Sociodemographic and clinical risk factors for suicidal ideation and suicide attempt in functional/dissociative seizures and epilepsy: a large cohort study.

BACKGROUND: People with functional/dissociative seizures (FDS) are at elevated suicidality risk. OBJECTIVE: To identify risk factors for suicidality in FDS or epilepsy. METHODS: Retrospective cohort study from the UK's largest tertiary mental healthcare provider, with linked national admission data from the Hospital Episode Statistics. Participants were 2383 people with a primary or secondary diagnosis of FDS or epilepsy attending between 01 January 2007 and 18 June 2021. Outcomes were a first report of suicidal ideation and a first hospital admission for suicide attempt (International Classification of Diseases, version 10: X60-X84). Demographic and clinical risk factors were assessed using multivariable bias-reduced binomial-response generalised linear models. FINDINGS: In both groups, ethnic minorities had significantly reduced odds of hospitalisation following suicide attempt (OR: 0.45-0.49). Disorder-specific risk factors were gender, age and comorbidity profile. In FDS, both genders had similar suicidality risk; younger age was a risk factor for both outcomes (OR: 0.16-1.91). A diagnosis of depression or personality disorders was associated with higher odds of suicidal ideation (OR: 1.91-3.01). In epilepsy, females had higher odds of suicide attempt-related hospitalisation (OR: 1.64). Age had a quadratic association with both outcomes (OR: 0.88-1.06). A substance abuse disorder was associated with higher suicidal ideation (OR: 2.67). Developmental disorders lowered the risk (OR: 0.16-0.24). CONCLUSIONS: This is the first study systematically reporting risk factors for suicidality in people with FDS. Results for the large epilepsy cohort complement previous studies and will be useful in future meta-analyses. CLINICAL IMPLICATIONS: Risk factors identified will help identify higher-risk groups in clinical settings.

Dual diagnosis of epilepsy and dissociative seizures: Prescription patterns, feasibility and safety of rationalising antiseizure medication.

BACKGROUND: Patients with a dual-diagnosis of epilepsy and dissociative seizures (DS) have received far less attention than those with single pathology. Anti-seizure medication (ASM) prescription patterns and safety of rationalisation have not been reviewed. METHODS: We undertook a retrospective cohort study of all patients with a dual-diagnosis admitted to the Scottish Epilepsy Centre between 2012-2020. ASM frequencies were compared across admission, discharge and follow-up and emergency hospital attendances compared a year before and after admission. Demographic data, seizure characteristics and mortality data were also reviewed. RESULTS: Across the 139 patients included in our study, ASM frequency at follow-up was significantly lower than on admission (mean 2.51 vs 2.14, Z = -2.11 p = 0.035, r = -0.215). Total hospital attendances in the year following admission were significantly lower than in the year before (mean 1.27 vs 0.77, Z = 2.306, p = 0.021, r = -0.262). Those with inactive epilepsy had their medications reduced to a greater extent that those with active epilepsy. 44 patients had their ASM frequency reduced during admission with a similar trend of reduced hospital attendances (mean 1.29 vs 0.43 Z = -3.162 p = 0.002). There was one epilepsy related death. CONCLUSIONS: Clinicians should consider the development of co-morbid DS in patients with epilepsy not responding to an escalation of ASM, especially if presenting with a new seizure type. Patients with a dual-diagnosis of epilepsy and DS, particularly those with well controlled epilepsy, are likely overtreated with ASM. Medication review in a tertiary epilepsy centre allows for safe rationalisation of ASM and likely contributes to the need for fewer hospital attendances.

Structural and functional changes associated with functional/dissociative seizures: A review of the literature.

