Preliminary development and validation of the Indonesian Pediatric Epilepsy Questionnaire (INA-PEPSI) to determine epilepsy and distinguish focal and generalized epilepsy in infants and children with unprovoked seizure in low-resource settings.

OBJECTIVE: To outline the preliminary development and validation of a questionnaire for diagnosing epilepsy and distinguishing focal and generalized epilepsy among infants and children in Indonesia, where electroencephalography and pediatric neurologists are generally not available. METHODS: A 10-question questionnaire comprising of 43 items was developed through literature review and expert panel discussions. Then, the questionnaire was administered by pediatricians to 75 children aged 1 month to 18 years old presenting with >1 episode of unprovoked seizures at an interval of >24 h. Subsequently, the questionnaire was assessed for content validity with item-level and scale-level content validity indices and ratio, construct validity with item-total correlation tests, criterion validity with diagnostic parameter assessments, and inter-rater reliability using Cohen's kappa (κ) and internal consistency with Cronbach's alpha (α) coefficient. RESULTS: The questionnaire exhibited favorable internal validity and reliability in diagnosing epilepsy and distinguishing focal and generalized epilepsy, with excellent content (both indices and ratio at 1) and construct validity (rcount > rtable at p < 0.001), inter-rater reliability (κ = 0.86 and κ = 0.84), and internal consistency (α = 0.634 and α = 0.806). The questionnaire had a sensitivity and specificity of 96.4% (95%CI 89.1-99.5%) and 95.0% (79.5-99.6%) (area under the curve [AUC] 0.946 [0.900-0.992, p < 0.001]) in diagnosing epilepsy and 80.0% (57.4-95.7%) and 97.4% (89.7-99.2%) (AUC 0.889 [0.783-0.995, p < 0.001]) in distinguishing focal and generalized epilepsy, with a misdiagnosis rate of 4.0%. SIGNIFICANCE: The questionnaire shows promising potential in diagnosing epilepsy and distinguishing focal and generalized epilepsy. Further external validation studies in larger and more diverse populations are required to confirm our findings. PLAIN LANGUAGE SUMMARY: The diagnosis of epilepsy in children is challenging, particularly in resource-limited settings such as Indonesia, where advanced diagnostic tests and pediatric neurologists are scarce. The Indonesian Pediatric Epilepsy Questionnaire (INA-PEPSI) is designed to address these limitations by enabling healthcare professionals in Indonesia to diagnose epilepsy and classify its types without relying on advanced diagnostic tools. Although the questionnaire is still in the early stages of development and validation, this study demonstrates that the questionnaire exhibits good overall diagnostic performance in diagnosing epilepsy and distinguishing epilepsy types among Indonesian children.

EEG in focal and generalized epilepsies: Pearls and perils.

Correctly diagnosing and classifying seizures and epilepsies is vital to ensure a tailored approach to patients with epilepsy. The ILAE seizure classification consists of two main groups: focal and generalized. Establishing if a seizure is focal or generalized is essential to classify the epilepsy type and the epilepsy syndrome, providing more personalized treatment and counseling about prognosis. EEG is one of the most essential tools for this classification process and further localization of the epileptogenic focus. However, some EEG findings are misleading and may postpone the correct diagnosis and proper treatment. Knowing the most common EEG pitfalls in focal and generalized epilepsies is valuable for clinical practice, avoiding misinterpretations. Some atypical features can be challenging in focal epilepsies, such as secondary bilateral synchrony, focal epileptiform activity induced by hyperventilation and photic stimulation, and non-focal slowing. On the other hand, more than 60 % of persons with idiopathic generalized epilepsies have at least one type of atypical abnormality. In this manuscript, we describe and illustrate some of the most common EEG findings that can make even experienced epileptologists question not only where the epileptogenic focus is but also if the patient has focal or generalized epilepsy. This review summarizes the perils and provide some pearls to assist EEG readers.

A generalized seizure type: Myoclonic-to-tonic seizure.

