Colin A. Ellis

Background: SLC7A6OS c.191A>G is a rare, autosomal recessive cause of progressive myoclonus epilepsy (PME). The c.191A>G variant, first discovered in two families from Türkiye and Portugal, was recently identified in three additional probands from the USA, all of Puerto Rican ancestry. Objectives: We sought to refine the SLC7A6OS ‐PME phenotype and determine whether all families inherited the variant from the same common ancestor. Methods: Clinical and genotyping data were obtained from all five families. Haplotype analysis using single nucleotide polymorphism arrays to investigate a possible common ancestor was performed. Results: Shared haplotypes suggest all five families inherited the SLC7A6OS variant from a common ancestor approximately 1100 years ago. Subsequent dating estimates were consistent with migration patterns between the eastern Mediterranean, Iberia, and Puerto Rico. Conclusions: Our findings strengthen the previous evidence for SLC7A6OS as a cause of PME and highlight a founder effect in regions with migratory links to Iberia. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Background: In glioblastoma, tumor-related epilepsy (TRE) is paradoxically associated with longer survival, but the mechanism is unclear. We hypothesized that structural connectivity is associated with seizure susceptibility and survival, and tested whether these associations are independent or mediated. Methods: We retrospectively studied glioblastoma patients with preoperative diffusion-weighted MRI. Fractional anisotropy-weighted connectivity matrices were constructed using lesion-aware tractography. Mean edge weight and local efficiency were computed per Yeo 7-network and with global efficiency at hemisphere and whole-brain levels. Associations with TRE, overall survival (OS), and progression-free survival (PFS) were assessed using logistic regression and Cox proportional hazards models with false discovery rate correction. Causal mediation analysis tested whether connectivity and TRE mediate each other’s relationship with overall survival. Results: We included 420 glioblastoma patients. Of 406 classifiable for TRE, 217 (53%) had TRE. TRE was associated with higher local efficiency across all seven contralateral networks ( d= 0.42-0.49, q< 0.010) and five of seven ipsilateral networks ( d =0.44-0.49, q< 0.050). In adjusted models, higher contralateral global efficiency was associated with longer OS (HR 0.84, q= 0.021), with no metric associated with PFS. TRE did not mediate the connectivity-OS relationship. Contralateral local efficiency partially mediated the TRE-OS association when postoperative KPS was excluded from the model (ACME 16.6 days, 7.8% mediated, p =0.029), though this was attenuated when KPS was included ( p =0.074). Conclusions: Structural connectivity may partially mediate the seizure-survival association, suggesting preserved network architecture may contribute to longer survival in glioblastoma patients with TRE, though most of the effect operates through other pathways. Key Points: Tumor-related epilepsy in glioblastoma was associated with relatively greater structural connectivity. Higher contralateral global efficiency related to longer overall survival. Contralateral local efficiency may partly mediate the seizure-survival link. Importance of the Study: Seizures in glioblastoma are paradoxically associated with longer survival, yet the biological basis of this relationship has remained unknown. Using lesion-aware diffusion tractography in 420 patients, we found that the same structural network measures relate to both seizure susceptibility and survival. Patients with tumor-related epilepsy had relatively greater white matter connectivity, and higher contralateral connectivity was independently associated with longer overall survival. Causal mediation analysis showed that connectivity accounted for a small fraction of the seizure-survival association, suggesting that seizures mark, rather than confer, the survival advantage, and that both may reflect a shared upstream driver not captured here. These findings identify structural connectivity as a shared correlate and candidate imaging biomarker for seizure risk and prognosis in glioblastoma.

Background and ObjectivesInpatient video-EEG epilepsy monitoring aims to provide a safe environment for antiseizure medication (ASM) tapering to precipitate seizures, which is often required for di...

Objective: Genetic testing has become a routine part of clinical epilepsy care. Family history is an indication for genetic testing, but the diagnostic yield, predictors of a genetic diagnosis, and association with familial patterns are not well understood. Methods: This was a retrospective cohort study of genetic testing performed at pediatric and adult epilepsy genetics clinics. Eligible patients (probands) had epilepsy and one or more first‐degree relatives or two or more other relatives with epilepsy. Genetic testing strategies were patient specific, reflecting real‐world clinical practice. Familial patterns were classified based on affected relatives of the proband. Diagnostic variants were tested in the proband's parents when possible. Results: We studied 484 probands and their families. A genetic diagnosis was identified in 99 of 484 (20%). Predictors of a genetic diagnosis were presence of neurodevelopmental disorder ( X ² (1) = 9.6, p = .002) and earlier age at seizure onset (Mann–Whitney U test, p < .001). The likelihood of a genetic diagnosis was not associated with epilepsy type, drug resistance, brain magnetic resonance imaging (MRI) findings, number of affected first‐degree relatives, total number of affected relatives, or having an affected parent with epilepsy. Among those with genetic diagnoses, variant segregation matched the familial pattern of affected individuals in 79%. The other 21% of families had unexpected segregation, including de novo variants in patients with affected ancestors and inherited variants in patients with no known affected ancestors. Significance: Familial epilepsy has a substantial rate of genetic diagnosis and is an appropriate indication for genetic testing. Pedigree‐related factors did not influence the likelihood of genetic diagnosis, suggesting that all families can be considered for genetic testing, independent of inheritance patterns and number of affected relatives. Familial patterns can help interpret genetic test results, while also revealing the complexities of incomplete penetrance and independent epilepsy etiologies in families.