INTRODUCTION: The term 'functional/dissociative seizures (FDS)' refers to a paroxysmal, transient clinical manifestation that may include motor, sensory, vegetative, psychological and cognitive signs, similar to the manifestations observed in epileptic seizures. In recent years, there has been an increase of literature in the field of brain imaging research on functional neurological disorders and, more specifically, on FDS. However, most of the studies have been carried out on limited samples. We propose an update of this review work by performing a systematic review of studies performed since 2017 in the field of neuroimaging in patients with FDS. METHODS: We conducted a systematic review of the literature using the PRISMA methodology and reproduced most of the methodological elements of the latest systematic literature review. RESULTS: Our work over the last five years has identified 14 articles. It is still difficult to isolate a distinct structure or network specifically involved in the mechanism of FDS. However, certain structures are recurrently involved in imaging studies, notably the amygdala, the orbitofrontal cortex, and the anterior cingulate cortex. CONCLUSION: The contribution of neuroimaging may allow a more precise explanation of the disorder for patients, avoiding the stigma frequently associated with this diagnosis. as with other 'conversion' phenomena which have traditionally been considered only as 'medically unexplained'. In the longer term and beyond a better understanding of the physiopathology of the disorder, the challenge of this neuroimaging work would be to identify specific imaging biomarkers for a diagnosis of FDS.

An update on psychogenic nonepileptic seizures.

PURPOSE OF REVIEW: The understanding of psychogenic nonepileptic seizures (PNES) has advanced steadily over recent decades. This update summarizes new insights from the last three years. RECENT FINDINGS: The process of diagnosing PNES has shifted from the exclusion of epilepsy to one based on the recognition of typical clinical features. While the diagnosis cannot rely on any single feature in isolation, a range of semiological features characterising PNES are now recognised and a number of studies hint at the potential for machine learning and AI to improve the diagnostic process. Advances in data processing and analysis may also help to make sense of the heterogeneity of PNES populations demonstrated by recent studies focussing on aetiology and patient subgroups. It is now clear that PNES are associated with high rates of mental and physical comorbidities and premature death, highlighting that they are only one manifestation of a complex disorder extending beyond the nervous system and the seizures themselves. SUMMARY: PNES are now understood as a manifestation of dysfunction in interacting brain networks. This understanding provides an explanation for the psychopathological and semiological heterogeneity of PNES patient populations. New insights into medical comorbidities and increased rates of premature death call for more research into associated pathological processes outside the nervous system.

EEG microstates show different features in focal epilepsy and psychogenic nonepileptic seizures.

OBJECTIVE: Electroencephalography (EEG) microstate analysis seeks to cluster the scalp's electric field into semistable topographical EEG activity maps at different time points. Our study aimed to investigate the features of EEG microstates in subjects with focal epilepsy and psychogenic nonepileptic seizures (PNES). METHODS: We included 62 adult subjects with focal epilepsy or PNES who received video-EEG monitoring at the epilepsy monitoring unit. The subjects (mean age = 42.8 ± 21.2 years) were distributed equally between epilepsy and PNES groups. We extracted microstates from a 4.4 ± 1.0-min, 21-channel resting-state EEG. We excluded subjects with interictal epileptiform discharges during resting-state EEGs. After preprocessing, we derived five main EEG microstates-MS1 to MS5-for the full frequency band (1-30 Hz) and frequency subbands (delta, 1-4 Hz; theta, 4-8 Hz; alpha, 8-12 Hz; beta, 12-30 Hz), using the MATLAB-based EEGLAB toolkit. Statistical features of microstates (duration, occurrence, contribution, global field power [GFP]) were compared between the groups, using logistic regression corrected for age and sex. RESULTS: We detected no differences in microstate parameters in the full frequency band. We found a longer duration (delta: B = -7.680, p = .046; theta: B = -16.200, p = .043) and a higher contribution (delta: B = -7.414, p = .035; theta: B = -7.509, p = .031) of MS4 in lower frequency bands in the epilepsy group. The PNES group showed a higher occurrence of MS5 in the delta subband (B = 3.283, p = .032). In the theta subband, a higher GFP of MS1 was associated with the PNES group (B = 5.674, p = .025), whereas a higher GFP of MS2 was associated with the epilepsy group (B = -6.579, p = .026). SIGNIFICANCE: Microstate features show differences between patients with focal epilepsy and PNES. EEG microstates could be a promising parameter, helping to understand changes in brain dynamics in subjects with epilepsy, and should be explored as a potential biomarker.

Right temporoparietal junction transcranial direct current stimulation in the treatment of functional dissociative seizures: a case series.

