels were linked to fewer molecules that guard cells from damage. These changes may help explain why seizures occur and why the brain can suffer ongoing injury in epilepsy.

To investigate the frequency, predictors, and clinical implications of diagnostic reassessment in patients previously diagnosed with childhood-onset epilepsy during the transition period to adult care at a tertiary epilepsy center. We conducted a retrospective cohort study of 317 patients previously diagnosed with childhood-onset epilepsy who underwent diagnostic reassessment between April 2018 and December 2023 at age 16 years or older at a tertiary epilepsy center in Japan. Diagnostic revision was defined as a newly established or corrected epilepsy/epilepsy syndrome diagnosis, identification of structural or genetic/metabolic etiologies, or diagnosis of non-epileptic conditions. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of diagnostic revision. A new or revised diagnosis was established in 60 of the 317 patients (18.9%). Independent predictors of diagnostic revision included exclusively non-motor seizures (adjusted odds ratio [aOR] = 7.610; 95% confidence interval [CI]: 2.660-21.767; p < 0.001) and weekly or monthly seizure frequency (aOR = 3.370; 95% CI: 1.265-8.976; p = 0.015), whereas prior visits to other epilepsy centers were strongly protective (aOR = 0.047; 95% CI: 0.015-0.146; p < 0.001). Sensitivity analyses yielded consistent results. Newly identified etiologies include focal cortical dysplasia, hippocampal sclerosis, and pathogenic genetic variants such as CDKL5, PCDH19, and SYNGAP1. Diagnostic reassessment facilitated antiseizure medication withdrawal in patients with self-limited epilepsy and non-epileptic events. Nearly one in five patients previously diagnosed with childhood-onset epilepsy required diagnostic revision during the transition to adult care. Non-motor seizure semiology and moderate seizure frequency were the major predictors of diagnostic revision, highlighting the diagnostic uncertainty associated with subtle clinical presentations. These findings highlight that systematic reassessment, especially for individuals who have not previously undergone specialized epilepsy center evaluation, is essential for achieving an accurate diagnosis and optimizing management in adulthood. Many people diagnosed with epilepsy in childhood continue medical care into adulthood, but their diagnosis may need to be reviewed later in life. In this study, nearly one in five patients who had been diagnosed with childhood-onset epilepsy required a change or refinement of their diagnosis when reassessed after age 16. Patients with seizures without clear physical movements and those whose seizures occurred weekly or monthly were more likely to need diagnostic review. These findings highlight the importance of reviewing the diagnosis during adolescence, especially for patients who have not previously been evaluated at specialized epilepsy centers.

ObjectiveCharacterize electroencephalogram (EEG) dynamics during propofol withdrawal in patients with generalized convulsive status epilepticus (GCSE) and explore their association with functional outcomes.MethodsWe conducted a retrospective cohort study of adult patients with GCSE who received continuous EEG monitoring and propofol sedation. EEG data were analyzed during two predefined periods: during sedation (0.5–1.5 mg/kg/h) and 4 h after complete sedation withdrawal. Preprocessed EEG signals underwent spectral and complexity analyses, including relative spectral power across frequency bands, alpha‐delta ratio, median frequency (MF), spectral edge frequency 85% (SEF85), and sample entropy. Principal component analysis was applied to EEG trajectory vectors for dimensionality reduction; hierarchical clustering was used to identify distinct evolution patterns during sedation withdrawal. Associations between EEG patterns, SE duration, and clinical outcomes were assessed.ResultsTwenty‐one patients were included. At the population level, EEG features shifted toward faster and more complex activity after sedation withdrawal, with decreased delta power, increased theta, alpha, and beta power, and greater signal complexity. Clustering analysis identified two distinct EEG trajectories: one subgroup (24%) showed marked recovery of cortical dynamics with significant increases in frequency metrics and entropy, while the other (76%) demonstrated minimal changes, with persistent delta‐band dominance and low complexity. Longer SE duration was significantly associated with the minimal‐change group (p = 0.007). No significant differences in functional outcomes were observed between groups.SignificanceEEG dynamics during propofol withdrawal in patients with GCSE evolve along distinct trajectories. Two distinct EEG trajectories emerged: one toward normalization and another with persistently slow, low‐complexity patterns. The majority of patients did not normalize their EEG after sedation withdrawal. Notably, patients with prolonged GCSE were overrepresented in the group lacking EEG recovery. However, these trajectories could not be correlated with functional prognosis. These findings underscore the potential of early EEG trajectories as markers of cerebral recovery.Plain Language SummaryWe studied how brain activity changes after stopping the sedative propofol in adults treated for severe, long‐lasting seizures. Most patients showed little improvement in their brain activity after sedation was stopped, while a smaller group showed signs of recovery. Patients whose seizures lasted longer were more likely to have little or no improvement in their brain activity patterns. These early brain activity patterns did not predict long‐term functional outcomes but may help identify how the brain is recovering after severe seizures.

