Short-term exposure to air pollution has previously been studied in relation to certain neurological disorders, but there is still a lack of convincing data linking air pollution to epileptic seizures. The study\'s goal was to investigate how exposure to ambient nitrogen dioxide (NO2) affected the number of patients seeking assistance at the Wuhan Emergency Medical Center due to epileptic seizures. We gathered data on medical emergency calls (MECs), daily ambient air pollution concentrations (SO2, NO2, PM2.5, PM10, CO, and O3), and meteorological variables in Wuhan, China, spanning from January 1, 2017, to November 30, 2019. To investigate the potential influence of ambient nitrogen dioxide on MECs for epileptic seizures, we carried out a time-series investigation using the general additive model (GAM). Additionally, analyses stratified by season, age, and gender were performed. A total of 8989 records of MECs for epileptic seizures were enrolled in our study during the period. Statistical analysis indicates that a rise of 10 μg/m3 in NO2 concentration is linked to a 0.17% increase in daily MECs for epileptic seizures (95% confidence interval [CI]: 0.02%, 0.32%). Furthermore, people aged 14-59 years were more susceptible(2.25%, P < 0.05). The short-term effects of NO2 exposure on daily MECs for epileptic seizures were stronger in warm seasons than in cool seasons (0.55% vs. -0.10%, P < 0.0001). Our findings suggests that short-term exposure to ambient NO2 was positively correlated with daily MECs for epileptic seizures in Wuhan, China. Additionally, we observed that these associations were stronger in patients aged above 14 but under 60 years and the warmer seasons (from April to September).

UNASSIGNED: Idiopathic epilepsy (IE) and meningoencephalomyelitis of unknown origin (MUO) are common causes of brain diseases leading to seizures in dogs. In this study, the concentrations of 196 lipid metabolites and nitrogen oxide (NO) production in the cerebrospinal fluid (CSF) and plasma of dogs with MUO or IE were measured using a LC-MS/MS and a NOx analyzer, respectively.
UNASSIGNED: Nine clinically healthy dogs and 11 and 12 dogs with IE and MUO, respectively, were included in the study.
UNASSIGNED: Lipid analysis revealed variations in the levels of four and six lipid metabolites in CSF and plasma, respectively, between the groups. The levels of 6-keto-prostaglandin (PG) F1α (PGF1α), 20-carboxy arachidonic acid (20-carboxy-AA), 9-hydroxyoctadecadienoic acid, and lyso-platelet-activating factor were high in the CSF of dogs with MUO. In addition, the plasma levels of 11,12-dihydroxyeicosatrienoic acid, 20-carboxy-AA, and oleoylethanolamide were high in dogs with IE, and those of PGF1α were high in dogs with MUO. NO production levels were high in CSF but not in plasma in dogs with MUO or IE.
UNASSIGNED: It remains unknown whether these changes represent the cause or effect of diseases of the central nervous system; however, lipid metabolites and NO production in CSF and plasma may be used as diagnostic biomarkers and could be exploited for treating idiopathic or inflammatory epilepsy in dogs.

OBJECTIVE: As the clinical differentiation between epileptic seizures, psychogenic non-epileptic seizures (PNES), and syncope depends mainly on a detailed report of the event, which may not be available, an objective assessment of a potential biochemical analysis is needed. We aimed to investigate whether serum creatine kinase (CK) could be used to differentiate epileptic seizure from PNES and syncope and to assess the strength of evidence present.
METHODS: We directed a retrospective cohort study coupled with a systematic review and meta-analysis of studies that measured CK in patients with epilepsy, PNES, syncope, and healthy controls.
RESULTS: The cohort study, which traced 202 patients, showed that the CK level was significantly higher 48 h after the event in the epilepsy group versus patients with syncope (p < 0.01) Along with 1086 patients obtained through a database search for meta-analysis, CK level compared to different types of seizures from PNES was higher in epileptic seizure patients with a mean difference of 568.966 mIU/ml (95% CI 166.864, 971.067). The subgroup analysis of CK showed that it was higher in GTCS compared to syncope with a mean difference of 125.39 mIU/ml (95% CI 45.25, 205.52).
CONCLUSIONS: Increased serum levels of CK have been associated mainly with epileptic seizures in relation to non-epileptic events. However, further studies would try to explore the variation in measurements and any other potential diagnostic marker.
CONCLUSIONS: The cohort study shows that the CK level in epilepsy seizures is higher after 48 h from the event compared to syncope. Moreover, the meta-analysis results show the present diagnostic utility of CK and its importance to be used in accordance with a detailed report of the event.