BACKGROUND AND PURPOSE: To test the hypothesis that myoclonic seizures can evolve to tonic seizures, we documented the electroclinical features of this under-recognized seizure type. METHODS: We observed a distinct seizure pattern starting with myoclonus without returning to an interictal state, which subsequently evolved into generalized tonic seizures. The detailed symptomatic and electroencephalographic characteristics of this seizure were extracted, and the clinical manifestations, drug curative responses in patients with this seizure were reviewed and analyzed. RESULTS: The onset of all seizures was characterized by a preceding period of myoclonus and bursts of generalized spike or poly-spike slow wave discharges with high amplitude. This was closely followed by the occurrence of tonic seizures, which were distinguished by bursts of generalized fast activity at 10 Hz or higher frequency. This under-recognized seizure type has been designated as myoclonic-to-tonic (MT) seizure. The number of patients identified with MT seizures in this study was 34. The prevalence rate of MT seizures was found to be higher in males. While MT seizures typically included a tonic component, it should be noted that some patients experiencing this seizure type never presented with isolated tonic seizures. Generalized Epilepsy not further defined (GE) accounted for approximately one-third of the diagnosed cases, followed by Lennox-Gastaut syndrome and Epilepsy with Myoclonic-Atonic seizures. In comparison to other types of epilepsy, GE with MT seizures demonstrated a more favorable prognosis. CONCLUSIONS: The classification of myoclonic-to-tonic seizure represents a novel approach in comprehending the ictogenesis of generalized seizures and can provide valuable assistance to clinicians in epilepsy diagnosis.

Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

OBJECTIVE: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy. METHODS: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of (1) leave-one-patient-out cross-validation (LOPO CV) on GCS patients, (2) false alarm rate (FAR) testing on nonseizure patients, and (3) "fixed-and-frozen" prospective testing on a prospective patient cohort. Balanced accuracy, precision, sensitivity, and FAR were used to quantify the performance of the algorithm. Seizure onsets and offsets were determined by using video-electroencephalographic (EEG) monitoring. Feature importance was calculated as the mean decrease in Gini impurity during the LOPO CV testing. RESULTS: LOPO CV results showed balanced accuracy of .93 (95% confidence interval [CI] = .8-.98), precision of .68 (95% CI = .46-.85), sensitivity of .87 (95% CI = .62-.96), and FAR of .21/24 h (interquartile range [IQR] = 0-.90). Testing the algorithm on patients without seizure resulted in an FAR of .28/24 h (IQR = 0-.61). During the "fixed-and-frozen" prospective testing, two patients had three GCS, which were detected by the algorithm, while generating an FAR of .25/24 h (IQR = 0-.89). Feature importance showed that heart rate-based features outperformed accelerometer/gyroscope-based features. SIGNIFICANCE: Commercially available wearable digital watches that reliably detect GCS, with minimum false alarm rates, may overcome usage adoption and other limitations of custom-built devices. Contingent on the outcomes of a prospective phase 3 study, such devices have the potential to provide non-EEG-based seizure surveillance and forecasting in the clinical setting.

Déjà vu in idiopathic generalized epilepsy: A systematic review.

INTRODUCTION: Déjà vu (DV), a French term meaning "already seen," refers to inappropriate sensation of familiarity in the present moment, as if it had been experienced before without a specific recollection of when or where. Traditionally, DV has been closely associated with focal seizures originating from the medial temporal lobe. However, there are occasional reports of DV occurring in idiopathic generalized epilepsies (IGEs). The objective of our study was to assess the presence and frequency of DV in individuals with IGE. METHODS: We used the Preferred Reporting Items for Systematic Review and Meta-Analysis for protocols (PRISMA-P) and searched PubMed and Embase from January 2000 to July 2022. RESULTS: 5 studies were included with a total of 1177 IGE and 1026 with temporal lobe epilepsy (TLE) patients. The frequency of DV in IGE ranged from 0 to 11 %, and the average was 3 %, compared to 19.6 % in TLE. Broadly, 40 % of patients with IGE reported some type of aura. EEG correlation of DV in IGE was not appropriately evaluated in the studies. CONCLUSION: Clinicians should be aware that individuals with IGE may experience DV and other types of auras. Recognizing these auras is crucial in order to avoid misdiagnosing IGE as focal epilepsy. This is important to prevent unnecessary investigations and incorrect treatment decisions.