Functional dissociative seizures (FDSs) are clinical events that resemble epileptic seizures but are not associated with abnormal brain electrical discharges or other physiological problems. In this pilot case series, ten adults with FDSs were recruited from our psychiatry department after being referred by a neurologist who made the diagnosis of FDS based on video EEG results. Each subject received ten sessions of cathodal tDCS focused on the right temporoparietal junction. A significant decrease in weekly seizure frequency was seen in all participants between baseline (30.2 ± 70.3 events) and 1 month after tDCS treatment (0.2 ± 0.3events) (p = 0.006). Main predisposing factors were unchanged after treatment.

Multidisciplinary Care May Help to Reduce Disparities Associated With Race in Youth With Psychogenic Nonepileptic Seizures.

BACKGROUND: Psychogenic nonepileptic seizures (PNES) are a common type of functional neurological disorder in which patients experience seizurelike episodes. Health disparities based on race and socioeconomics, documented in children with epilepsy and adults with PNES, have not been reported in children and adolescents with PNES. We hypothesize that disparities exist in this population, which impact overall care and therefore influence outcomes. METHODS: We retrospectively analyzed youth referred to our multidisciplinary clinic from 2018 to 2020. All patient charts were screened by social work before the visit to identify potential barriers to care, and a nurse conducted follow-up calls. Patients' race was identified from the electronic health record and compared with several variables. Outcomes were collected via phone follow-up. Descriptive statistics were produced, and comparisons between white patients and patients of other races were completed using Fisher exact tests and multivariable logistic regressions. RESULTS: During the study period, 237 patients were eligible for the analysis. Sixty-eight patients (29%) identified as a race other than white. Only 60%, 56%, and 40% of the cohort were reached for follow-up at one, three, and 12 months, respectively. In general, outcomes were similar between racial groups; however, we found that patients of nonwhite race were more likely to receive support from social work due to barriers identified in screening (P = 0.045). CONCLUSIONS: Health disparities based on race may exist in youth with PNES. A multidisciplinary clinic including social work may help mitigate barriers leading to more equitable care and similar outcomes for white and nonwhite youth with PNES.

Long-term course of psychogenic nonepileptic seizures: Who gets seizure-free, has better functional level and higher health-related quality of life?

BACKGROUND: The disease course of psychogenic nonepileptic seizures (PNES) over a prolonged period of time remains unclear. The aims of the study were: 1. to describe the course of illness with a median follow-up time of 4 years and a range of 2-15 years; and 2. to identify distinguishing features between participants regarding seizure cessation, functional level and health-related quality of life. METHODS: Formerly, inpatients of an epileptic ward diagnosed with PNES between 2000 and 2013 were contacted via mail. They were asked by questionnaire about illness characteristics, i.e., age at onset, PNES status at onset and in the course, treatments, psychosocial situation, and quality of life status. RESULTS: Two-thirds of the N = 63 formerly inpatients were female, their age at onset was 26.7 years. Seizure frequency decreased significantly over time, 31.7% were currently seizure-free, but still only 37% were regularly employed. Only 48% had a satisfying health-related quality of life. The remitted participants had a shorter duration of illness and higher health-related quality of life. Participants with a good level of functioning were more likely to be male, took fewer medications, and had a higher health-related quality of life. Those participants with higher quality of life were more frequently employed and had fewer seizures. CONCLUSIONS: As participants continue to be severely limited in their functional level and quality of life over the period under review, enhanced treatment approaches that address experiential avoidance seem to be needed.

Heart rate and autonomic biomarkers distinguish convulsive epileptic vs. functional or dissociative seizures.

