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Electroencephalography (EEG) can identify biomarkers of epileptogenesis and ictogenesis. However, few studies have used EEG in the prediction of poststroke seizures. Our primary aim was to evaluate whether early EEG abnormalities can predict poststroke epilepsy. A prospective study of consecutive acute anterior circulation ischemic stroke patients, without previous epileptic seizures, who were admitted to a stroke unit over 24 months and followed for 1 year. All patients underwent standardized clinical and diagnostic assessment during the hospital stay and after discharge. Video-EEG was performed in the first 72 h (first EEG), daily for the first 7 days, in case of neurological deterioration, at discharge, and at 12 months after stroke. The occurrence of epileptic seizures in the first year after stroke (primary outcome) was evaluated clinically and neurophysiologically during the hospital stay and at 12 months. A telephone interview was also performed at 6 months. The primary outcome was the occurrence of at least one unprovoked seizure (poststroke epilepsy). Secondary outcomes were the occurrence of at least one acute symptomatic seizure and (interictal and/or ictal) epileptiform activity on at least one EEG during the hospital stay for acute stroke. The first EEG variables were defined using international criteria/terminology. Bivariate and multivariate analyses with adjustment for age, admission National Institutes of Health Stroke Scale (NIHSS) score, and Alberta Stroke Program Early CT Score (ASPECTS) were performed. A total of 151 patients were included; 38 patients (25.2%) had an acute symptomatic seizure and 23 (16%) had an unprovoked seizure.The first EEG background activity asymmetry and first EEG with interictal epileptiform activity were independent predictors of poststroke epilepsy during the first year after stroke ( = 0.043 and = 0.043, respectively). No EEG abnormality independently predicted acute symptomatic seizures. However, the presence of periodic discharges on the first EEG was an independent predictor of epileptiform activity (p = 0.009) during the hospital stay. An early poststroke EEG can predict epilepsy in the first year after stroke, independently from clinical and imaging-based infarct severity.

There is currently no evidence to support the use of antiseizure medications to prevent unprovoked seizures following stroke. Experimental animal models suggested a potential antiepileptogenic effect for eslicarbazepine acetate (ESL), and a Phase II, multicenter, randomized, double‐blind, placebo‐controlled study was designed to test this hypothesis and assess whether ESL treatment for 1 month can prevent unprovoked seizures following stroke. We outline the design and status of this antiepileptogenesis study, and discuss the challenges encountered in its execution to date. Patients at high risk of developing unprovoked seizures after acute intracerebral hemorrhage or acute ischemic stroke were randomized to receive ESL 800 mg/d or placebo, initiated within 120 hours after primary stroke occurrence. Treatment continued until Day 30, then tapered off. Patients could receive all necessary therapies for stroke treatment according to clinical practice guidelines and standard of care, and are being followed up for 18 months. The primary efficacy endpoint is the occurrence of a first unprovoked seizure within 6 months after randomization (“failure rate”). Secondary efficacy assessments include the occurrence of a first unprovoked seizure during 12 months after randomization and during the entire study; functional outcomes (Barthel Index original 10‐item version; National Institutes of Health Stroke Scale); post‐stroke depression (Patient Health Questionnaire‐9; PHQ‐9); and overall survival. Safety assessments include the evaluation of treatment‐emergent adverse events; laboratory parameters; vital signs; electrocardiogram; suicidal ideation and behavior (PHQ‐9 question 9). The protocol aimed to randomize approximately 200 patients (1:1), recruited from 21 sites in seven European countries and Israel. Despite the challenges encountered, particularly during the COVID‐19 pandemic, the study progressed and included a remarkable number of patients, with 129 screened and 125 randomized. Recruitment was stopped after 30 months, the first patient entered in May 2019, and the study is ongoing and following up on patients according to the Clinical Trial Protocol.

The development of mobile health for epilepsy has grown in the last years, bringing new applications (apps) to the market and improving already existing ones. In this systematic review, we analyse the scope of mobile apps for seizure detection and epilepsy self-management, with two research questions in mind: what are the characteristics of current solutions and do they meet users’ requirements? What should be considered when designing mobile health for epilepsy? We used PRISMA methodology to search within App Store and Google Play Store from February to April of 2021, reaching 55 potential apps. A more thorough analysis regarding particular features was performed on 26 of those apps. The content of these apps was evaluated in five categories, regarding if there was personalisable content; features related to medication management; what aspects of seizure log were present; what type of communication prevailed; and if there was any content related to seizure alarm or seizure action plans. Moreover, the 26 apps were evaluated through using MARS by six raters, including two neurologists. The analysis of MARS categories was performed for the top and bottom apps, to understand the core differences. Overall, the lowest MARS scores were related to engagement and information, which play a big part in long-term use, and previous studies raised the concern of assuring continuous use, especially in younger audiences. With that in mind, we identified conceptual improvement points, which were divided in three main topics: customisation, simplicity and healthcare connection. Moreover, we summarised some ideas to improve m-health apps catered around long-term adherence. We hope this work contributes to a better understanding of the current scope in mobile epilepsy management, endorsing healthcare professionals and developers to provide off-the-shelf solutions that engage patients and allows them to better manage their condition.

