Validation of a novel classification model of psychogenic nonepileptic seizures by video-EEG analysis and a machine learning approach

Functional seizure semiology and classification in a public and private hospital

PURPOSE

Our understanding of potential differences in seizure semiology among patients with functional seizures (FS), also known as psychogenic non-epileptic seizures (PNES), across socioeconomic contexts is currently limited. By examining the differences in seizure manifestations between different socioeconomic groups, we aim to enhance the understanding of how socioeconomic factors may influence FS presentation. This study aimed to describe FS semiology in patients from a private and public epilepsy monitoring units (EMUs) in Cape Town, South Africa.

METHODS

The study included patients with FS confirmed through video-electroencephalography (video-EEG) and without comorbid epilepsy. For this retrospective case-control study, data on seizure semiology was gathered from digital patient records, beginning with the earliest available record for each hospital.

RESULTS

A total of 305 patients from a private hospital and 67 patients from a public hospital were eligible for the study (N = 372). The private hospital tended to report more akinetic and subjective seizure types when compared to the public hospital. Additionally, patients at the public hospital had higher odds of reporting emotional seizure triggers (aOR=2.57, 95% CI [1.03, 6.37]), loss of consciousness or awareness (aOR=2.58, 95% CI [1.07, 6.24]), and rapid post-event recovery (aOR=6.01, 95% CI [2.52, 14.34]). At the same time, they were less likely to report both short (<30 s) (aOR=0.21, 95% CI [0.08, 0.55]) and long (>5 min) seizures (aOR=0.73, 95% CI [0.13, 0.56]), amnesia for the event (aOR=0.19, 95% CI [0.09, 0.43]), ictal aphasia (aOR=0.33, 95% CI [0.14, 0.76]) or falls and drop attacks (aOR=0.43, 95% CI [0.18, 0.996]), when compared to the private hospital patients.

CONCLUSION

While the seizure manifestations were largely consistent across the two socioeconomic cohorts of patients with FS, some subtle differences were observed and warrant further investigation.

The Utility of 24-h Video-EEG Monitoring in the Diagnosis of Epilepsy in Children

Objectives: Evaluate the diagnostic yield of 24-h video-EEG monitoring in a group of children admitted in our epilepsy monitoring unit (EMU). Methods: 232 children who underwent 24-h video-EEG monitoring was analysed. We divided each patient's monitoring duration into the first 1, 2, 4, 8, 16 h, relative to the whole 24 h monitoring period. The detection of the first interictal epileptiform discharges (IEDs), epileptic seizures (ES), and psychogenic non-epileptic seizures (PNES) were analysed relative to the different monitoring time subdivision. Results: Our findings revealed that: (1) there was no significant difference in the prevalence of detecting initial IEDs between the first 4-h and 24-h monitoring periods (73.7% vs 81%); (2) clinical events detection rate was statistically similar between the first 8-h and 24-h monitoring periods (15.5% vs 19.3%); (4) an 8-h monitoring was sufficient to capture IEDs, ES and PNES in focal epilepsy children; (5) a 1-h monitoring was sufficient to capture IEDs, ES and PNES in generalized epilepsy children; and (6) IEDs were detected within the first 1-h of monitoring in 96.7% self-limited focal epilepsies (SeLFEs) patient. Conclusion: Our study suggests that a 4-h monitoring has more value in increasing the detection rate of IEDs compared to the traditional shorter routine EEG. And in the case of SeLFEs, a 1-h of monitoring might be sufficient in detecting IEDs. A 24-h VEEG monitoring can detect clinical events in 19.3% of patients. Overall, the yield of IEDs and clinical events detection is adequate in children in children undergoing 24-h video-EEG monitoring.