OBJECTIVE: 20-40% of individuals whose seizures are not controlled by anti-seizure medications exhibit manifestations comparable to epileptic seizures (ES), but there are no EEG correlates. These events are called functional or dissociative seizures (FDS). Due to limited access to EEG-monitoring and inconclusive results, we aimed to develop an alternative diagnostic tool that distinguishes ES vs. FDS. We evaluated the temporal evolution of ECG-based measures of autonomic function (heart rate variability, HRV) to determine whether they distinguish ES vs. FDS. METHODS: The prospective study includes patients admitted to the University of Rochester Epilepsy Monitoring Unit. Participants are 18-65 years old, without therapies or co-morbidities associated with altered autonomics. A habitual ES or FDS is recorded during admission. HRV analysis is performed to evaluate the temporal changes in autonomic function during the peri­ictal period (150-minutes each pre-/post-ictal). We determined if autonomic measures distinguish ES vs. FDS. RESULTS: The study includes 53 ES and 46 FDS. Temporal evolution of HR and autonomics significantly differ surrounding ES vs. FDS. The pre-to-post-ictal change (delta) in HR differs surrounding ES vs. FDS, stratified for convulsive and non-convulsive events. Post-ictal HR, total autonomic (SDNN & Total Power), vagal (RMSSD & HF), and baroreflex (LF) function differ for convulsive ES vs. convulsive FDS. HR distinguishes non-convulsive ES vs. non-convulsive FDS with ROC>0.7, sensitivity>70%, but specificity<50%. HR-delta and post-ictal HR, SDNN, RMSSD, LF, HF, and Total Power each distinguish convulsive ES vs. convulsive FDS (ROC, 0.83-0.98). Models with HR-delta and post-ictal HR provide the highest diagnostic accuracy for convulsive ES vs. convulsive FDS: 92% sensitivity, 94% specificity, ROC 0.99). SIGNIFICANCE: HR and HRV measures accurately distinguish convulsive, but not non-convulsive, events (ES vs. FDS). Results establish the framework for future studies to apply this diagnostic tool to more heterogeneous populations, and on out-of-hospital recordings, particularly for populations without access to epilepsy monitoring units.

Ictal crying in epileptic seizures and psychogenic nonepileptic seizures: What are the hints to differentiate them?

OBJECTIVES: Ictal crying (IC) is a quite rare semiological manifestation of epileptic seizures (ESs) and it has been mostly reported in psychogenic nonepileptic seizures (PNESs). However, labeling IC as a pathognomonic sign of PNES can be harmful. We first aimed to investigate IC frequency in ES and PNES and highlight the differences of IC between ES and PNES. Secondly, we aimed to analyze etiology, detailed semiology, treatment options, and outcome of patients with IC in ES in more detail. METHODS: We retrospectively screened all video-EEG monitoring unit reports from Hacettepe University Hospitals' Epilepsy Center over a 20-year period (1996-2017) for the diagnosis of IC. We included the patients with IC who had at least one documented seizure. Patients who had IC with both facial expression and vocalization compatible with crying with or without weeping and subjective feeling of sadness, were included in the study. We classified patients with IC as ES and PNES. Demographic, historical, clinical, neuroimaging, electrophysiological parameters, video-EEG data, treatment options, and prognosis of all patients were recorded. Demographic, clinical, and video-EEG data were compared between ES and PNES. RESULTS: During the study period, 1983 patients were investigated. Six patients (all female) with ES and 37 patients (33 female) with PNES were identified. When we compared patients with PNES and ES with IC, the number of ASMs taken and duration of disease were significantly higher in patients with ES than PNES. Longer duration of seizure, longer duration of crying component, late onset of crying component in seizure, early responsiveness after seizure, not occurring during sleep, accompanied by eye closure and weeping, were found significantly higher in patients with PNES. Besides, if we analyze ES group in more detail, all had medical treatment refractory focal epilepsy and two of them whose IC was seen as an early semiological manifestation of their seizures had good outcome after nondominant anterior temporal lobectomy (ATL)+amygdalohippocampectomy (AH). However, three patients had various cortical lesions apart from temporal lobe on MRI and one patient had focal epilepsy with frontal lobe semiology with negative MRI. CONCLUSION: Although the most common etiology for IC is PNES and it is rarely seen in ES, it can be harmful to label ictal crying as a pathognomonic sign for PNES. We proposed that there are some semiological differences in terms of IC between PNES and ES. These differences may help to distinguish IC in PNES and ES in daily practice. Moreover, it can be speculated that nondominant temporal lobe involvement may be associated with IC in ES.

Polymorphism of glucocorticoid receptor gene (rs41423247) in functional seizures (psychogenic nonepileptic seizures/attacks).