Seizures and electroencephalographic (EEG) abnormalities have been associated with unfavorable stroke functional outcome. However, this association may depend on clinical and imaging stroke severity. We set out to analyze whether epileptic seizures and early EEG abnormalities are predictors of stroke outcome after adjustment for age and clinical/imaging infarct severity. A prospective study was made on consecutive and previously independent acute stroke patients with a National Institutes of Health Stroke Scale (NIHSS) score ≥ 4 on admission and an acute anterior circulation ischemic lesion on brain imaging. All patients underwent standardized clinical and diagnostic assessment during admission and after discharge, and were followed for 12 months. Video-EEG (<60 min) was performed in the first 72 h. The Alberta Stroke Program Early CT Score quantified middle cerebral artery infarct size. The outcomes in this study were an unfavorable functional outcome (modified Rankin Scale [mRS] ≥ 3) and death (mRS = 6) at discharge and 12 months after stroke. Unfavorable outcome at discharge was independently associated with NIHSS score (p = 0.001), EEG background activity slowing (p < 0.001), and asymmetry (p < 0.001). Unfavorable outcome 1 year after stroke was independently associated with age (p = 0.001), NIHSS score (p < 0.001), remote symptomatic seizures (p = 0.046), EEG background activity slowing (p < 0.001), and asymmetry (p < 0.001). Death in the first year after stroke was independently associated with age (p = 0.028), NIHSS score (p = 0.001), acute symptomatic seizures (p = 0.015), and EEG suppression (p = 0.019). Acute symptomatic seizures were independent predictors of vital outcome and remote symptomatic seizures of functional outcome in the first year after stroke. Therefore, their recognition and prevention strategies may be clinically relevant. Early EEG abnormalities were independent predictors and comparable to age and early clinical/imaging infarct severity in stroke functional outcome discrimination, reflecting the concept that EEG is a sensitive and robust method in the functional assessment of the brain.

Sleep-related eating disorder (SRED) is characterised by eating episodes during the first period of the night sleep with partial loss consciousness, and amnesia. It can rarely be induced by some drugs, including zolpidem. We present a video report of a patient with a 1-year history of SRED caused by zolpidem causing important repercussions in the sleep structure and life quality. The night eating episodes ceased promptly with discontinuation of zolpidem. Upon the follow-up, the sleep structure improved and the daily consequences disappeared. As in few reported cases of zolpidem-induced SRED, our patient was suffering from the parasomnia for a long time before the diagnosis. Active exclusion of symptoms suggestive of SRED in patients under zolpidem treatment can avoid the deleterious effect of the sleep disorder.

Stroke is the leading cause of seizures and epilepsy in older adults. Patients who have larger and more severe strokes involving the cortex, are younger, and have acute symptomatic seizures and intracerebral haemorrhage are at highest risk of developing post-stroke epilepsy. Prognostic models, including the SeLECT and CAVE scores, help gauge the risk of epileptogenesis. Early electroencephalogram and blood-based biomarkers can provide information additional to the clinical risk factors of post-stroke epilepsy. The management of acute versus remote symptomatic seizures after stroke is markedly different. The choice of an ideal antiseizure medication should not only rely on efficacy but also consider adverse effects, altered pharmacodynamics in older adults, and the influence on the underlying vascular co-morbidity. Drug–drug interactions, particularly those between antiseizure medications and anticoagulants or antiplatelets, also influence treatment decisions. In this review, we describe the epidemiology, risk factors, biomarkers, and management of seizures after an ischaemic or haemorrhagic stroke. We discuss the special considerations required for the treatment of post-stroke epilepsy due to the age, co-morbidities, co-medication, and vulnerability of stroke survivors.

Circadian rhythms (CRs) orchestrate intrinsic 24-hour oscillations which synchronize an organism's physiology and behaviour with respect to daily cycles. CR disruptions have been linked to Parkinson's Disease (PD), the second most prevalent neurodegenerative disorder globally, and are associated to several PD-symptoms such as sleep disturbances. Studying molecular changes of CR offers a potential avenue for unravelling novel insights into the PD progression, symptoms, and can be further used for optimization of treatment strategies. Yet, a comprehensive characterization of the alterations at the molecular expression level for core-clock and clock-controlled genes in PD is still missing. The proposed study protocol will be used to characterize expression profiles of circadian genes obtained from saliva samples in PD patients and controls. For this purpose, 20 healthy controls and 70 PD patients will be recruited. Data from clinical assessment, questionnaires, actigraphy tracking and polysomnography will be collected and clinical evaluations will be repeated as a follow-up in one-year time. We plan to carry out sub-group analyses considering several clinical factors (e.g., biological sex, treatment dosages, or fluctuation of symptoms), and to correlate reflected changes in CR of measured genes with distinct PD phenotypes (diffuse malignant and mild/motor-predominant). Additionally, using NanoString.sup.â multiplex technology on a subset of samples, we aim to further explore potential CR alterations in hundreds of genes involved in neuropathology pathways. CLOCK4PD is a mono-centric, non-interventional observational study aiming at the molecular characterization of CR alterations in PD. We further plan to determine physiological modifications in sleep and activity patterns, and clinical factors correlating with the observed CR changes. Our study may provide valuable insights into the intricate interplay between CR and PD with a potential to be used as a predictor of circadian alterations reflecting distinct disease phenotypes, symptoms, and progression outcomes.