Computer vision for automated seizure detection and classification: A systematic review

Computer vision (CV) shows increasing promise as an efficient, low-cost tool for video seizure detection and classification. Here, we provide an overview of the fundamental concepts needed to understand CV and summarize the structure and performance of various model architectures used in video seizure analysis. We conduct a systematic literature review of the PubMed, Embase, and Web of Science databases from January 1, 2000 to September 15, 2023, to identify the strengths and limitations of CV seizure analysis methods and discuss the utility of these models when applied to different clinical seizure phenotypes. Reviews, nonhuman studies, and those with insufficient or poor quality data are excluded from the review. Of the 1942 records identified, 45 meet inclusion criteria and are analyzed. We conclude that the field has shown tremendous growth over the past 2 decades, leading to several model architectures with impressive accuracy and efficiency. The rapid and scalable detection offered by CV models holds the potential to reduce sudden unexpected death in epilepsy and help alleviate resource limitations in epilepsy monitoring units. However, a lack of standardized, thorough validation measures and concerns about patient privacy remain important obstacles for widespread acceptance and adoption. Investigation into the performance of models across varied datasets from clinical and nonclinical environments is an essential area for further research.

Dissociative seizures in the emergency room: room for improvement

BACKGROUND

Dissociative seizures, also known as functional or psychogenic non-epileptic seizures, account for 11%-27% of all emergency seizure presentations. Misdiagnosis as epileptic seizures is common and leads to ineffective and potentially harmful treatment escalations. We assess the potential for diagnostic improvement at different stages of emergency workup and estimate the utility of benzodiazepines.

METHODS

A retrospective study of all emergency presentations with a discharge diagnosis of acute dissociative seizures seen at a university hospital 2010-2022 was performed to assess clinical characteristics and emergency decision-making.

RESULTS

Among 156 patients (73% female, median 29 years), 15% presented more than once for a total of 203 presentations. Half of seizures were ongoing at first medical contact; prolonged seizures and clusters were common (23% and 24%). Diagnostic accuracy differed between on-site emergency physicians and emergency department neurologists (12% vs 52%). Typical features such as eye closure, discontinuous course and asynchronous movements were common. Benzodiazepines were given in two-thirds of ongoing seizures, often in high doses and preferentially for major hyperkinetic semiology. Clinical response to benzodiazepines was mixed, with a minority of patients remaining either unaffected (16%) or becoming critically sedated (13%). A quarter of patients given benzodiazepines by emergency medical services were admitted to a monitoring unit, 9% were intubated.

CONCLUSIONS

Improved semiological assessment could reduce early misdiagnosis of dissociative seizures. Although some seizures seem to respond to benzodiazepines, critical sedation is common, and further studies are needed to assess the therapeutic ratio.

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.

Pediatric psychogenic non-epileptic seizures: A retrospective observational cohort study at a quaternary center

BACKGROUND

Psychogenic non-epileptic seizures (PNES) represent a common functional disorder in the pediatric population. We aimed to characterize pediatric PNES by describing their clinical characteristics, PNES semiologies, and healthcare pathway towards and after diagnosis.

MATERIAL AND METHODS

This was a retrospective, observational chart review of pediatric patients aged 6 to 18 years admitted between December 2020 and December 2021 for spell classification or suspected PNES. Psychogenic non-epileptic seizure diagnosis was made by the capture of a typical event on video electroencephalogram (vEEG). We used descriptive statistics to summarize demographic and clinical characteristics.

RESULTS

We included 26 patients (18 females, 69.2%) with a mean age (SD) of 13.9 (2.5) years. Pre-morbid neurologic and psychiatric conditions included: epilepsy (23.1%), migraine (46.2%), mild traumatic brain injury (26.9%), anxiety (57.7%), ADHD (34.6%), and depression (30.8%). Six patients (23.1%) had a prior diagnosis of PNES. 14 patients (53.8%) presented with convulsive, and 6 (23.1%) each with non-convulsive and mixed PNES. Patients were seen by a range of providers prior to diagnosis including ED providers (50%), neurologists (53.8%), pediatricians (34.6%), and psychology/psychiatry (11.5%). Emergency department evaluation occurred for 13 patients (50%) on 15 occasions, and six (23.1%) were admitted to the hospital. The median (p25-p75) time from PNES onset to presentation and diagnosis at our institution was 3.5 (1.5-6.2) and 4.1 (3-7) months, respectively. A total of 33 events from the 26 patients were captured on vEEG. The most frequent semiologies in our cohort were rhythmic motor (27.3%) followed by equal frequency (18.2%) of complex motor and dialeptic. Eighteen patients (69.2%) were followed after the PNES diagnosis, for a median (p25-p75) of 17.3 months (6.3-21) with variable outcome.