Construction and validation of an algorithm to separate focal and generalised epilepsy using clinical variables: A comparison of machine learning approaches.

PURPOSE: Epilepsy type, whether focal or generalised, is important in deciding anti-seizure medication (ASM). In resource-limited settings, investigations are usually not available, so a clinical separation is required. We used a naïve Bayes approach to devise an algorithm to do this, and compared its accuracy with algorithms devised by five other machine learning methods. METHODS: We used data on 28 clinical variables from 503 patients attending an epilepsy clinic in India with defined epilepsy type, as determined by an epileptologist with access to clinical, imaging, and EEG data. We adopted a machine learning approach to select the most relevant variables based on mutual information, to train the model on part of the data, and then to evaluate it on the remaining data (testing set). We used a naïve Bayes approach and compared the results in the testing set with those obtained by several other machine learning algorithms by measuring sensitivity, specificity, accuracy, area under the curve, and Cohen's kappa. RESULTS: The six machine learning methods produced broadly similar results. The best naïve Bayes algorithm contained eleven variables, and its accuracy was 92.2% in determining epilepsy type (sensitivity 92.0%, specificity 92.7%). An algorithm incorporating the best eight of these variables was only slightly less accurate - 91.0% (sensitivity 89.6%, and specificity 95.1%) - and easier for clinicians to use. CONCLUSION: A clinical algorithm with eight variables is effective and accurate at separating focal from generalised epilepsy. It should be useful in resource-limited settings, by epilepsy-inexperienced doctors, to help determine epilepsy type and therefore optimal ASMs for individual patients, without the need for EEG or neuroimaging.

Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures.

Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy diagnosis, but manual seizure classification is time-consuming and requires extensive expertise. This paper presents an automated multi-class seizure classification model using EEG signals from the Temple University Hospital Seizure Corpus ver. 1.5.2. 11 features including time-based correlation, time-based eigenvalues, power spectral density, frequency-based correlation, frequency-based eigenvalues, sample entropy, spectral entropy, logarithmic sum, standard deviation, absolute mean, and ratio of Daubechies D4 wavelet transformed coefficients were extracted from 10-second sliding windows across channels. The model combines multi-head self-attention mechanism with a deep convolutional neural network (CNN) to classify seven subtypes of generalized and focal epileptic seizures. The model achieved 0.921 weighted accuracy and 0.902 weighted F1 score in classifying focal onset non-motor, generalized onset non-motor, simple partial, complex partial, absence, tonic, and tonic-clonic seizures. In comparison, a CNN model without multi-head attention achieved 0.767 weighted accuracy. Ablation studies were conducted to validate the importance of transformer encoders and attention. The promising classification results demonstrate the potential of deep learning for handling EEG complexity and improving epilepsy diagnosis. This seizure classification model could enable timely interventions when translated into clinical practice.

Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs.

OBJECTIVE: Focal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. METHODS: 32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. RESULTS: We observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 - 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. CONCLUSIONS: All included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. SIGNIFICANCE: Our findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs.

Long-term prognosis of patients with photosensitive idiopathic generalized epilepsy.