OBJECTIVE: We investigated the association between the glucocorticoid receptor (GR) gene, also known as the nuclear receptor subfamily 3, group C, member 1 (NR3C1), rs41423247 polymorphism, and functional seizures (psychogenic nonepileptic seizures/attacks) in a case-control study. We hypothesized that the tested polymorphism has significant associations with functional seizures (psychogenic nonepileptic seizures/attacks) independent from comorbid depression. METHODS: Seventy patients with functional seizures (psychogenic nonepileptic seizures/attacks), 70 with major depressive disorder (MDD), and 70 healthy controls (HCs) were studied. Their DNAs were analyzed for NR3C1 rs41423247 polymorphism. RESULTS: Genotype and allele frequencies of rs41423247 were different between the three groups. G allele carriers were more frequent in patients with functional seizures (psychogenic nonepileptic seizures/attacks) and those with MDD compared to HCs (p = 0.0001). However no significant difference was observed with respect to allele distributions between functional seizures (psychogenic nonepileptic seizures/attacks) and MDD groups (p = 0.391). CC genotype was less often associated with functional seizures (psychogenic nonepileptic seizures/attacks) versus HC: Codominant model; p = 0.001, OR = 0.11, 95% CI = 0.05-0.24, and -2loglilkelihood = 231.7. In comparison between functional seizures (psychogenic nonepileptic seizures/attacks) group and other (MDD + HC) groups, we observed a significant association between CG genotype and functional seizures (psychogenic nonepileptic seizures/attacks) (Codominant model; p = 0.001, OR = 5.63, 95% CI = 2.60-12.40 and -2loglikelihood = 245.99). SIGNIFICANCE: Patients with functional seizures (psychogenic nonepileptic seizures/attacks) and those with MDD were significantly more often G allele carriers in rs41423247 compared with HCs. We observed a significant association between CG genotype and functional seizures (psychogenic nonepileptic seizures/attacks). However, we could not exclude the possibility of confounding effects of depression. Future genetic studies of patients with functional seizures (psychogenic nonepileptic seizures/attacks) should include a comparison group with depression in addition to a comparison group of HCs.

Classification of Epileptic and Psychogenic Nonepileptic Seizures via Time-Frequency Features of EEG Data.

The majority of psychogenic nonepileptic seizures (PNESs) are brought on by psychogenic causes, but because their symptoms resemble those of epilepsy, they are frequently misdiagnosed. Although EEG signals are normal in PNES cases, electroencephalography (EEG) recordings alone are not sufficient to identify the illness. Hence, accurate diagnosis and effective treatment depend on long-term video EEG data and a complete patient history. Video EEG setup, however, is more expensive than using standard EEG equipment. To distinguish PNES signals from conventional epileptic seizure (ES) signals, it is crucial to develop methods solely based on EEG recordings. The proposed study presents a technique utilizing short-term EEG data for the classification of inter-PNES, PNES, and ES segments using time-frequency methods such as the Continuous Wavelet transform (CWT), Short-Time Fourier transform (STFT), CWT-based synchrosqueezed transform (WSST), and STFT-based SST (FSST), which provide high-resolution time-frequency representations (TFRs). TFRs of EEG segments are utilized to generate 13 joint TF (J-TF)-based features, four gray-level co-occurrence matrix (GLCM)-based features, and 16 higher-order joint TF moment (HOJ-Mom)-based features. These features are then employed in the classification procedure. Both three-class (inter-PNES versus PNES versus ES: ACC: 80.9%, SEN: 81.8%, and PRE: 84.7%) and two-class (Inter-PNES versus PNES: ACC: 88.2%, SEN: 87.2%, and PRE: 86.1%; PNES versus ES: ACC: 98.5%, SEN: 99.3%, and PRE: 98.9%) classification algorithms performed well, according to the experimental results. The STFT and FSST strategies surpass the CWT and WSST strategies in terms of classification accuracy, sensitivity, and precision. Moreover, the J-TF-based feature sets often perform better than the other two.

Development and validation of a peripheral cell ratio and lactate score for differentiating status epilepticus from prolonged psychogenic nonepileptic seizures.