CONCLUSION

Pediatric PNES has female predominance and often presents with comorbid psychosocial stressors and psychiatric conditions. High clinical suspicion and early recognition are crucial to decrease healthcare utilization and establish timely diagnosis and treatment.

Improving the treatment of functional seizures through a public specialist outpatient clinic

OBJECTIVES

We performed an audit of the first 12 months of clinical operations to assess the feasibility of a newly established public outpatient clinic for the assessment and treatment of functional (psychogenic nonepileptic) seizures (FS).

METHOD

Clinical notes for the first 12 months of the FSclinic weresystematicallyreviewed with data compiled onreferral pathways, clinic attendance, clinical features, treatments, and outcomes.

RESULTS

Of eighty-two new FS patients referred to the clinic, over 90% attended. Patients were diagnosed with FS after comprehensive epileptological and neuropsychiatric review, mostly with typical seizure-like episodes captured during video-EEG monitoring, and most accepted the diagnosis. Most had FS at least weekly, with little sense of control and significant impairment. The majority of individuals had significant psychiatric and medical comorbidity. Predisposing, precipitating, and perpetuating factors were readily identified in >90% of cases. Of 52 patients with follow-up data within12 months, 88% were either stable or improved in terms of the control of their FS.

CONCLUSION

The Alfred functional seizure clinic model, the first dedicated public outpatient clinic for FS in Australia, provides a feasible and potentially effective treatment pathway for this underserved and disabled patient group.

Epilepsy in Joubert Syndrome: A Still Few Explored Matter

Epilepsy is rarely associated with Joubert's syndrome and related disorders (JSRD), being reported only in 3% of cases. Few patients have been described, moreover, with poor evidences of specific seizures' semiology or standard of practice for pharmacological treatment. Epilepsy is likely to be related to brain malformations in ciliopathies. Beyond the typical hindbrain malformation, the molar tooth sign, other cerebral anomalies variably reported in JSRD, such as generalized polymicrogyria, hamartomas, periventricular nodular heterotopia, and hippocampal defects, have been described. Herein, we aimed to revise the main clinical and etiopathogenetic characteristics of epilepsy associated with JSRD.

Bardet–Biedl Syndrome: A Brief Overview on Clinics and Genetics

Bardet–Biedl syndrome is a genetically pleiotropic disorder characterized by high clinical heterogeneity with severe multiorgan impairment. Clinically, it encompasses primary and secondary manifestations, mainly including retinal dystrophy, mental retardation, obesity, polydactyly, hypogonadism in male, and renal abnormalities. At least 21 different genes have been identified, all involved into primary cilium structure or function. To date, genotype–phenotype correlation is still poor.

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records

Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care. We performed a retrospective study using neuropathology reports from the German Neuropathology Reference Center for Epilepsy Surgery at Erlangen, Germany. This cohort included 312 patients who underwent epilepsy surgery and were labeled with one or more diagnoses, including dual pathology, hippocampal sclerosis, malformation of cortical dysplasia, tumor, encephalitis, and gliosis. We modeled the diagnosis terms together with their microscopy, immunohistochemistry, anatomy, etiologies, and imaging findings using the description logic-based Web Ontology Language (OWL) in the Epilepsy and Seizure Ontology (EpSO). Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology-based feature engineering. We used five-fold cross validation to avoid overfitting with a fixed number of repetitions while leaving out one subset of data for testing, and we used recall, balanced accuracy, and hamming loss as performance metrics for the multi-label classification task. The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in logistics regression, random forest, and gradient tree boosting models respectively. The run time performance of all three models improved significantly with ontology-based feature engineering with gradient tree boosting model showing a 93.8% reduction in the time required for training and testing of the model. Although, all three models showed an overall improved performance across the three-performance metrics using ontology-based feature engineering, the rate of improvement was not consistent across all input features. To analyze this variation in performance, we computed feature importance scores and found that microscopy had the highest importance score across the three models, followed by imaging, immunohistochemistry, and anatomy in a decreasing order of importance scores. This study showed that ontologies have an important role in feature engineering to make heterogeneous clinical data accessible to machine learning models and also improve the performance of machine learning models in multilabel multiclass classification tasks.