OBJECTIVE: The long-term prognosis of photosensitive idiopathic generalized epilepsy (p-IGE) is generally considered favorable; however, its specific characteristics remain unclear. Our objective was to investigate the extended prognosis of p-IGE. METHODS: We analyzed the demographics, clinical, and electroencephalographic (EEG) data of consecutive patients who were diagnosed as having p-IGE, who were under follow-up for a minimum of 10 years and exhibited a photoparoxysmal response (PPR) in their EEGs. Prognostic data, epilepsy course types, and electroclinical variables were compared using appropriate statistical methods. RESULTS: The mean follow-up duration for 108 consecutive patients with p-IGE (74.1 % female) was 16.8 ± 6.5 years. The main syndromes within this cohort included juvenile myoclonic epilepsy (37 %), juvenile absence epilepsy (15.7 %), and epilepsy with eyelid myoclonia (EEM) (14.8 %). In terms of epilepsy course types, 27.8 % were in the relapse-remission group, and 13.9 % had never experienced remission. A low early remission rate (5.6 %) was evident, with the remaining half of the cohort categorized as the late remission group. Several significant poor prognostic factors were identified including self-induction, clinical symptoms accompanying PPR, asynchrony and focal findings in EEG discharges, a wide frequency range of PPR, the coexistence of three seizure types, the presence of accompanying focal seizure features, and a history of convulsive status epilepticus. CONCLUSIONS: Our long-term follow-up study, conducted within a substantial p-IGE group, unveiled newly proposed course types within this epilepsy category and highlighted significant poor prognostic factors related to photosensitivity. These findings furnish valuable insights for precise prognosis counselling and effective management strategies for patients with p-IGE.

Drug-resistant generalized epilepsies: Revisiting the frontiers of idiopathic generalized epilepsies.

The 2017 International League Against Epilepsy (ILAE) classification suggested that the term "genetic generalized epilepsies" (GGEs) should be used for the broad group of epilepsies with so-called "generalized" seizure types and "generalized" spike-wave activity on EEG, based on a presumed genetic etiology. Within this framework, idiopathic generalized epilepsies (IGEs) are described as a subset of GGEs and include only four epileptic syndromes: childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, and epilepsy with generalized tonic-clonic seizures alone. The recent 2022 ILAE definition of IGEs is based on the current state of knowledge and reflects a community consensus and is designed to evolve as knowledge advances. The term "frontiers of IGEs" refers to the actual limits of our understanding of these four syndromes. Indeed, among patients presenting with a syndrome compatible with the 2022 definition of IGEs, we still observe a significant proportion of patients presenting with specific clinical features, refractory seizures, or drug-resistant epilepsies. This leads to the discussion of the boundaries of IGEs and GGEs, or what is accepted within a clinical spectrum of a definite IGE. Here, we discuss several entities that have been described in the literature for many years and that may either constitute rare features of IGEs or a distinct differential diagnosis. Their recognition by clinicians may allow a more individualized approach and improve the management of patients presenting with such entities.

Epilepsy with eyelid myoclonia (Jeavons syndrome): Generalized, focal, or combined generalized and focal epilepsy syndrome?

Epilepsy with eyelid myoclonia (EM) or Jeavons syndrome (JS) is an epileptic syndrome related to the spectrum of genetic generalized epilepsies (GGE). We report two untreated children on which EEGs were performed several hours after a generalized tonic-clonic seizure (GTCS). These showed a unilateral, nearly continuous posterior slowing. This slow-wave activity was associated with contralateral epileptiform activity in one case, while in the second case, it was associated with an ipsilateral activity. However, in the latter child, a few months later an independent focus on the contralateral side was observed. A diagnosis of focal occipital lobe epilepsy was proposed in both cases, and one child underwent a left occipital lobectomy at 3.5 years of age. Despite surgery, absences with EM persisted in this child, and a marked photosensitivity to photic stimulation was observed two years later. The focal slow wave activity of one occipital lobe several hours after a GTCS in these two subjects was in favor of a focal onset preceding the generalization. The EEG evidence for independent left and right posterior focus in these two cases, the persistence of EM, and the development of a marked photosensitivity to photic stimulation in the child who underwent an occipital lobectomy, allow us to suggest that JS is associated with a network of bi-occipital hyperexcitability that rapidly engages bilaterally to produce generalized seizures.

Resting-state brain activity distinguishes patients with generalised epilepsy from others.