Around one-third of epilepsy patients develop drug-resistant seizures; early detection of seizures could help improve safety, reduce patient anxiety, increase independence, and enable acute treatment. In recent years, the use of artificial intelligence techniques and machine learning algorithms in different diseases, including epilepsy, has increased significantly. The main objective of this study is to determine whether the mjn-SERAS artificial intelligence algorithm developed by MJN Neuroserveis, can detect seizures early using patient-specific data to create a personalized mathematical model based on EEG training, defined as the programmed recognition of oncoming seizures before they are primarily initiated, usually within a period of a few minutes, in patients diagnosed of epilepsy. Retrospective, cross-sectional, observational, multicenter study to determine the sensitivity and specificity of the artificial intelligence algorithm. We searched the database of the Epilepsy Units of three Spanish medical centers and selected 50 patients evaluated between January 2017 and February 2021, diagnosed with refractory focal epilepsy who underwent video-EEG monitoring recordings between 3 and 5 days, a minimum of 3 seizures per patient, lasting more than 5 s and the interval between each seizure was greater than 1 h. Exclusion criteria included age <18 years, intracranial EEG monitoring, and severe psychiatric, neurological, or systemic disorders. The algorithm identified pre-ictal and interictal patterns from EEG data using our learning algorithm and was compared to a senior epileptologist\'s evaluation as a gold standard. Individual mathematical models of each patient were trained using this feature dataset. A total of 1963 h of 49 video-EEG recordings were reviewed, with an average of 39.26 h per patient. The video-EEG monitoring recorded 309 seizures as subsequently analyzed by the epileptologists. The mjn-SERAS algorithm was trained on 119 seizures and split testing was performed on 188 seizures. The statistical analysis includes the data from each model and reports 10 false negatives (no detection of episodes recorded by video-EEG) and 22 false positives (alert detected without clinical correlation or abnormal EEG signal within 30 min). Specifically, the automated mjn-SERAS AI algorithm achieved a sensitivity of 94.7% (95 %; CI 94.67-94.73), and an F-Score representing specificity of 92.2% (95 %; CI 92.17-92.23) compared to the reference performance represented by a mean (harmonic mean or average) and a positive predictive value of 91%, with a false positive rate of 0.55 per 24 h in the patient-independent model. This patient-specific AI algorithm for early seizure detection shows promising results in terms of sensitivity and false positive rate. Although the algorithm requires high computational requirements on specialized servers cloud for training and computing, its computational load in real-time is low, allowing its implementation on embedded devices for online seizure detection.

BACKGROUND:  ​​Epilepsy is one of the most common neurological disorders in the pediatric age group, and teachers have a crucial role in providing appropriate epilepsy first aid. This study aims to assess the knowledge of and attitude toward epilepsy and seizure first aid among male teachers in the Mecca region, Saudi Arabia.
METHODS:  This cross-sectional study used an online self-administered questionnaire. A 22-item questionnaire was distributed via social media platforms between November 18, 2021, and February 15, 2022. The study used descriptive statistics to describe the participants\' characteristics, and relations were tested using the Pearson chi-square test.
RESULTS:  Of 385 male teachers, approximately two-thirds (57.9%) of teachers had poor knowledge of epilepsy and its first aid, 86.5% of teachers were aware that epilepsy is a neurological disorder, 67% correctly reported that during epileptic seizures, they should ensure the patient\'s safety and seek help, 37.7% of teachers knew when they should transfer the students to the hospital, and 45.3% who had a positive attitude towards children with epilepsy had good knowledge regarding the disease (P=.010). Only 13% had training on how to deal with seizures.
CONCLUSIONS: Overall knowledge of epilepsy and its first aid among schoolteachers in Mecca is still inadequate. It necessitates the inclusion of a nationwide, specialized educational epilepsy program into the teacher training curriculum.

