Abstract Objective Mental health conditions often co‐occur with epilepsy, causing burden and stress beyond seizures. Some of these conditions can emerge early and even predate the onset of seizure and/or epilepsy diagnosis. This systematic review synthesizes evidence on mental health outcomes in adults with newly diagnosed epilepsy (NDE). Methods A systematic literature search was conducted up to September 2025. All quantitative studies were included without restriction to study types. Mental health outcomes included a board range of mood, anxiety, quality of life, and stigma as primary or secondary outcome measures that were assessed and reported using validated scales. Standard methodological procedures for literature search, data collection, assessment of risk of bias, and analysis were used based on the Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) 2020 guideline. Results Twenty‐one publications ( n = 4728 adults) across 10 countries were included, of which 12 (57%) showed low risk of bias. Methodological heterogeneity precluded meta‐analysis. Depressive and anxiety symptoms were the most frequently assessed, with 11%–50% (data from 14 papers) and 25%–35% (11 papers) of NDE screened positive on validated screening tools, respectively. Structured diagnostic tools in two papers revealed clinical depression in 2.9%–13.3% and anxiety/neurotic disorders in approximately one‐quarter of NDE. The prevalence of perceived stigma was reported in 25%–53% of NDE; quality of life was impaired by mood symptom, stigma, and role disability. Significance Mental health conditions impose a substantial early burden among adults with NDE. Managing this burden requires integrating routine screening into early care pathways as a first step, coupled with a tiered psychiatric diagnostic process. Psychoeducation on these mental health risks should also be integrated into epilepsy care to promote awareness and access to services.

OBJECTIVE:This study evaluated the performance of the ENCEVIS artificial intelligence (AI)-based algorithm as a screening tool to predict the presence of ictal and/or interictal epileptiform discharges (IEDs) in electroencephalography (EEG) recordings. METHODS:This prospective study was conducted from 2019 to 2023 at Khechinashvili University Hospital, Tbilisi. EEG recordings over 3 h were included; standard EEGs and recordings with EEG-negative seizures were excluded. Two independent EEG experts performed blinded visual analyses. In case of disagreement, a third neurophysiologist was consulted, and the final consensus served as the reference standard. ENCEVIS annotations were compared to this reference. RESULTS:A total of 267 EEG recordings were analyzed. Clinical events occurred in 54 patients (20.2%): 43 had epileptic seizures, 11 had nonepileptic events, and 2 had both. A total of 114 seizures were captured, of which ENCEVIS correctly detected 65 (sensitivity 57.0%, p > 0.05). Detection sensitivity varied by seizure type, FB-TCS bilateral and GTCS 100%, focal seizures with impaired consciousness 66.7% (median 50 s), for focal seizures with preserved consciousness 36.4% (median 28 s), and for tonic seizures 23.1% (median 11 s). Longer seizure duration was associated with higher detection rates. False positive seizure detection rate was 0.27/h. ENCEVIS detected at least one seizure in 42 of 43 seizure-positive recordings (97.7%). Specificity was 48.2%, a positive predictive value (PPV) of 26.6%, and a negative predictive value (NPV) of 99.1%. Performance for interictal detection demonstrated a sensitivity of 97.4%, a specificity of 40.2%, a PPV of 69.3%, and an NPV of 91.8%. SIGNIFICANCE:The ENCEVIS algorithm demonstrates high sensitivity in detecting EEG recordings with ictal and interictal epileptiform activity. However, its limited specificity necessitates neurophysiological review to validate positive findings. Its high NPV highlights ENCEVIS's potential as a prescreening tool for identifying EEG recordings without ictal or interictal abnormalities, thereby reducing the workload on neurophysiologists. PLAIN LANGUAGE SUMMARY:This study evaluated the ENCEVIS artificial intelligence (AI) algorithm as a tool to support electroencephalography (EEG) analysis in epilepsy care. Researchers analyzed 267 long-term EEG recordings and compared ENCEVIS results to expert neurophysiologists' evaluations. The algorithm showed high accuracy in detecting normal EEGs and most seizures, especially longer ones. It also performed well in identifying interictal epileptiform activity. However, ENCEVIS sometimes incorrectly annotated normal recordings as abnormal. While it cannot replace expert review, ENCEVIS may serve as a helpful screening tool to reduce the time experts spend reviewing EEGs without epileptic activity.