ObjectiveTo investigate a recently developed MRI technique for mapping the Mean Diffusivity of Tissue (MDT), which improves diffusion MRI imaging of the cerebral cortex by reducing partial volume effects from cerebrospinal fluid (CSF). As cortical lesions are common in patients with focal epilepsy, we explored the clinical value of MDT imaging in patients with drug resistant epilepsy and low‐grade glioma.MethodThis is a prospective study in which 18 patients undergoing evaluation for epilepsy surgery and five patients undergoing evaluation for low‐grade glioma were recruited. Patients underwent conventional MRI and MDT imaging. The images were analyzed by a neuroradiologist who visually assessed the images using a lesion visibility score.ResultsElevated MDT coincided with suspected FLAIR‐positive FCD lesions in the majority of cases (5 out of 8 lesions). Ulegyria was also MDT‐positive, but heterotopias were not. MDT did not detect abnormalities in epilepsy surgery cases previously deemed MRI‐negative. In low‐grade gliomas, MDT and FLAIR findings were co‐localized; however, the MDT abnormalities were more conspicuous, and tumor‐associated signals were more distinct relative to FLAIR. MDT was helpful in visual demarcation of ischemia and glioma tumor‐associated signals in postoperative imaging.SignificanceMDT frequently aligns with the FLAIR signal, but MDT is visually more prominent. In the presurgical evaluation of epilepsy patients, it contributes to supporting existing or ambiguous findings. The very pronounced MDT signal in low‐grade gliomas might have the potential to be a visual aid in the diagnosis, treatment, and follow‐up of low‐grade gliomas.Plain Language SummaryThis is a pilot study that investigates a newly developed MRI technique called MDT imaging. The study shows that MDT helps identify brain lesions in patients with epilepsy. Finding brain lesions can improve the success of epilepsy surgery and help patients become seizure‐free. MDT imaging also helps visualize tumors in low‐grade glioma patients, which could improve surgical planning. These early findings suggest that MDT could be an additional useful tool for imaging in epilepsy surgery and low‐grade glioma patients, but more research is required to confirm its benefits.

ObjectiveTo examine the real‐world experience, comorbidities, and mental health of patients with epilepsy (PwE) who are currently receiving antiseizure medication (ASM) treatment.MethodsA web‐enabled survey of PwE was conducted from July–September 2023. Patients were recruited via patient panels or physician referrals. US residents, ≥18 years old, with physician‐confirmed diagnosis of epilepsy for ≥1 year, self‐reported focal seizures, ≥1 seizure per month, past/present use of ≥2 ASMs, and currently receiving an ASM for ≥1 month, were eligible. Self‐reported aspects of the treatment journey and disease burden were examined, including four validated patient‐reported outcome measures: Quality of Life in Epilepsy Inventory‐10 (QOLIE‐10), Patient Health Questionnaire‐9 (PHQ‐9), Generalized Anxiety Disorder‐7 (GAD‐7), and Work Productivity and Activity Impairment questionnaire (WPAI). Healthcare resource utilization and perceived levels of caregiver burden were also assessed.ResultsOf 170 patients surveyed, 66.5% reported >1 seizure per month, 75.3% rated their seizures as moderate‐to‐highly severe, and 72.9% reported ≥3 non‐seizure symptoms despite ASM treatment. The most common non‐seizure symptoms were mood issues (76.5%), fatigue/lack of energy (72.4%), and problems with sleep (68.8%). Anxiety (49.4%), migraines (40.6%), and depression (40.0%) were the top reported physician‐diagnosed comorbidities. The mean QOLIE‐10 score was 44.5 (SD, 17.5), indicative of a notable impact on QoL. Overall, 63.5% and 46.5% of patients exhibited moderate‐to‐severe depression and anxiety based on PHQ‐9 and GAD‐7, respectively. Using the WPAI, 60.6% mean work productivity loss was observed, driven by presenteeism. Patients averaged 9.4 outpatient visits and 2.8 emergency visits and/or hospitalizations annually. Of patients requiring caregivers (60.6%, n = 103), 68.9% agreed day‐to‐day and emotional demands from their epilepsy negatively impacted their family/caregivers.SignificanceCollectively, these findings provide a broad perspective of the burden of illness experienced by PwE who are currently receiving treatment and demonstrate unmet needs for additional therapies that can improve patient experience.Plain Language SummaryThe primary treatment goals for epilepsy are to maximize seizure control, reduce side effects of medication, and improve quality of life. In our study, US patients with epilepsy currently using antiseizure medications used a survey to report their perspectives on the epilepsy treatment journey and ongoing burdens from the disease. We found that despite receiving treatment, patients still had a high frequency/severity of seizures, were dissatisfied with medication side effects, reported depression, anxiety, and reduced work productivity, and perceived that their disease had negative impacts on caregivers. New medications that improve the experience for patients with epilepsy are needed.