Multidimensional psychopathological profile differences between patients with psychogenic nonepileptic seizures and epileptic seizure disorders

OBJECTIVE

Early differential diagnosis of psychogenic nonepileptic seizures (PNES) and epileptic seizures (ES) remains difficult. Self-reported psychopathology is often elevated in patients with PNES, although relatively few studies have examined multiple measures of psychopathology simultaneously. This study aimed to identify differences in multidimensional psychopathology profiles between PNES and ES patient groups.

METHOD

This was a retrospective case-control study involving patients admitted for video-EEG monitoring (VEM) over a two-year period. Clinicodemographic variables and psychometric measures of depression, anxiety, dissociation, childhood trauma, maladaptive personality traits, and cognition were recorded. Diagnosis of PNES or ES was determined by multidisciplinary assessment and consensus opinion. General linear mixed models (GLMMs) were used to investigate profile differences between diagnostic groups across psychometric measures. A general psychopathology factor was then computed using principal components analysis (PCA) and differences between groups in this 'p' factor were investigated.

RESULTS

261 patients (77 % with ES and 23 % with PNES) were included in the study. The PNES group endorsed greater symptomatology with GLMM demonstrating a significant main effect of group (η²_p = 0.05) and group by measure interaction (η²_p = 0.03). Simple effects analysis indicated that the PNES group had particularly elevated scores for childhood trauma (β = 0.78), dissociation (β = 0.70), and depression (β = 0.60). There was a high correlation between psychopathology measures, with a single p factor generated to explain 60 % variance in the psychometric scores. The p factor was elevated in the PNES group (β = 0.61). ROC curve analysis indicated that these psychometric measures had limited usefulness when considered individually (AUC range = 0.63-0.69).

CONCLUSION

Multidimensional psychopathological profile differences exist between patients with PNES and ES. Patients with PNES report more psychopathology overall, with particular elevations in childhood trauma, dissociation, and depression. Although not suitable to be used as a standalone screening tool to differentiate PNES and ES, understanding of these profiles at a construct level might help triage patients and guide further psychiatric examination and enquiry.

Case report on psychogenic nonepileptic seizures: A series of unfortunate events

Psychogenic nonepileptic seizures, also called Functional Seizures, are a highly disabling form of Functional Neurological Disorder. The diagnosis of PNES could be missed in clinical scenarios where patients exhibit concurrent musculoskeletal/neurological findings. Characterization of convulsions and judicious use of diagnostics are equally valuable in establishing the diagnosis.

Machine learning and clinical neurophysiology

Clinical neurophysiology constructs a wealth of dynamic information pertaining to the integrity and function of both central and peripheral nervous systems. As with many technological fields, there has been an explosion of data in neurophysiology over recent years, and this requires considerable analysis by experts. Computational algorithms and especially advances in machine learning (ML) have the ability to assist with this task and potentially reveal hidden insights. In this update article, we will provide a brief overview where such technology is being applied in clinical neurophysiology and possible future directions.

Translating Phenomenology of Psychogenic Nonepileptic Seizures Into Nosology: Insights From Patients' and Caregivers' Profiles

BACKGROUND

Patients with psychogenic nonepileptic seizures (PNES) can be semiologically dichotomized into those with hyperkinetic and those with paucikinetic events. The objective of this study was to compare characteristics of patients with diverse phenomenology and their caregivers to evaluate for differences that could inform about disease nosology.