Background: Hospitalized patients often experience poor sleep, which is associated with worse health outcomes, increased rates of delirium, and readmissions. Objective: To improve overnight sleep for clinically stable general neurology patients at a single academic center. Methods: We conducted a quasi‐experimental pre‐post clinical trial of two sleep‐protective interventions: (1) a sleep‐friendly order set that reduced overnight interruptions by discontinuing vital sign checks/neurological examinations and retiming medications/blood draws; and (2) a “sleep menu” of comfort items. The primary outcome measure was sleep duration. Secondary outcomes were awakenings and patient responses to the Richards‐Campbell Sleep Questionnaire. Safety outcomes were rates of delirium, ICU transfers, and 30‐day readmissions. We compared the groups using linear mixed‐effects models to account for repeated measures (multiple nights per participant). Results: We analyzed data from 66 pre‐intervention participants (238 nights) and 61 post‐intervention participants (244 nights). The interventions did not increase sleep duration (pre‐intervention median 5.5 h [interquartile range (IQR) 4.0,6.6], post‐intervention median 5.4 h [4.1, 6.7], p = .84). There was marginal improvement in nightly awakenings (pre‐intervention 2 [1, 4], post‐intervention 2 [1, 3], p = .04). There were no significant differences in subjective sleep measures or safety outcomes. Targeted care team interruptions all significantly decreased post‐intervention, though staff intrusions remained a common patient‐reported barrier to sleep. Conclusion: Fragmented and reduced sleep was common in our general neurology population. Although our interventions did not improve sleep outcomes—apart from a modest drop in nocturnal awakenings—there was a significant decrease in care team interruptions. Poor inpatient sleep is multifactorial, and meaningful change likely requires comprehensive interventions.

This review provides an overview of the emergence and application of transformer-based language models in electronic health records in neurology. Transformer architectures are well-suited for neurological data due to their ability to model complex spatiotemporal patterns and capture long-range dependencies, both characteristic of neurological conditions and their documentation. We introduce the foundational principles of transformer models and outline the model training and evaluation frameworks commonly used in clinical text processing. We then examine current applications of transformers in neurology, spanning disease detection and diagnosis, phenotyping and symptom extraction, and outcome and prognosis prediction, and synthesize emerging patterns in model adaptation and evaluation strategies. Additionally, we discuss the limitations of current models, including generalizability, model bias, and data privacy, and propose future directions for research and implementation. By synthesizing recent advances, this review aims to guide future efforts in leveraging transformer-based language models to improve neurological care and research.

Hemiplegic migraine presents as recurrent episodes of migraine with associated unilateral weakness. Patients can present with more severe paroxysmal episodes of encephalopathy. Treatment varies widely and it is not standardized. Despite the growing understanding of genetic causes of hemiplegic migraine, pathogenic variants in SLC4A4 are the only described etiology with recessive inheritance. Better understanding of the various genetic causes and associated symptoms of hemiplegic migraine would allow more personalized treatments leading to a reduction in morbidity. This case describes a 34-year-old patient with episodes of hemiplegic migraine and paroxysmal encephalopathy who was found to have homozygous SLC4A4 pathogenic variants. It describes his initial renal and ocular dysfunction in childhood followed by hemiplegic migraine in adolescence and episodes of encephalopathy in adulthood. In his most recent presentation, the patient improved after initiation of high-volume bicarbonate repletion and steroids. SLC4A4 pathogenic variants are associated with a multiorgan syndrome in which neurologic symptoms typically develop in adolescence or young adulthood. Common symptoms include hemiplegic migraine and paroxysmal attacks of acute encephalopathy. In this case, there was improvement with initiation of steroids despite no evidence of cerebral edema. Furthermore, rapid correction of pH and volume status additionally contributed to clinical improvement. Recognizing the diverse set of genetic causes of hemiplegic migraine and the evolution of symptoms over time can lead to improved diagnosis and identification of appropriate treatment strategies.

Sleep is a critical component of health and recovery. Awakening sleeping patients for routine vital sign monitoring overnight is a common inpatient practice, but its benefits are uncertain. This study asked 3 questions: (1) How often are routine overnight vital signs abnormal? (2) How often are those abnormal vital signs clinically actionable? (3) Are there patients who may not need routine overnight vital sign monitoring? We analyzed observational retrospective data extracted from electronic health records of patients admitted to inpatient neurology floors at our institution between 2017 and 2024. We defined routine vital signs as collected by nursing assistants at least 3 hours apart. The outcome measure was an urgent clinical action (stat orders, rapid responses, or transfers to a higher level of care) within 1 hour of vital sign events. We compared the rate of urgent clinical actions after abnormal vital signs with the base rate of those events after normal vital signs. Statistical analysis used generalized estimating equations to account for repeated measures. We analyzed 102,184 routine vital sign events from 5,569 neurology admissions. In total, 9% of vital sign events were abnormal. The likelihood of urgent clinical actions increased after abnormal vital sign events, compared with after normal vital sign events during the day (4.3% vs 2.4%, odds ratio (OR) 1.8 [1.6-2.1]); at night (2.4% vs 0.9%, OR 2.8 [2.2-3.7]); during the night in low-risk patients with normal daytime vitals (2.0% vs 0.7%, OR 3.0 [1.8-4.9]); and at night in high-risk patients with abnormal daytime vitals (2.6% vs 1.1%, OR 2.5 [1.7-3.6]). The number needed to treat (NNT), i.e., the number of vital sign events needed to initiate 1 extra urgent clinical action above the base rate, was 1,856 [943; 4,598] in low-risk patients. The NNT for low-risk stroke patients was 1,570 [679; 4,707] and for general neurology patients was 2,231 [797; 5,423]. Urgent clinical actions attributable to abnormal routine vital signs were uncommon in neurology inpatients, especially overnight in patients with normal daytime vital signs. Determining the risks and benefits of routine overnight vital sign monitoring will help hospitals and health care providers move toward more patient-centered inpatient neurologic care.