Colin Bruce Josephson

Objective: Persons with epilepsy may experience many postictal symptoms after a seizure, which can significantly impact quality of life. We aimed to determine the frequency, duration, and severity of postictal symptoms to better characterize the postictal period. Methods: Our cross‐sectional questionnaire was adapted from a prior pediatric postictal survey. Face and content validity were evaluated by epilepsy experts and patients from the Calgary Epilepsy Program (CEP). The survey was pilot tested and modified, consisting of 14 physical, cognitive, and psychiatric postictal signs and symptoms. Consecutive CEP adults who had agreed to participate in research and experienced a seizure in the prior 2 years were approached. CEP clinical data were used to supplement survey data. Frequency of factors alleviating and exacerbating postictal symptoms were examined. Spearman's rho was used to explore associations between survey and CEP registry data with statistical significance at ≤ 0.05. Results: Of 351 patients approached, 313 agreed to participate (89%). Fourteen were lost after consent was obtained, and 15 were excluded (incomplete surveys, missing registry data, not having epilepsy). Of the 298 final participants, 54% were female, mean age was 40 years (SD = 15.6), and 95% (282/298) experienced at least one postictal symptom. The three most frequent postictal symptoms were fatigue, sleepiness, or tiredness (84%), confusion or difficulty thinking clearly (75%), and memory problems (69%). For eight of 14 captured postictal symptoms, the most frequently reported symptom duration was <5 min. Mean postictal symptom burden score was correlated with patient reported quality of life and epilepsy‐related disability measures. Sleep or rest, medication, and food or drinks were the most common alleviating factors. Lack of rest or sleep, and stress most often exacerbated postictal symptoms. Significance: This work contributes toward a better understanding of the postictal period and informs the development of future interventions to minimize the impact of the postictal period in epilepsy.

Objective: Recent work has provided population‐based estimates of the prevalence of cause‐specific epilepsy across the lifespan in Denmark. We sought to externally validate these Danish “secondary epilepsy” findings to ascertain consistency across geographic regions. Methods: We conducted a population‐based cross‐sectional study using linked Alberta Health Care Insurance Plan administrative datasets. Epilepsy was identified using a validated algorithm. Point prevalence was calculated on December 31, 2018 among residents alive at that date. Secondary epilepsy was assigned when a recognized antecedent condition (stroke, traumatic brain injury [TBI], dementia, brain neoplasm, congenital brain malformations/perinatal conditions, or central nervous system infection) occurred before the first epilepsy diagnosis. If no antecedent condition was identified, the case was classified as “idiopathic.” In sensitivity analyses, Danish‐derived definitions were replaced with published validated case definitions. Results: Among ~4.274 million Albertans, 26 056 prevalent epilepsy cases were identified (606 per 100 000; 584 females, 628 males). Idiopathic epilepsy accounted for 394 per 100 000 and secondary epilepsy for 212 per 100 000. Prevalence peaked in childhood, stabilized by early adulthood, and then increased after age 40 years, where male cases exceeded females. The proportional contribution of idiopathic epilepsy declined after midlife, with secondary epilepsy predominating by ages 65–70 years. Cause‐specific patterns were largely consistent with Denmark, exhibiting age‐dependency: congenital/perinatal causes in youth, TBI most common in young/middle‐aged adults, and stroke and dementia in older adults. Use of published validated definitions reduced secondary epilepsy prevalence to 139 per 100 000 and increased idiopathic prevalence to 467 per 100 000, largely driven by fewer cases attributed to stroke. Significance: Secondary epilepsy becomes increasingly dominant with age, but cause‐specific attribution is sensitive to administrative case definitions. This highlights the need for rigorous and consistent algorithms to improve burden modeling, surveillance, and health‐system planning. These analyses validate the Danish estimates and inform future work deriving regional cause‐specific epilepsy burden.