OBJECTIVES:To understand the extent to which women of childbearing age (WoCBA) are aware of the issues associated with epilepsy and pregnancy and identify unmet reproductive healthcare and information needs. METHODS:WoCBA with epilepsy completed a 34-question online survey (January to March 2021), including sections on demographics, clinical information, and access to reproductive health care. The survey was available in English, Croatian, Czech, Georgian, German, Italian, Polish, Russian and Spanish. RESULTS:Overall, 865 responses were received and included in the analysis. Most respondents were aged 20-39 years (77.0 %), were married (43.6 %) and 63.2 % had been diagnosed with epilepsy for more than 10 years. Over half of respondents (53.9 %) had previously been pregnant, with 75.5 % reporting that they took anti-seizure medication (ASMs) during pregnancy. Most (67.6 %) respondents had received information about epilepsy and pregnancy with 43.4 % of respondents receiving this information before their first pregnancy. Although 71.5 % found the information 'very helpful' or 'somewhat helpful', some respondents found the information frightening, confusing, or difficult to access. Most respondents (74.1 %) had been made aware of the risks of taking some ASMs while pregnant; 59.8 % had been advised to consider pregnancy planning, however, 52.7 % were not provided with information on contraception while taking ASMs. Over half (56.9 %) of respondents felt that clear and concise information was not available for women with epilepsy who were considering becoming pregnant. CONCLUSIONS:There is a need to improve education and support for WoCBA with epilepsy to help them with decision-making, planning and managing pregnancy.

Progressive myoclonic epilepsies (PMEs) are a diverse group of neurodegenerative disorders characterized by myoclonus, seizures, and progressive cognitive and motor decline. This report presents a case of a subtype of PME, autosomal dominant Kufs disease (NCL type 4) documented for the first time outside of North America or Western Europe. The patient had a six-year history of progressive epilepsy that was resistant to pharmacotherapy, followed by myoclonus, cerebellar dysfunction, and cognitive deterioration. The patient's family history revealed a similar syndrome in the mother, who passed away seven years after the onset of the disease. Genetic testing identified the heterozygous pathogenic variant NM_025219.2:c.344T > G (p.Leu115Arg) in the DNAJC5 gene. This case report broadens the geographic distribution of NCL type 4 and calls attention to the multifaceted diagnostic challenges posed by the condition.

The study's purpose was to assess the seizure detection performance of ENCEVIS 1.7, identify factors that may influence algorithm performance, and explore its potential for implementation and application in long-term video EEG monitoring units.The study included video-EEG recordings containing at least one epileptic seizure. Forty-three recordings, encompassing 112 seizures, were included in the analysis. True positive, false negative, and false positive seizure detections were defined. Factors that may influence algorithm performance were studied.ENCEVIS demonstrated an overall sensitivity of 71.2%, significantly higher (75.1%) in focal compared to generalized seizures (62%).Ictal patterns rhythmicity (rhythmic 59.4 %, arrhythmic 41.7 %), seizure duration (<10 sec 6.3 %, >60 sec. 63.9 % (p < 0.05)) and patient age (<18 years 39.5 %, >18 years 58.1 % (P < 0.05)) influenced ENCEVIS sensitivity. The coexistence of extracerebral signal changes did not influence sensitivity.ENCEVIS with 79.1% accuracy annotates at least one seizure in those recordings containing epileptic seizures.ENCEVIS seizure detection performance was reasonable for generalized/focal to bilateral tonic-clonic seizures and seizures with temporal lobe onset.Rhythmic ictal patterns, longer seizure duration, and adult age positively influenced algorithm performance.ENCEVIS can be a valuable tool for identifying recordings containing seizures and can potentially reduce the workload of neurophysiologists.