METHODS

Patients and caregivers monitored at the Epilepsy Monitoring Unit completed surveys about sociodemographic and disease characteristics, treatment and health care utilization, physical and psychosocial impact, and epilepsy knowledge. Patients were classified into hyperkinetic versus paucikinetic based on their recorded events. Comparison of the 2 populations was performed using Student t test for continuous variables and Fischer exact test for categorical variables.

RESULTS

Forty-three patients with Epilepsy Monitoring Unit confirmed PNES and 28 caregivers were enrolled. Patients with hyperkinetic events were more commonly non-White patients and necessitated greater caregiving time. Otherwise, no statistically significant differences were seen between the 2 semiologically diverse groups of patients and caregivers in their sociodemographic (age, sex, employment, income, marital, and education) and disease (age of onset, duration, seizures frequency) characteristics, treatment (number of antiseizure medications before diagnosis, side effects) and health care utilization (emergency room visits, hospitalizations, clinic visits), physical (injuries) and psychosocial (depression, anxiety, quality of life, stigma, burden) characteristics, nor in their knowledge about seizures.

CONCLUSIONS

Hyperkinetic events were more frequently encountered in non-White patients and required more caregiving time. Further research is required to elucidate if phenomenological dichotomy of PNES can inform about their nosological basis, and if it can guide treatment and define prognosis.

[Psychogenic non-epileptic seizures]

The review provides epidemiological data and discuss the associated burden of non-epileptic seizures (PNES). Data on the prevalence, socio-demographic and clinical risk factors for the development of PNES are presented. The hypotheses of the PNES origin, including the contribution of psychological trauma, are considered. We also describe contemporary methods for differential diagnosis of epileptic seizures and PNES, including biomarkers and the use of diagnostic questionnaires. Special attention is given to the issues of the psychiatric comorbidity of PNES.

Psychogenic non-epileptic seizures in children

Psychogenic Non-Epileptic Seizures (PNES) are a relatively common condition in children. While their clinical presentation resembles epileptic seizures, the underlying cause for PNES involves a multitude of bio-psychosocial factors. Patients may be misdiagnosed with epilepsy and subjected to unnecessary treatments, often delaying the diagnosis for years. A strong understanding of its symptomatology is essential for diagnosis of PNES. Successful management depends on effective teamwork that involves the neurologist as well as mental health professionals. This paper reviews the various aspects of PNES in children with emphasis on the clinical presentation, diagnosis as well as the underlying psychological basis and treatment.

Usefulness of a new semiological classification for characterizing psychogenic nonepileptic seizures

BACKGROUND

Nonepileptic events misdiagnosed as epilepsy lead to a risk of iatrogenic morbidity, which increases health costs. Among the patients affected by nonepileptic events, 11-46% are psychogenic nonepileptic seizures (PNESs).

OBJECTIVE

To investigate the usefulness of the semiological classification of PNESs among patients diagnosed by means of video electroencephalograms (vEEGs).

METHODS

This was a retrospective review of the medical records of patients admitted to the adult vEEG unit between April 2007 and December 2016, who were diagnosed with PNES that was confirmed through vEEG. Analysis on demographic and clinical data and classification of PNESs according to the Magaudda classification were performed.

RESULTS

We identified 143 patients, among whom 31.5% had also epilepsy. According to the Magaudda classification, the events were: hypermotor (58%); subjective symptoms (21.7%); akinetic (14.7%) and focal motor (5.6%). Hypermotor predominated in both genders, followed by subjective symptoms in women (23.9%) and akinetic in men (19.2%). The mean number of antiepileptic drugs (AEDs) prescribed per patient was 2.3. Thirty-two patients (22.4%) required at least one hospitalization for PNESs. 48.3% of the patients had psychiatric comorbidities.

CONCLUSION

The proposed semiological classification of PNESs is a relevant tool that general neurologists can use to characterize these events in their daily practice. Correct use of this classification, together with vEEG and appropriate clinical suspicion, makes it possible to reach an accurate early diagnosis, thus reducing morbidity and, possibly, the high costs associated with PNESs.

