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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. [ABSTRACT FROM AUTHOR]

Objective: Epilepsy is a neurological disease that affects ~50 million people worldwide, 30% of which have refractory epilepsy and recurring seizures, which may contribute to higher anxiety levels and poorer quality of life. Seizure detection may contribute to addressing some of the challenges associated with this condition, by providing information to health professionals regarding seizure frequency, type, and/or location in the brain, thereby improving diagnostic accuracy and medication adjustment, and alerting caregivers or emergency services of dangerous seizure episodes. The main focus of this work was the development of an accurate video‐based seizure‐detection method that ensured unobtrusiveness and privacy preservation, and provided novel approaches to reduce confounds and increase reliability. Methods: The proposed approach is a video‐based seizure‐detection method based on optical flow, principal component analysis, independent component analysis, and machine learning classification. This method was tested on a set of 21 tonic–clonic seizure videos (5–30 min each, total of 4 h and 36 min of recordings) from 12 patients using leave‐one‐subject‐out cross‐validation. Results: High accuracy levels were observed, namely a sensitivity and specificity of 99.06% ± 1.65% at the equal error rate and an average latency of 37.45 ± 1.31 s. When compared to annotations by health care professionals, the beginning and ending of seizures was detected with an average offset of 9.69 ± 0.97 s. Significance: The video‐based seizure‐detection method described herein is highly accurate. Moreover, it is intrinsically privacy preserving, due to the use of optical flow motion quantification. In addition, given our novel independence‐based approach, this method is robust to different lighting conditions, partial occlusions of the patient, and other movements in the video frame, thereby setting the base for accurate and unobtrusive seizure detection. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Cerebrovascular disease is the leading cause of epilepsy in adults, although post-stroke seizures reported frequency is variable and few studies used EEG in their identification. To describe and compare EEG and clinical epileptic manifestations frequency in patients with an anterior circulation ischaemic stroke. Prospective study of acute anterior circulation ischaemic stroke patients, consecutively admitted to a Stroke Unit over 24 months and followed-up for 1 year. All patients underwent standardized clinical and diagnostic assessment. Seizure occurrence was clinically evaluated during hospitalization and by a telephone interview at 6 months and a clinical appointment at 12 months after stroke. Video-EEG was performed in the first 72 h (1st EEG), daily after the 1st EEG for the first 7 days after the stroke, or later if neurological worsening, at discharge, and at 12 months. 151 patients were included (112 men) with a mean age of 67.4 (11.9) years. In the 1st year after stroke, 38 patients (25.2%) had an epileptic seizure. During hospitalization, 27 patients (17.9%) had epileptiform activity (interictal or ictal) in the EEG, 7 (25.9%) of them electrographic seizures. During the first week after stroke, 22 (14.6%) patients had a seizure and 4 (2.6%) non-convulsive status epilepticus criteria. Five (22.7%) acute symptomatic seizures were exclusively electrographic. At least one remote symptomatic seizure occurred in 23 (16%) patients. In the first 7 days after stroke, more than one-fifth of patients with seizures had exclusively electrographic seizures. Without a systematic neurophysiological evaluation the frequency of post-stroke seizures are clinically underestimated. [ABSTRACT FROM AUTHOR]

Mesial temporal lobe seizures can be misdiagnosed as panic attacks. There is a spectrum of symptoms that are common to both, like fear sensation. We report a case of a young woman, initially diagnosed as having panic attacks of short duration. The symptoms persisted for two years despite treatment with SSRIs. Epileptic seizures were suggested when the patient started reporting involuntary limb movements during some of the episodes. Further investigations showed mesial temporal sclerosis on MRI and epileptic activity in EEG, and she began antiepileptic treatment. In some patients with panic attacks, particularly if associated with atypical features, the possibility of epilepsy should be considered. [ABSTRACT FROM AUTHOR]

Seizures are not only a frequent complication of stroke but have been associated with an unfavorable functional and vital outcome of patients who have had stroke. Facing a new paradigm of acute standard stroke care, acute symptomatic seizures in this clinical setting deserve to be rethought. Reperfusion therapies, the gold standard treatment for acute ischemic stroke, improve long-term survival and outcome of patients who have had stroke and have been associated both with clinical seizures and the occurrence of epileptiform activity in the electroencephalogram (EEG). This narrative review describes the different physiopathological mechanisms underlying the possible association between reperfusion therapies and seizures, both acute symptomatic seizures and unprovoked seizures, and the current evidence regarding the risk of poststroke seizures in treated patients. It also identifies the gaps in our knowledge to foster future studies in this field. By different mechanisms, reperfusions therapies may have opposing effects on the risk of poststroke seizures. There is a need for a better definition of the specific physiopathology of seizures in clinical practice, as many factors can be recognized. Additionally, most of the current clinical evidence refers to acute symptomatic seizures and not to unprovoked seizures or poststroke epilepsy, and our analysis does not support the existence of a strong association between thrombolysis and poststroke seizures. So far, the impact of reperfusion therapies on the frequency of poststroke seizures is unclear. To study this effect, many clinical challenges must be overcome, including a better and clear operational definition of seizures and stroke characteristics, the standard of stroke and epilepsy care and EEG monitoring, and the degree of reperfusion success. Prospective, high quality, larger, and longer follow-up multicentric studies are urgently needed. Additionally, stroke registries can also prove useful in better elucidate whether there is an association between reperfusion therapies and seizures. This article is part of the Special Issue "Seizures & Stroke". • In animal models, thrombolysis seems to affect the risk of poststroke seizures. • Different mechanisms have opposing effects on the risk of poststroke seizures. • Clinical evidence does not support an association between reperfusion therapies and seizures. [ABSTRACT FROM AUTHOR]