Insomnia is a common sleep disorder which has a 5–6% prevalence rate and shows high social impact. At least 10% of patients with insomnia will see a medical specialist. Hence, 20,000–40,000 people in Georgia require medical help for insomnia. Treatment of insomnia is very effective. Pharmacotherapy is common, but it is recognized that cognitive behavioral therapy (CBT) is a better choice, since it is safe for patients and shows sustainable improvement. CBT of insomnia is not currently available in Georgia.The aim of our study was to evaluate a Georgian version of an innovative, internet-delivered digital CBT (dCBT) for insomnia in terms of therapeutic efficacy, adherence, and ease of handling.The Georgian digital cognitive behavioral therapy for insomnia was developed as an analogue of Dutch dCBT “i-Sleep.” All online materials were made applicable for the Georgian population through translation, validation by translation back to the original language, and adaptation to the Georgian reality, in order to avoid linguistic, cultural, and social pitfalls.Fifty-two adult patients with insomnia were recruited for the study: 34 women and 18 men, aged 18–64 years (mean: 33.5 years). Inclusion criteria included: age over 18, access to internet, and sufficient skills to use electronic devices. The patients who were treated pharmacologically continued their usual medication and received dCBT in addition to this treatment. DCBT was guided by a therapist. Clinical efficacy was evaluated on the basis of Insomnia Severity Index (ISI), measured before the dCBT and one month after its completion.25 out of 52 patients (48%) completed a full dCBT course. Mean ISI in this group dropped from 22.88 to 8.24 (P < 0.01), showing significant therapeutic effect one month after CBT completion. 27 patients (52%) stopped treatment for various reasons at different stages of dCBT. Sixteen patients dropped out from the first module (31%). 7 patients older than 50 years encountered problems with handling electronic devices and the platform itself. 9 patients stopped therapy, showing bad adherence for different reasons, mostly related to finding the sessions time-consuming and being disappointed by the absence of immediate therapeutic effect. Eleven more patients (21%) stopped at sleep restriction, finding it difficult to accomplish sleep restriction-related tasks. In general, patients found dCBT quite comprehensive and easy to handle.This data suggests that the Georgian version of dCBT for insomnia is a promising therapeutic tool, comparable with international analogues in terms of efficacy and adherence. Further studies, involving a greater number of patients and long-term follow-up are required for the final assessment of therapeutic efficacy and sustainability of results.

We conducted a survey to assess public awareness of epilepsy and stigma expression in different social groups in Tbilisi, Georgia. Respondents were divided into those from a medical or paramedical background, those with a nonmedical professional background, and a group with unskilled workers or unemployed individuals. One thousand and sixteen people completed a Knowledge, Attitude and Perception questionnaire. Medical and paramedical professionals had a better general knowledge about epilepsy, its possible causes, and its nature, but their views on treatment and attitudes towards epilepsy were the same or worse when compared to the other groups. Of the respondent, 14% would not let their children play with people with epilepsy, and 75% would not allow their children to marry a person with epilepsy. Nearly a third of teachers considered epilepsy a psychiatric disorder. This suggests a high degree of stigma towards epilepsy in Georgia. Increasing awareness is crucial to ameliorate this.

Introduction: Data on the prevalence of epilepsy and the extent of its treatment gap are important for planning health care delivery for people with epilepsy. The prevalence of active epilepsy in Georgia prior to the social and political re-organization in the early 1990s was estimated at around 5.7 per 1000. Changes to the social structure of the country may have affected this. There is no previous estimate of the treatment gap.Methods: A door-to-door survey was carried out using a validated screening questionnaire to determine the prevalence of epilepsy and the extent of the treatment gap amongst a population of about 10,000 people in Tbilisi, the capital of Georgia. The diagnosis of epilepsy amongst those who screened positive was confirmed by a multidisciplinary team.Results: Lifetime prevalence was 11.4/1000. The prevalence of active epilepsy was estimated at 8.8/1000, and 5/1000 had seizures in the previous 12 months. About two thirds of people with active epilepsy had not received appropriate antiepileptic treatment in the month prior to the survey. 89% had focal epilepsy and two thirds had co-morbidity (neurological deficits, behavioral, psychiatric or somatic problems).Conclusion: The prevalence of epilepsy was higher than previously estimated and the treatment gap was substantial. Results should inform the planning of epilepsy care delivery in the country. (C) 2011 Elsevier B.V. All rights reserved.