Objective: Epilepsy surgery is a recommended treatment for individuals with drug‐resistant epilepsy. However, patients often face significant challenges in decision‐making due to a lack of accessible and high‐quality information. Methods: We conducted a scoping review to identify the information needs of people considering surgery for epilepsy. Nine databases were searched between 1990 and 2025 to identify research relevant to this review. We included studies that described the information needs of people considering epilepsy surgery and that evaluated available resources to support this decision. Abstract screening, full text review, and data charting were done in duplicate. Risk of bias assessment was completed by one reviewer. Results: We identified 2949 studies, of which 18 were included, addressing the following topics: patient informational needs ( n = 12), resources designed to support patients through epilepsy surgery decision‐making ( n = 5), and resource readability ( n = 2). Themes of information needs included discussion of risks and benefits, personalized prognosis, medical assessments needed to determine eligibility, and procedure‐specific outcomes. Six studies identified the importance of involving epilepsy specialists in information sharing, and six highlighted the importance of patient testimonials. Multiple studies suggested current resources lack clarity and consistency, and two identified average readability of available resources to be at or above grade 12 level. Five studies evaluated resources including a mixed reality education tool, a caregiver intensive information program, use of a decision coach, and a patient information program. Providing patient‐centered information can reduce anxiety/depression and increase quality of life for patients and caregivers. Significance: This review highlights critical gaps in the quality and accessibility of information for individuals considering epilepsy surgery. Patient testimonials emerged as a powerful tool in supporting informed decision‐making. Future efforts should focus on developing culturally responsive, readable, and patient‐centered resources tailored to diverse epilepsy populations.

Introduction/Aims: Objective, scalable measures of function are needed in amyotrophic lateral sclerosis (ALS). Research‐grade accelerometers are promising but may be difficult to deploy for prolonged remote monitoring, whereas consumer smartwatches offer a practical alternative. We evaluated the feasibility of long‐term smartwatch monitoring in ALS and compared smartwatch‐ and accelerometer‐derived daily step counts. Methods: In this single‐centre prospective observational study, participants wore a Fitbit Sense (smartwatch) on the wrist longitudinally and an ActiGraph GT9X Link (accelerometer) on the opposite wrist during clinic‐aligned assessment periods. Device comparison was restricted to concurrent valid days (≥ 10 h wear) and included paired comparison of mean daily step counts, Pearson correlation, Bland–Altman analysis, and proportional bias assessment. Results: Forty participants were enrolled and 39 contributed data across 8093 smartwatch and 915 accelerometer days. Step count comparison included 503 concurrent valid days from 34 participants. Mean daily step counts were 3480 (SD 4365) for smartwatch and 4066 (SD 4797) for accelerometer ( p < 0.0001), with strong correlation ( r = 0.91, p < 0.0001). Mean bias was −586 steps for smartwatch, with 95% limits of agreement from −4193 to 3021. Among participants with ≥ 6 months of concurrent data, devices showed similar decline over time (interaction p = 0.76). Discussion: Long‐term remote monitoring using a smartwatch was feasible in ALS. Smartwatch‐derived step counts were strongly correlated with accelerometer‐derived estimates but were systematically lower and showed wide day‐level limits of agreement. Smartwatch‐derived step counts may be useful for group‐level analyses and longitudinal monitoring, though device‐specific bias should be considered in interpretation.

Objective: Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a commonly prescribed first‐line ASM, yet only approximately half of patients achieve sustained seizure freedom. Treatment selection remains largely empirical. We aimed to develop and independently validate a multimodal predictive model to estimate response to VPA and support more individualized treatment strategies. Methods: This cross‐sectional treatment response modeling study used data from a subset of the international Epi25 cohort (Belgium, Finland, Germany). Individuals with epilepsy were included if they had received VPA monotherapy and had available genetic or clinical data. Discovery data (1965–2021, 58% female) were split into a training set ( n = 196) and test set ( n = 133). Independent validation was performed in a Canadian cohort (2021–2022, n = 156, 40% female). The primary outcome was binary VPA response. Responders achieved ≥12 months of seizure freedom attributed to VPA; nonresponders had >50% seizure recurrence or discontinued VPA due to inefficacy, adverse effects, or unclear reasons. The predictive algorithm integrated features derived from common and rare variants in VPA pharmacokinetic and pharmacodynamic genes, in vitro neuronal VPA response measures, and clinical features. Model performance was assessed using accuracy, predictive values (negative predictive value [NPV]/positive predictive value [PPV]), and area under the curve (AUC). Results: In the independent validation cohort, the multimodal classifier achieved a balanced accuracy of 63% (95% confidence interval [CI] = 52%–73%), NPV of 70% (95% CI = 51%–85%), PPV of 60% (95% CI = 46%–72%), and AUC of .73 (95% CI = .63–.83). Models restricted to single or dual data modalities showed consistently lower predictive performance. Significance: This proof‐of‐concept study demonstrates that integrating genetic, cellular, and clinical data enables prediction of VPA treatment response with clinically meaningful accuracy. Although not yet ready for clinical application, this approach supports the feasibility of biomarker‐informed ASM selection and may ultimately reduce time to effective seizure control.