PURPOSE: Epilepsy is a prevalent neurological disorder characterised by repetitive seizures. It is categorised into three types: generalised epilepsy (GE), focal epilepsy (FE), and combined generalised and focal epilepsy. Correctly subtyping the epilepsy is important to select appropriate treatments. The types are mainly determined (i.e., diagnosed) by their semiologies supported by clinical examinations, such as electroencephalography and magnetoencephalography (MEG). Although these examinations are traditionally based on visual inspections of interictal epileptic discharges (IEDs), which are not always visible, alternative analyses have been anticipated. We examined if resting-state brain activities can distinguish patients with GE, which would help us to diagnose the type of epilepsy. METHODS: The 5 min resting-state brain activities acquired using MEG were obtained retrospectively from 15 patients with GE. The cortical source of the activities was estimated at each frequency band from delta to high-frequency oscillation (HFO). These estimated activities were compared with reference datasets from 133 healthy individuals and control data from 29 patients with FE. RESULTS: Patients with GE showed larger theta in the occipital, alpha in the left temporal, HFO in the rostral deep regions, and smaller HFO in the caudal ventral regions. Their area under the curves of the receiver operating characteristic curves was around 0.8-0.9. The distinctive pattern was not found for data from FE. CONCLUSION: Patients with GE show distinctive resting-state brain activity, which could be a potential biomarker and used complementarily to classical analysis based on the visual inspection of IEDs.

Focal electroclinical features in generalized tonic-clonic seizures: Decision flowchart for a diagnostic challenge.

OBJECTIVE: Bilateral tonic-clonic seizures with focal semiology or focal interictal electroencephalography (EEG) can occur in both focal and generalized epilepsy types, leading to diagnostic errors and inappropriate therapy. We investigated the prevalence and prognostic values of focal features in patients with idiopathic generalized epilepsy (IGE), and we propose a decision flowchart to distinguish between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal EEG or semiology. METHODS: We retrospectively analyzed video-EEG recordings of 101 bilateral tonic-clonic seizures from 60 patients (18 with IGE, 42 with focal epilepsy). Diagnosis and therapeutic response were extracted after ≥1-year follow-up. The decision flowchart was based on previous observations and assessed concordance between interictal and ictal EEG. RESULTS: Focal semiology in IGE was observed in 75% of seizures and 77.8% of patients, most often corresponding to forced head version (66.7%). In patients with multiple seizures, direction of head version was consistent across seizures. Focal interictal epileptiform discharges (IEDs) were observed in 61.1% of patients with IGE, whereas focal ictal EEG onset only occurred in 13% of seizures and 16.7% of patients. However, later during the seizures, a reproducible pattern of 7-Hz lateralized ictal rhythm was observed in 56% of seizures, associated with contralateral head version. We did not find correlation between presence of focal features and therapeutic response in IGE patients. Our decision flowchart distinguished between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal features with an accuracy of 96.6%. SIGNIFICANCE: Focal semiology associated with bilateral tonic-clonic seizures and focal IEDs are common features in patients with IGE, but focal ictal EEG onset is rare. None of these focal findings appears to influence therapeutic response. By assessing the concordance between interictal and ictal EEG findings, one can accurately distinguish between focal and generalized epilepsies.

Idiopathic Generalized Epilepsy: Misunderstandings, Challenges, and Opportunities

The idiopathic generalized epilepsies (IGE) make up a fifth of all epilepsies, but <1% of epilepsy research. This skew reflects misperceptions: diagnosis is straightforward, pathophysiology is understood, seizures are easily controlled, epilepsy is outgrown, morbidity and mortality are low, and surgical interventions are impossible. Emerging evidence reveals that patients with IGE may go undiagnosed or misdiagnosed with focal epilepsy if EEG or semiology have asymmetric or focal features. Genetic, electrophysiologic, and neuroimaging studies provide insights into pathophysiology, including overlaps and differences from focal epilepsies. IGE can begin in adulthood and patients have chronic and drug-resistant seizures. Neuromodulatory interventions for drug-resistant IGE are emerging. Rates of psychiatric and other comorbidities, including sudden unexpected death in epilepsy, parallel those in focal epilepsy. IGE is an understudied spectrum for which our diagnostic sensitivity and specificity, scientific understanding, and therapies remain inadequate.

Epilepsy with generalized tonic-clonic seizures alone: Electroclinical features and prognostic patterns.