OBJECTIVE: Differentiating status epilepticus (SE) from prolonged psychogenic nonepileptic seizures (pPNES) can be difficult clinically. We aimed to define the utility of peripheral cell counts, cell ratios, and lactate levels in distinguishing SE from pPNES. METHODS: Retrospective two-center study investigating the sensitivity and specificity of acute (≤12 h of event offset) peripheral cell counts, cell ratios (neutrophil-lymphocyte ratio, neutrophil-monocyte ratio, monocyte-lymphocyte ratio, platelet-lymphocyte ratio, systemic immune-inflammatory index [SII], systemic inflammatory response index [SIRI]), and lactate levels in differentiating SE from pPNES. Patients were identified from two tertiary hospitals, with one forming the development cohort and the other the validation cohort. Using generalized additive models to generate biomarker vs time curves, optimal blood collection times were defined for set parameters. Three diagnostic scores combining neutrophil count, SII, or SIRI with lactate levels were developed and validated in separate cohorts. RESULTS: For the development cohort, 1262 seizure-like events were reviewed and 79 SE and 44 pPNES events were included. For the validation cohort, 241 events were reviewed and 20 SE and 11 pPNES events were included. Individually, the biomarkers generally had low sensitivity and reasonable specificity for differentiating SE from pPNES, with the neutrophil count, SIRI, and SII performing best with sensitivities of 0.65-0.84, specificities of 0.64-0.89, and ROC AUCs of 0.78-0.79. Lactate levels peaked at 60 min, while cell counts and ratios peaked after 240 min. Combining early peaking lactate levels and later peaking neutrophil count, SIRI or SII resulted in three scores that improved predictive potential with sensitivities of between 0.75 and 0.79, specificities between 0.93 and 1.00, and ROC AUCs of 0.89-0.91. SIGNIFICANCE: Lactate levels peak early post-SE, whereas cell counts and ratios do so later. The differing post-event time profiles of lactate levels vs neutrophil count, SIRI, and SII allow incorporation into three separate scores which can assist in differentiating SE from pPNES.

Subjective seizure symptom reporting in functional/dissociative seizures and epilepsy: Effects of sampling technique and patient characteristics.

BACKGROUND: Differences in subjectively reportable ictal experiences between epilepsy and functional/dissociative seizures (FDS) have received less attention than visible manifestations. Patients with FDS (pwFDS) tend to report seizure symptoms differently than patients with epilepsy (pwE). The effects of symptom elicitation method and mediation by psychopathological traits have not been examined and may aid in differentiating the disorders. METHOD: Analysis of responses of 24 pwE and 28 pwFDS in interviews exploring ictal experiences through open questioning followed by structured closed questioning using possible symptom prompts (74-item modified Psychosensory-Psychomotor Phenomena Interview, PPPI); self-report of psychological profile (HADS-A, HADS-D, PHQ-15, DES-T, THQ, PCL-C). RESULTS: Symptom prompting with PPPI elicited three times more seizure symptoms than open questions in pwE (median 34 vs. 11.5, p = 0.005) and over four times more in pwFDS (42.5 vs. 11, p = 0.001). Intra-ictal symptoms were reported freely more frequently by pwE (median 6.5 vs. 4, p = 0.005), while pwFDS reported more pre-ictal symptoms after prompts (median 6 vs 14.5, p = 0.004). The difference between freely reported and PPPI-elicited symptoms correlated with different psychopathological traits in pwE and pwFDS. Symptoms of anxiety (HADS-A) correlated more strongly with prompted symptoms among pwE than pwFDS (z = 2.731, p = 0.006). CONCLUSION: Prompting generates more detailed ictal symptom profiles than simply encouraging patients to narrate their subjective seizure experiences. While pwFDS freely reported fewer symptoms related to the intra-ictal period compared to pwE, pwFDS reported more pre-ictal symptoms than pwE when prompted. Differences in the psychopathological traits associated with the number of peri-ictal symptoms captured by symptom prompting in pwE and pwFDS possibly reflect etiological or psychological differences between these patient groups.

Latency of epileptic and psychogenic nonepileptic seizures.