Objective: Emerging adulthood (EAs; ages 19–29 years) is a unique developmental stage marked by major psychological, social, and occupational transitions. We sought to characterize the clinical, psychosocial, and surgical features of epilepsy in emerging adulthood, considering both current age and age at epilepsy onset. Methods: We conducted cross‐sectional analyses in two cohorts, an adult epilepsy registry in Calgary, Canada (single tertiary center; first visits 2007–2024), and a multi‐center epilepsy surgery satisfaction cohort recruited from three Canadian centers and Gothenburg, Sweden. Age categories were 29 years. Outcomes included seizure freedom, anti‐seizure medications, substance use, patient‐reported outcomes measures, and surgical characteristics (procedure type, wait times, seizure and psychosocial outcomes, and satisfaction). Results: Of 7439 registry patients, 1724 (23%) were EAs and 1252 had EA‐onset epilepsy. Compared with other ages, EAs had lower 1‐year seizure freedom and higher depression, anxiety, disability, and substance use (all p 's < .001). EA‐onset epilepsy showed similar psychosocial burden, especially for anxiety and substance use. In 240 epilepsy surgery patients (69 EAs), EAs were less likely to undergo selective amygdalohippocampectomy (odds ratio [OR] .17, 95% confidence interval [CI] .03–.94) and had higher rates of permanent complications (OR 6.01, 95% CI 1.45–24.94). EA also spent a greater proportion of life waiting for epilepsy surgery and reported lower post‐operative psychosocial satisfaction despite a seizure‐freedom rate similar to that for other ages. Significance: Epilepsy during emerging adulthood is associated with elevated psychosocial morbidity and less seizure freedom, whereas EAs undergoing epilepsy surgery have a distinct case profile with comparable seizure freedom, more complications, and lower post‐operative psychosocial satisfaction. These findings highlight the distinctive impact of epilepsy during this developmental stage and underscore the need for targeted transitional care, mental‐health support, and timely surgical evaluation. Longitudinal studies are warranted to elucidate causal mechanisms and inform targeted interventions.

Purpose of review: Epilepsy increases risk of cardiovascular morbidity and mortality, and growing evidence suggests broader systemic effects, including on bone health. This review examines the evolving concepts of the “epilepsy–heart syndrome’ and the impact that both epilepsy and antiseizure medications (ASMs) have on cardiovascular and both health, highlighting why timely recognition is clinically and scientifically imperative. Recent findings: Epilepsy promotes myocardial injury through catecholamine surges, hypoxemia, and ischemia, resulting in arrhythmias, diastolic dysfunction, and accelerated atherosclerosis. Conversely, cardiovascular disorders and metabolic dysregulation predispose to epilepsy, reinforcing a bidirectional relationship. Enzyme-inducing ASMs increase lipid levels, attenuate statin efficacy, and increase risks of long-term cardiovascular disease. Both enzyme-inducing and noninducing ASMs contribute to reduced bone mineral density and potentially to increased fracture risk via altered vitamin D metabolism and hormonal effects. Summary: Epilepsy is a multisystem disorder that encompasses cardiovascular disease and skeletal fragility. Although formal guidelines are currently lacking, clinicians should consider integrating cardiovascular screening, rational ASM selection, and proactive bone-health surveillance into routine epilepsy management. Research should focus on longitudinal, mechanistic, and interventional studies to improve cardiovascular and bone health and to validate emerging screening and management guidelines to improve overall health in epilepsy.