OBJECTIVE: Epilepsy with generalized tonic-clonic seizures alone (GTCA) is a common but poorly characterized idiopathic generalized epilepsy (IGE) syndrome. Hence, we investigated electroclinical features, seizure outcome, and antiseizure medication (ASM) withdrawal in a large cohort of GTCA patients. METHODS: In this multicenter retrospective study, GTCA patients defined according to the diagnostic criteria of the International League Against Epilepsy (2022) were included. We investigated prognostic patterns, drug resistance at the last visit, and ASM withdrawal, along with their prognostic factors. RESULTS: We included 247 patients with a median (interquartile range [IQR]) age at onset of 17 years (13-22) and a median follow-up duration of 10 years (IQR = 5-20). Drug resistance at the last visit was observed in 40 (16.3%) patients, whereas the median latency to achieve 2-year remission was 24 months (IQR = 24-46.5) with a median number of 1 (IQR = 1-2) ASM. During the long-term follow-up (i.e., 202 patients followed ≥5-years after the first ASM trial), 69 (34.3%) patients displayed an early remission pattern and 36 (17.9%) patients displayed a late remission pattern, whereas 16 (8%) and 73 (36.3%) individuals had no-remission and relapsing-remitting patterns, respectively. Catamenial seizures and morning predominance of generalized tonic-clonic seizures (GTCS) independently predicted drug resistance at the last visit according to multivariable logistic regression. Treatment withdrawal was attempted in 63 (25.5%) patients, with 59 (93.7%) of them having at least a 12-month follow-up after ASM discontinuation. At the last visit, 49 (83%) of those patients had experienced GTCS recurrence. A longer duration of seizure freedom was the only factor predicting a higher chance of successful ASM withdrawal according to multivariable Cox regression. SIGNIFICANCE: GTCA could be considered a relatively easily manageable IGE syndrome, with a low rate of drug resistance and a high prevalence of early response to treatment. Nevertheless, a considerable proportion of patients experience relapsing patterns of seizure control, highlighting the need for appropriate counseling and lifestyle recommendations.

Prenatal diagnosis of developmental and epileptic encephalopathy 9 with a 10.05-Mb microdeletion at Xq21.31q22.1 inherited from mother: A case report and literature review.

BACKGROUND: Developmental and epileptic encephalopathy 9 (DEE9) is characterized by early infantile seizures and mild-to-severe neuropsychiatric symptoms. Despite being an X-linked dominant disorder, DEE9 mainly affects heterozygous females or mosaic males, while hemizygous males are less affected. PCDH19 gene has been documented as the causative gene. METHODS: Karyotyping analysis and copy number variation sequencing (CNV-seq) were performed on a pregnant woman with epilepsy, together with her husband, son, and fetus. RESULTS: A disease-causing microdeletion, seq[GRCh37] del(X)(q21.31q22.1) (90310001-100360000), was identified in the pregnant woman and her female fetus. The microdeletion includes the entire PCDH19 gene and is classified as "pathogenic" according to the American College of Medical Genetics and Genomics guidelines. CONCLUSION: In this case study, we have not only identified the epilepsy type of the woman as DEE9 but have also made an unfavorable prognosis for her fetus. Our findings from this prenatal case provide valuable clinical resources for prenatal diagnosis and genetic counseling, while also implying the potential of CNV-seq as a viable method for uncovering PCDH19-related epilepsy.

Juvenile idiopathic epilepsy in Egyptian Arabian foals, a potential animal model of self-limited epilepsy in children.