Long-Term V-EEG in Epilepsy: Chronological Distribution of Recorded Events Focused on the Differential Diagnosis of Epileptic Seizures and Psychogenic Non-Epileptic Seizures

Differential diagnosis in epilepsy is sometimes challenging. Video-electroencephalography (V-EEG) is an essential tool in the diagnosis and management of epilepsy. The prolonged duration of V-EEG recording increases the diagnostic yield of a conventional V-EEG. The right length of monitoring for different indications is still to be established. We present a retrospective descriptive study with a sample of 50 patients with long-term V-EEG monitoring, with a mean age of 36.1 years, monitored from 2013 to 2019 at the Burgos University Hospital. The mean monitoring time was 3.6 days. Events were obtained in 76% of the patients, corresponding to epileptic seizures (ES) in 57.9% of them, with psychogenic non-epileptic seizures (PNES) in 39.5%, and with episodes of both pathologies in 2.6% of the patients. We found that the first event was highly representative, and it correlated with the rest of the events that would be recorded. Moreover, 92% of the first PNES had been captured at the end of the second day, and 89% of the first ES by the end of the third day. V-EEG for differential diagnosis between ES and PNES can be performed in hospitals without specialized epilepsy surgery units. For this indication, the duration of long-term V-EEG can be adjusted individually depending on the nature of the first event.

Updated Review on the Diagnosis and Primary Management of Psychogenic Nonepileptic Seizure Disorders

Psychogenic nonepileptic seizures (PNES) are paroxystic and episodic events associated with motor, sensory, mental or autonomic manifestations, which resemble epileptic seizures (ES), but are not caused by epileptogenic activity. PNES affect between 20% and 30% of patients attending at epilepsy centers and constitute a serious mental health problem. PNES are often underdiagnosed, undertreated and mistaken with epilepsy. PNES are diagnosed after medical causes (epilepsy, syncope, stroke, etc.) have been ruled out, and psychological mechanisms are involved in their genesis and perpetuation. For psychiatry, there is not a single definition for PNES; the DSM-IV and ICD-10/11 describe the conversion and dissociative disorders, and the DSM-5 describes the functional neurological disorders. However, patients with PNES also have a high frequency of other comorbidities like depression, particularly trauma and post-traumatic stress disorder. It has been postulated that PNES are essentially dissociations that operate as a defensive psychological mechanism that use the mind as a defense to deal with traumas. With the advent of VEEG in the 90s, the recognition of PNES has significantly increased, and several psychological treatments have been developed. In this manuscript, we carried out a state-of-the-art review, with the aim to provide a critical approach to the extensive literature about PNES, focusing on diagnostic aspects, the primary management, and the available treatments that have been shown to be effective for the improvement of PNES.

Quality of life in patients with epilepsy or psychogenic nonepileptic seizures and the contribution of psychiatric comorbidities

Epilepsy is a common neurological disorder, and psychogenic nonepileptic seizures (PNES) is an important differential diagnosis. Psychiatric comorbidities are prevalent among people with epilepsy (PWE). Additionally, lower quality of life (QoL) in people with PNES compared with PWE was reported with higher rates of general psychiatric comorbidity. Although there are previous studies evaluating the QoL in patients with epilepsy, this study is unique and compelling because it represents a study comparing PNES and PWE on QoL, depression, and anxiety in a Spanish-speaking group of Argentine patients. The aim of this study was to analyze self-reported anxiety and depression in PWE and PNES and to establish the impact on QoL.

METHODS

This is a cross-sectional study; QoL was measured using the Quality of Life in Epilepsy Inventory (QOLIE-31). To study anxiety and depression, the Hospital Anxiety and Depression Scale (HADS) was administered. Clinical and complementary data were recorded.

RESULTS

Psychogenic nonepileptic seizures scored significantly higher in anxiety and depression and with lower levels of QoL compared with PWE. Anxiety and depression had a negative correlation with QoL.