Clear documentation and transfer of information between health care providers is key to ensuring the delivery of high‐quality patient care. Our aim was to determine how to optimize and standardize physician documentation in outpatient epilepsy clinics as well as to highlight challenges and barriers to their implementation. We conducted a scoping review of studies implementing standardization and optimization of physician documentation within outpatient epilepsy clinics. The study is reported according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses Extension for Scoping Reviews. The following databases were searched from inception to March 2025: MEDLINE, Embase, APA PsycInfo, CINAHL, and Cochrane Library. All abstracts, full texts, and data charting were completed in duplicate. The search yielded 10 268 studies, of which 16 met eligibility criteria. Studies were primarily from the United States ( n = 12, 75.0%) and focused on adult practices ( n = 9, 56.25%). Studies were quality improvement framework/consensus guideline investigations ( n = 9, 56.3%), observational audits/cross‐sectional designs ( n = 2, 12.5%), and retrospective cohort/chart reviews ( n = 2, 12.5%), followed by several mixed‐methods development, observational field study, and observational toolkit implementation designs ( n = 1, 6.25% each). Most clinical notes were in electronic medical records ( n = 14, 87.5%) using free‐text fields ( n = 4, 25.0%), structured fields ( n = 2, 12.5%), or hybrid approaches ( n = 7, 43.8%). Common Data Elements included seizure information and treatment counseling information. Outcomes associated with standardized note implementation included reduced epilepsy‐related adverse events, better seizure control, and more consistent documentation of pertinent patient information. Highlighted challenges to implementation included workflow disruptions, hesitation to initial uptake, and cost‐related barriers such as information technology support. Implementation of standardized documentation was associated with fewer adverse events and better seizure control. Future efforts should prioritize inclusive design, have expanded quality indicators, be easy to use at point of care, and have robust evaluation metrics to optimize their utility for epilepsy care.

The artificial intelligence (AI) revolution is upon us. It will inevitably form a central component of epilepsy workflows and patient advocacy. Therefore, it behooves us as health care providers to ride the crest of this wave and guide its direction for the benefit of all people with epilepsy. Emerging AI‐based solutions include decision support tools, automated interpretation of electroencephalography (EEG) and brain imaging, and wearable devices that detect seizures and improve patient safety. Pipelines, including decentralized approaches and federated learning, are now being built that will democratize access and facilitate the next generation of AI tools for the global epilepsy community. Despite this, enduring issues remain incompletely addressed. For example, AI requires high volumes of data, leading to concerns about ethical ownership, stewardship, and privacy. Few AI‐based tools have progressed from derivation to validation stages, and only rare exceptions undergo real‐world evaluation. Inadvertent harmful algorithmic and decision allocation biases also continue to represent major risks to the global epilepsy population. Additional barriers include geographical disparities in computing resources, proprietary ownership of electronic health records, EEG, and brain‐imaging platforms, and greenhouse gas emissions related to the demanding power requirements of AI. Therefore, to fully avail ourselves of the benefits of AI, we assert that ethical, equitable, and effective AI for epilepsy requires collaboration from the entirety of the global epilepsy community. Fundamental to this is early and deliberate engagement of people from low‐ and middle‐income countries to ensure that AI‐based solutions do not exacerbate existing global disparities. Ultimately, we advocate for “decision intelligence” approaches to the development of AI‐based epilepsy solutions, which involves early engagement of all interest‐holders to ensure that the correct questions are addressed and the right technical approaches are deployed to maximize value for the global epilepsy community.

Consensus‐based recommendations (CBRs) are essential for health care decision‐making when evidence is limited or conflicting. They can be developed using established methodologies such as the Delphi technique, the nominal group technique (NGT), and the RAND Corporation/University of California Los Angeles (UCLA) Appropriateness Method (RAM). This review explores the advantages and disadvantages of these methods and their applications in epilepsy. A narrative review using PubMed (November 22, 2017 to November 22, 2022) was undertaken examining publications describing Delphi, NGT, and RAM. The frequency of use of each method and their applications in epilepsy care were also reviewed (1966 to October 31, 2023). Sixteen articles were included describing the different consensus‐based methods. The advantages and disadvantages of each method varied widely. The Delphi technique, the most widely used method, emerged as adaptable for instances with limited evidence or impracticality of face‐to‐face interactions. Although NGT favors prompt consensus in single‐session formats, the RAM offers a balanced approach with its hybrid structure. We identified 64 epilepsy studies that used consensus methods, with 58 utilizing the most widely used technique, the Delphi. The Delphi guided consensus mostly for management including for individuals with rare conditions such as myoclonic–atonic seizures or in those with epilepsy and pregnancy. The NGT guided expert consensus on the use of cannabidiol for Dravet and Lennox–Gastaut syndromes and facilitated decision‐making among pharmacy students addressing ethical issues related to patients with epilepsy who drive. The RAM was applied in four studies for its combined individual and group evaluative approach. It was used to develop recommendations or imaging, create quality‐of‐care indicators for infantile spasms, and establish a web‐based tool for assessing surgical candidacy. Consensus methodologies are crucial to inform robust CBR for epilepsy management where clinical practice guidelines are not possible due to limited evidence. The best method depends on the study goal and available resources.