BACKGROUND: Due to their semiological similarities, psychogenic nonepileptic seizures (PNESs) can occasionally hardly be differentiated from epileptic seizures (ESs), and long-term video-electroencephalographic monitoring (VEM) is needed for the differential diagnosis. OBJECTIVE: To investigate the time of the first clinical event and its distribution on the days of VEM in ES and PNES patients. METHODS: In total, a consecutive series of 48 PNES and 51 ES patients matched for gender and age were retrospectively and consecutively evaluated. The time distribution of the seizures during the day was noted. Seizure latency was determined as the time in hours from the start of the video-electroencephalographic recording to the first clinical event. RESULTS: The seizure latency was significantly shorter in PNES patients compared to ES patients (p < 0.001). Seventy-two percent of PNES patients and 49.1% of ES patients had their first seizure in the 24 hours of video-EEG recording (p = 0.023). Recording longer than 48 hours was required for 12.5% of PNES patients and 37.3% of ES patients (p = 0.006). While ESs were almost evenly distributed throughout the day, most PNESs occurred during the evening hours (p = 0.011). CONCLUSION: We observed that the PNESs appeared earlier than the ESs in the VEM and were concentrated during daylight hours. Although not strictly reliable, seizure latency can contribute to the differential diagnosis of ES and PNES.

ANTECEDENTES: Debido a sus similitudes semiológicas, las crisis no epilépticas psicógenas (CNEP) en ocasiones apenas se pueden diferenciar de las crisis epilépticas (CE), y se necesita una monitorización video-electroencefalográfica (EEG) prolongada para el diagnóstico diferencial. OBJECTIVO: Investigar el momento del primer evento clínico y su distribución en los días de monitorización video-EEG en pacientes con CE y CNEP. MéTODOS: Se evaluó retrospectivamente a una serie consecutiva de 48 pacientes con CNEP y 51 con ES emparejados por sexo y edad. Se anotó la distribución temporal de las incautaciones durante el día. La latencia de las crisis se determinó como el tiempo en horas desde el inicio de la grabación del video-EEG hasta el primer evento clínico. RESULTADOS: La latencia de las crisis fue significativamente menor en los pacientes con CNEP en comparación con los pacientes con CE (p < 0,001). El 72% de los pacientes con CNEP y el 49,1% de los pacientes con CE tuvieron su primera crisis en las 24 horas de registro del video-EEG (p = 0,023). Se requirió un registro de más de 48 horas para el 12,5% de los pacientes con CNEP y el 37,3% de los pacientes con CE (p = 0,006). Mientras que las CE se distribuyeron casi uniformemente a lo largo del día, la mayoría de las CNEP ocurrieron durante las horas después del anochecer (p = 0,011). CONCLUSIóN: Observamos que las CNEPs aparecieron antes que las CEs en la monitorización video-EEG, y se agruparon durante las horas del día. Aunque no es estrictamente confiable, la latencia de las crisis puede contribuir al diagnóstico diferencial de ES y CNEP.

Psychiatric and psychological assessment of Spanish patients with drug-resistant epilepsy and psychogenic nonepileptic seizures (PNES) with no response to previous treatments.

OBJECTIVE: Psychogenic nonepileptic seizures (PNES) are common imitators of epileptic seizures. Refractoriness to antiseizure medication hinders the differential diagnosis between ES and PNES, carrying deleterious consequences in patients with PNES. Psychiatric and psychological characteristics may assist in the differential diagnosis between drug-resistant epilepsy (DRE) and PNES. Nevertheless, current comprehensive psychiatric and psychological descriptive studies on both patient groups are scarce and with several study limitations. This study provides a comprehensive psychiatric and psychological characterization of Spanish patients with DRE and PNES. METHOD: A cross-sectional and comparative study was completed with 104 patients with DRE and 21 with PNES. Psychiatric and psychological characteristics were assessed with the HADS, SCL-90-R, NEO-FFI-R, PDQ-4+, COPE, and QOLIE-31 tests. Parametric and non-parametric tests were used, and regression models were fit to further explore factors affecting patients' life quality. RESULTS: Patients with PNES had greater levels of somatization and extraversion and were associated with benzodiazepine intake. Patients with DRE showed greater narcissistic personality disorder symptoms than those with PNES. In patients with DRE, difficulty in performing basic needs-related tasks and greater psychological distress severity and seizure frequency were associated with poorer life quality. In contrast, being a woman, having a psychiatric disorder history, and greater psychiatric symptoms' intensity were associated with poorer life quality in patients with PNES. CONCLUSION: Patients with DRE and PNES share similar psychiatric and psychological characteristics, with only very few being significantly different.