Circadian rhythms (CRs) orchestrate intrinsic 24-hour oscillations which synchronize an organism's physiology and behaviour with respect to daily cycles. CR disruptions have been linked to Parkinson's Disease (PD), the second most prevalent neurodegenerative disorder globally, and are associated to several PD-symptoms such as sleep disturbances. Studying molecular changes of CR offers a potential avenue for unravelling novel insights into the PD progression, symptoms, and can be further used for optimization of treatment strategies. Yet, a comprehensive characterization of the alterations at the molecular expression level for core-clock and clock-controlled genes in PD is still missing. The proposed study protocol will be used to characterize expression profiles of circadian genes obtained from saliva samples in PD patients and controls. For this purpose, 20 healthy controls and 70 PD patients will be recruited. Data from clinical assessment, questionnaires, actigraphy tracking and polysomnography will be collected and clinical evaluations will be repeated as a follow-up in one-year time. We plan to carry out sub-group analyses considering several clinical factors (e.g., biological sex, treatment dosages, or fluctuation of symptoms), and to correlate reflected changes in CR of measured genes with distinct PD phenotypes (diffuse malignant and mild/motor-predominant). Additionally, using NanoString.sup.â multiplex technology on a subset of samples, we aim to further explore potential CR alterations in hundreds of genes involved in neuropathology pathways. CLOCK4PD is a mono-centric, non-interventional observational study aiming at the molecular characterization of CR alterations in PD. We further plan to determine physiological modifications in sleep and activity patterns, and clinical factors correlating with the observed CR changes. Our study may provide valuable insights into the intricate interplay between CR and PD with a potential to be used as a predictor of circadian alterations reflecting distinct disease phenotypes, symptoms, and progression outcomes.

Circadian rhythms (CRs) orchestrate intrinsic 24-hour oscillations which synchronize an organism's physiology and behaviour with respect to daily cycles. CR disruptions have been linked to Parkinson's Disease (PD), the second most prevalent neurodegenerative disorder globally, and are associated to several PD-symptoms such as sleep disturbances. Studying molecular changes of CR offers a potential avenue for unravelling novel insights into the PD progression, symptoms, and can be further used for optimization of treatment strategies. Yet, a comprehensive characterization of the alterations at the molecular expression level for core-clock and clock-controlled genes in PD is still missing. The proposed study protocol will be used to characterize expression profiles of circadian genes obtained from saliva samples in PD patients and controls. For this purpose, 20 healthy controls and 70 PD patients will be recruited. Data from clinical assessment, questionnaires, actigraphy tracking and polysomnography will be collected and clinical evaluations will be repeated as a follow-up in one-year time. We plan to carry out sub-group analyses considering several clinical factors (e.g., biological sex, treatment dosages, or fluctuation of symptoms), and to correlate reflected changes in CR of measured genes with distinct PD phenotypes (diffuse malignant and mild/motor-predominant). Additionally, using NanoStringⓇ multiplex technology on a subset of samples, we aim to further explore potential CR alterations in hundreds of genes involved in neuropathology pathways. CLOCK4PD is a mono-centric, non-interventional observational study aiming at the molecular characterization of CR alterations in PD. We further plan to determine physiological modifications in sleep and activity patterns, and clinical factors correlating with the observed CR changes. Our study may provide valuable insights into the intricate interplay between CR and PD with a potential to be used as a predictor of circadian alterations reflecting distinct disease phenotypes, symptoms, and progression outcomes.

This study aims to review the proposed methodologies and reported performances of automated algorithms for seizure forecast. A systematic review was conducted on studies reported up to May 10, 2024. Four databases and registers were searched, and studies were included when they proposed an original algorithm for automatic human epileptic seizure forecast that was patient specific, based on intraindividual cyclic distribution of events and/or surrogate measures of the preictal state and provided an evaluation of the performance. Two meta-analyses were performed, one evaluating area under the ROC curve (AUC) and another Brier Skill Score (BSS). Eighteen studies met the eligibility criteria, totaling 43 included algorithms. A total of 419 patients participated in the studies, and 19442 seizures were reported across studies. Of the analyzed algorithms, 23 were eligible for the meta-analysis with AUC and 12 with BSS. The overall mean AUC was 0.71, which was similar between the studies that relied solely on surrogate measures of the preictal state, on cyclic distributions of events, and on a combination of these. BSS was also similar for the three types of input data, with an overall mean BSS of 0.13. This study provides a characterization of the state of the art in seizure forecast algorithms along with their performances, setting a benchmark for future developments. It identified a considerable lack of standardization across study design and evaluation, leading to the proposal of guidelines for the design of seizure forecast solutions.