Epileptic seizures during non-ketotic hyperglycemia (NKH) represent a rare complication of uncontrolled diabetes mellitus. The definition associates a blood sugar level > 200mg/dL (11mmol/L), hyperosmolality, absence of ketosis, dehydration and seizure control after normalization of blood sugar levels.
This retrospective observational study included patients hospitalized for epileptic seizures and NKH in the Cayenne Hospital Center between January 2010 and June 2020. The clinical, biological, and radiological results were collected.
18 out of 228 (7.9%) patients with both diabetes and epileptic seizures had NKH. The mean age of the 12 women and 6 men was 64.8 years. In 8 patients, brain imaging did not show acute lesions and the seizures disappeared with control of hyperglycemia by hydration and insulin. In 6 patients, the seizures revealed a stroke, hemorrhagic in 4 cases, ischemic in 2 cases. 4 patients had a seizure in a context of known vascular epilepsy. The epileptic seizures were mainly focal seizures with motor symptoms that could be repeated, focal to bilateral tonic-clonic or focal status.
Seizures in NKH are symptomatic of an acute brain lesion or vascular epilepsy more than 1 in 2 times. However, isolated NKH can cause seizures with a suggestive brain MRI.

UNASSIGNED: Ictal semiology is a fundamental part of the presurgical evaluation of patients with temporal lobe epilepsy. We aimed to identify different anatomical and semiologic subgroups in temporal lobe seizures, and investigate the correlation between them.
UNASSIGNED: We enrolled 93 patients for whom stereoelectroencephalography exploration indicated that the seizure-onset zone was within the temporal lobe. Ictal signs and concomitant stereoelectroencephalography changes were carefully reviewed and quantified, and then cluster analysis and the Kendall correlation test were used to associate ictal signs with the temporal structures of patients.
UNASSIGNED: Clustering analysis identified two main groups of temporal structures. Group 1 consisted of the medial temporal lobe structures and the temporal pole, which were divided into two subgroups. Group 1A included the hippocampal head, hippocampal body, and amygdala, and this subgroup correlated significantly with oroalimentary automatisms, feeling of fear, and epigastric auras. Group 1B included the hippocampal tail, temporal pole, and parahippocampal gyrus, and this subgroup correlated significantly with manual and oroalimentary automatisms. Group 2 consisted of the cortical structures of the temporal lobe and was also divided into two subgroups. Group 2A included the superior and middle temporal gyrus, correlated significantly with bilateral rictus/facial contraction, generalized tonic-clonic seizure, and manual automatisms. Group 2B included Heschl\'s gyrus, the inferior temporal gyrus, and the fusiform gyrus, and this subgroup correlated significantly with auditory auras, focal hypokinetics, unilateral upper and lower limbs tonic posture/clonic signs, head/eye deviation, unilateral versive signs, and generalized tonic-clonic seizure.
UNASSIGNED: The temporal structures can be categorized according to the level at which each structure participates in seizures, and different anatomical subgroups can be correlated with different ictal signs. Identifying specific semiologic features can help us localize the epileptogenic zone and thus develop stereoelectroencephalography electrode implantation and surgical resection protocols for patients with temporal lobe epilepsy.

