Stroke and Ischemic Heart Disease With Enzyme-inducing Antiseizure Medications: Time to Change Prescribing Habits

Importance: Enzyme-inducing antiseizure medications (eiASMs) have been hypothesized to be associated with long-term risks of cardiovascular disease. Objective: To quantify and model the putative hazard of cardiovascular disease secondary to eiASM use. Design, Setting, and Participants: This cohort study covered January 1990 to March 2019 (median [IQR] follow-up, 9 [4–15], years). The study linked primary care and hospital electronic health records at National Health Service hospitals in England. People aged 18 years or older diagnosed as having epilepsy after January 1, 1990, were included. All eligible patients were included with a waiver of consent. No patients were approached who withdrew consent. Analysis began January 2021 and ended August 2021. Exposures: Receipt of 4 consecutive EI ASMs (carbamazepine, eslicarbazepine, oxcarbazepine, phenobarbital, phenytoin, primidone, rufinamide, or topiramate) following an adult-onset (age >/=18 years) epilepsy diagnosis or repeated exposure in a weighted cumulative exposure model. Main Outcomes and Measures: Three cohorts were isolated, 1 of which comprised all adults meeting a case definition for epilepsy diagnosed after 1990, 1 comprised incident cases diagnosed after 1998 (hospital linkage date), and 1 was limited to adults diagnosed with epilepsy at 65 years or older. Outcome was incident cardiovascular disease (ischemic heart disease or ischemic or hemorrhagic stroke). Hazard of incident cardiovascular disease was evaluated using adjusted propensity-matched survival analyses and weighted cumulative exposure models. Results: Of 10,916,166 adults, 50,888 (.6%) were identified as having period-prevalent cases (median [IQR] age, 32 [19–50] years; 16 584 [53%] female), of whom 31,479 (62%) were diagnosed on or after 1990 and were free of cardiovascular disease at baseline. In a propensity-matched Cox proportional hazards model adjusted for age, sex, baseline socioeconomic status, and cardiovascular risk factors, the hazard ratio for incident cardiovascular disease was 1.21 (95% CI, 1.06–1.39) for those receiving eiASMs. The absolute difference in cumulative hazard diverges by more than 1% and greater after 10 years. For those with persistent exposure beyond 4 prescriptions, the median hazard ratio increased from a median (IQR) of 1.54 (1.28–1.79) when taking a relative defined daily dose of an eiASM of 1 to 2.38 (1.52–3.56) with a relative defined daily dose of 2 throughout a maximum of 25 years' follow-up compared with those not receiving an eiASM. The hazard was elevated but attenuated when restricting analyses to incident cases or those diagnosed when older than 65 years. Conclusions and Relevance: The hazard of incident cardiovascular disease is higher in those receiving eiASMs. The association is dose dependent and the absolute difference in hazard seems to reach clinical significance by approximately 10 years from first exposure.

Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future

Artificial intelligence (AI) is increasingly used in medical image analysis and has accelerated scientific discoveries across fields of medicine. In this review, we highlight how AI has been applied to neuroimaging in patients with epilepsy to enhance classification of clinical diagnosis, prediction of treatment outcomes, and the understanding of cognitive comorbidities. We outline the strengths and shortcomings of current AI research and the need for future studies using large datasets that test the reproducibility and generalizability of current findings, as well as studies that test the clinical utility of AI approaches.

Epilepsy Research Now in 3D: Harnessing the Power of Brain Organoids in Epilepsy

Brain organoids represent a powerful tool for studying human neurological diseases, particularly those that affect brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes, raising the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network-level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network dynamics reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from induced pluripotent stem cells from individuals with Rett syndrome, accompanied by transcriptomic differences revealed by single-cell analyses. We also rescue key physiological activities with an unconventional neuroregulatory drug, pifithrin-α. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.