Alain Lekoubou

Calcitonin gene‐related peptide (CGRP) inhibitors modulate pain and neuroinflammation, a recognized contributor to epileptogenesis and status epilepticus (SE). We examined the association between CGRP inhibitor use and SE hospitalization in epilepsy patients with comorbid migraine. Using TriNetX (130 healthcare organizations), we identified patients with epilepsy from May 2018 through May 2026, and propensity‐matched cohorts for age, sex, race, anti‐seizure medications (ASMs), migraine diagnosis, migraine treatments, and cognitive impairment. The primary outcome was SE occurrence. Following matching, 17 738 patients were on CGRP inhibitors and 18 594 were not. SE occurred in 427 (2.41%) and 860 (4.63%) patients, respectively. Mean age (±SD) was 48.4 ± 14.9 vs 48.9 ± 17.0 years. Risk difference was −2.2% (95% confidence interval [CI]: −2.6% to −1.8%, p < .001), risk ratio 0.52 (95% CI: 0.46–0.58), and odds ratio 0.51 (95% CI: 0.45–0.57). SE‐related hospital visits were significantly fewer in the CGRP inhibitor group ( t = −6.60, p < .001). CGRP inhibitor use was associated with reduced SE occurrence and hospitalization, supporting further investigation in patients with comorbid migraine and epilepsy.

Digital twins have rapidly entered healthcare discourse, accompanied by ambitious claims regarding personalization, prediction, and decision support. Originating in engineering domains characterized by well-observed, controllable, and mechanistically understood systems, the concept is increasingly being applied to biological, clinical, and organizational settings whose underlying assumptions differ substantially. As a result, the term now encompasses a heterogeneous collection of models, simulations, and artificial intelligence (AI) systems, often without clear specification of what is being represented, what can be inferred, or what actions can legitimately be justified.This review develops a scale-aware framework for evaluating healthcare digital twins. Through a structured analysis spanning cardiovascular disease, diabetes, Alzheimer's disease, maternal–fetal health, addiction, radiology, and hospital operations, we argue that the scientific validity and practical utility of a digital twin depend fundamentally on scale. As applications move from mechanistic physiological systems to individual patients, coupled human systems, sociotechnical settings, and healthcare organizations, the central challenges shift from model fidelity and state estimation to non-identifiability, behavioral adaptation, contested objectives, and governance.Across domains, recurring failure modes arise less from insufficient computational capability than from misalignment among state definitions, uncertainty representation, causal support, decision authority, and governance. We examine the roles of AI in state estimation, prediction, uncertainty quantification, and decision support while highlighting its limits in addressing poorly defined state spaces, non-identifiability, causal ambiguity, and normative questions regarding acceptable actions. We further argue that governance is not an external constraint but a foundational component of healthcare digital twins, shaping accountability, lifecycle oversight, data stewardship, and the legitimacy of decisions informed by digital twin outputs.This review reframes healthcare digital twins not as a single technology but as a family of computational representations whose validity depends on scale, context, purpose, and governance. Future progress will depend less on increasingly sophisticated models than on maintaining alignment among representation, evidence, intervention, and accountability, and on ensuring digital twin ambitions remain commensurate with the epistemic conditions and institutional constraints of the systems they seek to represent. Building on this analysis, the review offers complementary research roadmaps for AI and governance that emphasize explicit state semantics, uncertainty-aware inference, decision-centered evaluation, adaptive oversight, and governance-by-design.

Rationale: Seizure medication must be taken regularly to be effective; seizures often result from missed doses. Numerous barriers can delay people with epilepsy (PWE) from obtaining medication on time. Methods: Two surveys were designed, one for PWE and their caregivers and one for healthcare providers (HCPs). Surveys were delivered electronically and data analysis was descriptive. Results: Medication unavailability was the most common barrier reported. Additional barriers in order of decreasing frequency included: the message “too soon to refill,” insurance coverage, prescription delay, and cost. For non-active drivers, transportation was a barrier. Sequelae of delayed medication access included: stress, emergency medication utilization, and hospitalization. Access to seizure medications was recognized as a problem by 95% of HCP surveyed, most frequently attributed to insurance barriers and cost. Over 10% of HCP reported a patient death from a medication access issue. Conclusion: The American Epilepsy Society's Position Statement on medication access supports reducing obstacles that delay obtaining medication through a multifaceted approach. It recommends elimination of unnecessary regulatory barriers, cost containment and insurance reform, supply chain transparency, practice management guidance, and ongoing research.

Understanding the evolution of clinical tools and models of care is fundamental to advancing the field of epilepsy. The 2025 American Epilepsy Society Annual Course examined the expanding spectrum of epilepsy care through the integration of multispecialty collaboration, innovative diagnostic modalities, and surgical and nonsurgical therapeutic interventions. The course underscored significant global advancements in epilepsy research and practice. This comprehensive review synthesizes key educational insights from the program, offering a critical perspective on the ongoing transformation of epilepsy care.

Numerous factors including social determinants of health, knowledge gaps, economic challenges, workforce limitations, and health system deficiencies are associated with significant disparities in access to health care services and health outcomes for people with epilepsy (PWE). The American Epilepsy Society (AES) and the International League Against Epilepsy—North America (ILAE-NA) established a joint task force to explore and develop recommendations to address health care disparities experienced by PWE. The task force gathered foundational knowledge through meetings, public and patient organization comments and discussions to develop consensus recommendations. We enumerate the recommendations and discuss the rationale behind them to reduce disparities in epilepsy care through comprehensive research, inclusive clinical practices, robust advocacy, and targeted educational initiatives. While our recommendations are focused on the United States, we acknowledge that similar barriers and limitations exist for PWE globally and that these also need to be addressed within their local domains and with attention to unique factors therewithin.