CONCLUSION

Nonepileptic seizures have an even greater impact on QoL than epileptic seizures, and this could be influenced by psychiatric comorbidities. These findings corroborate what other studies in English-speaking nations that have found regarding the impact of psychopathology on QoL in those with PNES and further support the importance of assessing for psychiatric comorbidities to tailor treatment.

Functional neurological disorder: Characteristics and outcome in a limited-resources country (Sudan)

BACKGROUND

There is a scarcity of reports from limited-resources countries on functional neurological disorder (FND). We therefore carried out this descriptive study from Sudan to highlight the clinical characteristics of patients and the cultural, diagnostic, and management outcome.

METHOD

Of 1000 new referrals and patients seen at a central neuropsychiatric clinic in Khartoum, Sudan, 40 fulfilled the criteria for FND. Subjects were diagnosed by excluding organic illness and confirming psychological distress through neuropsychological assessment and clinical interview. Mood was measured using the Beck Depression Inventory (BDI) and Hospital Anxiety and Depression (HAD) scales.

RESULTS

Young unemployed women constituted 60% of our sample. Most subjects presented with psychogenic nonepileptic seizures (82.5%), speech abnormalities (47.5%), and limb paralysis or weakness was (35%). Associated mood disorder was found in 97.5% of all subjects. However, 95% of our sample showed a remarkable clinical response to combination therapy (antidepressants and psychotherapy).

SIGNIFICANCE

Patients with FND showed strong evidence of comorbid affective disorders in the form of depression and anxiety disorder. Most patients (95%) responded well to combination therapy with antidepressants and psychotherapy. Sociodemographic correlates of FND in Sudan prove to be consistent with features found in Western cultures, with only minor idiosyncratic characteristics due to local culture.

Differential Semiology Based on Video Electroencephalography Monitoring Between Psychogenic Nonepileptic Seizures and Temporal Lobe Epileptic Seizures

BACKGROUND

Psychogenic nonepileptic seizures (PNESs) are disruptive changes in behavior without ictal correlate of epileptic activity and high prevalence of psychiatric morbidity. Differential diagnosis is difficult particularly with temporal lobe epilepsy (TLE), which is also associated with high prevalence of psychiatric comorbidity. Although video electroencephalography is the gold standard for differential diagnosis, clinical semiology analysis may help the clinician in general medical practice.

OBJECTIVE

In this study, the differential semiology, based on video electroencephalography, between PNESs and TLE seizures was analyzed.

METHODS

The video electroencephalography of patients with diagnosis of PNES and TLE were reviewed and compared between groups. Clinical semiology of all episodes recorded by video electroencephalography in each patient was analyzed and classified in accordance with the presence of behavioral arrest, motor hyperkinetic activity, impaired awareness, aura, and automatisms. Chi square test and binary logistic regression were determined.

RESULTS

Thirty-two patients with PNES (32 ± 11 y) and 34 with TLE (32 ± 12 y) were included. Female patients were predominant in the PNES group (P < 0.05). Mean time duration of episodes was 6.8 ± 10 minutes in PNES and 1.6 ± 0.8 minutes in TLE (P < 0.05). Impaired awareness (odds ratio = 24.4; 95% confidence interval = 3.79 -157.3, P < 0.01), automatisms (odds ratio = 13.9; 95% confidence interval = 2.1- 90.5, P < 0.01), and shorter duration of the events (odds ratio = 2.261, 95% confidence interval = 1.149 - 4.449, P = 0.018) were found as independent factors for detecting TLE seizures comparing PNESs.

CONCLUSION

Clinical semiology analysis may orientate the differential diagnosis in general medical practice, between PNESs and TLE seizures. Further studies comparing PNES semiology with other subtypes of epilepsies may complete these preliminary findings.