A meta-analytic review of the effectiveness of psychological treatment of functional/dissociative seizures on non-seizure outcomes in adults.

Psychological therapies are considered the treatment of choice for functional/dissociative seizures (FDSs). Although most previous studies have focused on seizure persistence or frequency, it has been argued that well-being or health-related quality of life outcomes may actually be more meaningful. This study contributes by summarizing and meta-analyzing non-seizure outcomes to quantify the effectiveness of psychological treatment in this patient group. A pre-registered systematic search identified treatment studies (e.g., cohort studies, controlled trials) in FDSs. Data from these studies were synthesized using multi-variate random-effects meta-analysis. Moderators of treatment effect were examined using treatment characteristics, sample characteristics, and risk of bias. A total of 171 non-seizure outcomes across 32 studies with a pooled sample size of N = 898 yielded a pooled effect-size of d = .51 (moderate effect size). The outcome domain assessed and the type of psychological treatment were significant moderators of reported outcomes. Greater rates of improvement were demonstrated for outcomes assessing general functioning. Behavioral treatments emerged as particularly effective interventions. Psychological interventions are associated with clinical improvements across a broad array of non-seizure outcomes, over and above seizure frequency, in adults with FDSs.

Differentiating between epileptic and functional/dissociative seizures using semantic content analysis of transcripts of routine clinic consultations.

The common causes of Transient Loss of Consciousness (TLOC) are syncope, epilepsy, and functional/dissociative seizures (FDS). Simple, questionnaire-based decision-making tools for non-specialists who may have to deal with TLOC (such as clinicians working in primary or emergency care) reliably differentiate between patients who have experienced syncope and those who have had one or more seizures but are more limited in their ability to differentiate between epileptic seizures and FDS. Previous conversation analysis research has demonstrated that qualitative expert analysis of how people talk to clinicians about their seizures can help distinguish between these two TLOC causes. This paper investigates whether automated language analysis - using semantic categories measured by the Linguistic Inquiry and Word Count (LIWC) toolkit - can contribute to the distinction between epilepsy and FDS. Using patient-only talk manually transcribed from recordings of 58 routine doctor-patient clinic interactions, we compared the word frequencies for 21 semantic categories and explored the predictive performance of these categories using 5 different machine learning algorithms. Machine learning algorithms trained using the chosen semantic categories and leave-one-out cross-validation were able to predict the diagnosis with an accuracy of up to 81%. The results of this proof of principle study suggest that the analysis of semantic variables in seizure descriptions could improve clinical decision tools for patients presenting with TLOC.

Does explaining psychogenic nonepileptic seizures using either a biomedical or biopsychosocial framework affect young people's illness representations? An experimental vignette study.

Lay representations of psychogenic nonepileptic seizures (PNES) are important both for understanding public stigma and anticipating patient responses to PNES diagnosis. The current study presents the first evidence of the general public's representations of PNES and the malleability of these understandings to different ways of explaining PNES. An online experimental study exposed participants (n = 193, aged 18-25 years) to a vignette describing a case of PNES in biomedical terms, PNES in biopsychosocial terms, or epilepsy. Subsequent questionnaires assessed participants' illness representations, causal attributions, and stigmatising attitudes regarding the case about which they read. Results suggest that compared with biomedical framings, biopsychosocial explanations increased perceptions of PNES as threatening. While epilepsy was attributed to significantly more biological and less social causes than either of the PNES vignettes, causal attributions did not differ between biomedically- vs. biopsychosocially-framed PNES. Neither were there any differences between the three conditions in stigmatising attitudes towards people who experience seizures. These findings are useful for clinicians delivering a PNES diagnosis and patients disclosing a PNES diagnosis, in helping anticipate responses to these communications. Further research is required to confirm the clinical and societal significance of the study's first insights into the dynamics of lay responses to PNES.