UNASSIGNED: Epilepsy is a neurological disorder characterized by a persistent propensity to generate recurring epileptic seizures. Young adults such as university students can bridge the gap and improve attitudes toward patients with epilepsy and reduce stigma. This study aims to assess the knowledge and attitude of university students in the city of Makkah about epilepsy.
UNASSIGNED: This cross-sectional descriptive study was carried out at main universities in the Makkah region of Saudi Arabia. The study was conducted after getting approval from Umm Al-Qura University\'s ethics and research committee. A total of 394 participants were enrolled in the study, and a stratified random sampling (probability sampling) technique was used to select respondents.
UNASSIGNED: The study included students with a mean age of 20.9 ± 4.6 (18-28 years), 271 (68.8%) students were females, 374 (94.9%) of the students agreed that epilepsy is not contagious, and 215 (54.6%) refused the impact of epilepsy on patients\' marital status, relationships and fertility, respectively, 213 (54.1%) of the students reported that they feel scared to witness a seizure. About 334 (84.8%) respondents believed that epilepsy is an affliction, and 123 (31.2%) reported that they thought epilepsy was a supernatural phenomenon or black magic.
UNASSIGNED: The study concluded a satisfactory level of awareness among university students in Makkah related to dealing with patients with epilepsy. Further scientific studies will help build student\'s positive attitudes through simulation programs and interventional studies.

BACKGROUND: Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was declared a pandemic on March 11th, 2020, by the World Health Organization (WHO). There has been a substantial increase in the epileptic seizures and status epilepticus reported in the pandemic period. In this context, it is aimed with this study to identify the electroencephalography (EEG) features of patients admitted to the intensive care unit with the diagnosis of COVID-19 and to look for any specific patterns in these features.
METHODS: The material of this study primarily comprised the neurological evaluations and continuous EEG recordings of 87 intensive care patients who were diagnosed with COVID-19. In addition, demographic and clinical features and comorbid conditions of these patients were also analyzed, and any correlation thereof was investigated.
RESULTS: The EEG data of 87 patients who were diagnosed with COVID-19 and were followed up in the intensive care unit were recorded and then analyzed. Abnormal EEG findings were detected in 93.1% (n = 81) of the patients, which were found to increase significantly with age (p < 0.001). The mean age of patients with specific epileptiform abnormalities on EEG was found to be significantly higher than those with non-specific abnormalities. Epileptiform discharges were seen in 37.9% (n = 33) of the patients. Nonconvulsive status epilepticus (NCSE) was detected in 5.7% of the patients, and antiepileptic drugs were started in 25 (28.7%) of the patients.
CONCLUSIONS: Statistically significant EEG changes were observed in the continuous EEGs of the patients followed up in the intensive care unit due to COVID-19 infection. However, further studies are needed to associate the EEG changes observed in the COVID-19 patients with the epileptogenesis of COVID-19 infection.

Driving is a critical topic to counsel among patients with epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES), with significant legal and public health implications. This prospective cohort study examined the frequency of ES and PNES in a single institution\'s Epilepsy Monitoring Unit (EMU) and assessed driving-related issues between each group.
Adult patients from the Mayo Clinic Arizona Epilepsy Monitoring Unit (EMU) were given comprehensive surveys addressing driving history. Descriptive analysis and statistics were used to summarize differences between patients with ES and PNES. Differences between patients with epilepsy and PNES were determined by Pearson chi-square.
Nearly half (n = 75/163) of all patients admitted to the EMU were diagnosed with PNES. Although the PNES group had a statistically significant higher frequency of events (p = 0.01), 87.7% of these patients reported compliance with the driving law recommendations, suggesting a trend that patients who have been counseled regarding fitness-to-drive are likely to follow the recommendation. One-third of patients with PNES reported an event while operating a motor vehicle and 8% (n = 2/25) resulted in a motor vehicle collision severe enough to require hospitalization. In contrast to those with ES, 25% of patients reported a typical event while driving and 25% (n = 2/8) of those resulted in a collision requiring hospitalization. The incidence of habitual events while driving is higher in the population with PNES (n = 25) when compared to those with ES (n = 8); however, it appears that patients with PNES were less likely to become involved in an accident resulting in seriously bodily injury than in ES.
Compared to patients with PNES, patients with ES have less frequent events but more severe collisions. This study reinforces the need for diligent driving counseling to help prevent driving-related injuries in patients with PNES and ES.