BACKGROUND: Juvenile idiopathic epilepsy (JIE) is categorized as a generalized epilepsy. Epilepsy classification entails electrocortical characterization and localization of epileptic discharges (ED) using electroencephalography (EEG). HYPOTHESIS/OBJECTIVES: Characterize epilepsy in Egyptian Arabian foals with JIE using EEG. ANIMALS: Sixty-nine foals (JIE, 48; controls, 21). METHODS: Retrospective study. Inclusion criteria consisted of Egyptian Arabian foals: (1) JIE group diagnosed based on witnessed or recorded seizures, and neurological and EEG findings, and (2) control group of healthy nonepileptic age-matched foals. Clinical data were obtained in 48 foals. Electroencephalography with photic stimulation was performed under standing sedation in 37 JIE foals and 21 controls. RESULTS: Abnormalities on EEG were found in 95% of epileptic foals (35 of 37) and in 3 of 21 control asymptomatic foals with affected siblings. Focal ED were detected predominantly in the central vertex with diffusion into the centroparietal or frontocentral regions (n = 35). Generalization of ED occurred in 14 JIE foals. Epileptic discharges commonly were seen during wakefulness (n = 27/37 JIE foals) and sedated sleep (n = 35/37 JIE foals; 3/21 controls). Photic stimulation triggered focal central ED in 15 of 21 JIE foals. CONCLUSIONS AND CLINICAL IMPORTANCE: Juvenile idiopathic epilepsy has a focal onset of ED at the central vertex with spread resulting in clinical generalized tonic-clonic seizures with facial motor activity and loss of consciousness. Electroencephalography with photic stimulation contributes to accurate phenotyping of epilepsy. Foals with this benign self-limiting disorder might serve as a naturally occurring animal model for self-limited epilepsy in children.

Coexistence of temporal lobe epilepsy and idiopathic generalized epilepsy.

OBJECTIVE: We investigated the frequency of coexistence of temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) in a retrospective database study. We also explored the underlying pathomechanisms of the coexistence of TLE and IGE based on the available information, using bioinformatics tools. METHODS: The first phase of the investigation was a retrospective study. All patients with an electro-clinical diagnosis of epilepsy were studied at the outpatient epilepsy clinic at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2023. In the second phase, we searched the following databases for genetic variations (epilepsy-associated genetic polymorphisms) that are associated with TLE or syndromes of IGE: DisGeNET, genome-wide association study (GWAS) Catalog, epilepsy genetic association database (epiGAD), and UniProt. We also did a separate literature search using PubMed. RESULTS: In total, 3760 patients with epilepsy were registered at our clinic; four patients with definitely mixed TLE and IGE were identified; 0.1% of all epilepsies. We could identify that rs1883415 of ALDH5A1, rs137852779 of EFHC1, rs211037 of GABRG2, rs1130183 of KCNJ10, and rs1045642 of ABCB1 genes are shared between TLE and syndromes of IGE. CONCLUSION: While coexistence of TLE and IGE is a rare phenomenon, this could be explained by shared genetic variations.

Idiopathic generalized epilepsy with phantom absences, absence status, and generalized tonic-clonic seizures: A case report.

RATIONALE: Phantom absences refer to mild and short-lasting absence seizures, which are usually accompanied by infrequent generalized tonic-clonic seizures and absence status. Generally, phantom absences do not impair the individual neurological functions. Herein, we report the case of a young woman with idiopathic generalized epilepsy, phantom absences, absence status, and generalized tonic-clonic seizures. PATIENT CONCERNS: A 31-year-old woman presented with a 16-year history of paroxysmal convulsions. DIAGNOSES: Electroencephalogram (EEG) showed recurrent universal and synchronized 3~4 Hz spike waves and spike-slow waves in the interictal phase with normal background activity. During the ictal phases, EEG revealed bursts of 3~4 Hz spike waves and spike-slow waves that were universal, synchronized, and symmetrical. Additionally, there was 1 seizure episode induced by a 3-Hz flash in the current case. Based on these findings, a diagnosis of idiopathic generalized epilepsy was made. INTERVENTIONS: The patient was treated with oral sodium valproate, and the epileptic seizures were controlled. OUTCOMES: The frequency of absence seizures was significantly reduced and there were no generalized tonic-clonic seizures. LESSONS: Idiopathic generalized epilepsy with phantom absences, absence status, and generalized tonic-clonic seizures is an extremely rare condition. EEG is the exclusive method for diagnosis. Antiepileptic drugs are effective for controlling epileptic seizures in this disease.