Psychogenic Non-epileptic Seizures and Pseudo-Refractory Epilepsy, a Management Challenge

Psychogenic nonepileptic seizures (PNES) are neurobehavioral conditions positioned in a gray zone, not infrequently a no-man land, that lies in the intersection between Neurology and Psychiatry. According to the DSM 5, PNES are a subgroup of conversion disorders (CD), while the ICD 10 classifies PNES as dissociative disorders. The incidence of PNES is estimated to be in the range of 1.4-4.9/100,000/year, and the prevalence range is between 2 and 33 per 100,000. The International League Against Epilepsy (ILAE) has identified PNES as one of the 10 most critical neuropsychiatric conditions associated with epilepsy. Comorbidity between epilepsy and PNES, a condition leading to "dual diagnosis," is a serious diagnostic and therapeutic challenge for clinicians. The lack of prompt identification of PNES in epileptic patients can lead to potentially harmful increases in the dosage of anti-seizure drugs (ASD) as well as erroneous diagnoses of refractory epilepsy. Hence, pseudo-refractory epilepsy is the other critical side of the PNES coin as one out of four to five patients admitted to video-EEG monitoring units with a diagnosis of pharmaco-resistant epilepsy is later found to suffer from non-epileptic events. The majority of these events are of psychogenic origin. Thus, the diagnostic differentiation between pseudo and true refractory epilepsy is essential to prevent actions that lead to unnecessary treatments and ASD-related side effects as well as produce a negative impact on the patient's quality of life. In this article, we review and discuss recent evidence related to the neurobiology of PNES. We also provide an overview of the classifications and diagnostic steps that are employed in PNES management and dwell on the concept of pseudo-resistant epilepsy.

Psychogenic nonepileptic seizures in pediatric population: A review

INTRODUCTION

Psychogenic nonepileptic seizures (PNES) are observable abrupt paroxysmal changes in behavior or consciousness that resemble epileptic seizures, but without concurrent electroencephalographic abnormalities.

METHODS

In this manuscript, we reviewed literature concerning pediatric PNES and focused on those articles published in the last 10 years, in order to try to understand what the state of the art is at the moment, particularly as regards relationship and differential diagnosis with epilepsy.

RESULTS

Psychogenic nonepileptic seizures have been extensively described in literature mainly in adults and less frequently in children. Despite the potential negative impact of a misdiagnosis (unnecessary investigations and antiepileptic drugs, structured pathological behavioral patterns), in literature there is little information regarding the real prevalence, clinical features, treatment, and outcome of PNES in children and adolescents.

CONCLUSION

Psychogenic nonepileptic seizures are common but frequently missed entity in pediatric population. Diagnosis could be difficult, especially in those children who have both epileptic and nonepileptic seizures; video EEG and home video can help clinicians in diagnosis. More studies are needed to better classify PNES in children and facilitate diagnosis and treatment.

Semiological classification of psychogenic nonepileptic seizures: A systematic review and a new proposal

PURPOSE

A semiological classification of psychogenic nonepileptic seizures (PNES) may help address proper diagnosis and management and also provide standardization for future studies. The aim of the current paper was to systematically review the literature on the proposed classification systems for the semiology of PNES and to provide a new proposal based on the best available evidence.

METHODS

I searched the electronic database PubMed on May 16, 2019 for articles that included the following search terms: "psychogenic" AND "semiology" or "classification" and also "nonepileptic" AND "semiology" or "classification" and also "pseudoseizure" AND "semiology" or "classification" since 1940. I applied the same methodology using the electronic database Scopus, though I limited the search to the title, abstract, and keywords.

RESULTS

I could identify 15 classification systems through this search strategy using the electronic database PubMed. Searching the Scopus did not yield any additional relevant papers.

CONCLUSION

I proposed a new semiological classification system for PNES based on this systematic review. This includes three major classes of motor seizures, nonmotor seizures, and mixed semiology. A universally accepted and appropriate semiological classification system for PNES may lead to better standardization of future studies and may also help in better understanding of the pathophysiological basis of this condition.

Differential diagnosis between epileptic seizures and psychogenic nonepileptic seizures based on semiology

Psychogenic nonepileptic seizures present as paroxysmal symptoms and signs mimicking epileptic seizures. The gold standard test is the synchronous recording by video, electrocardiogram and electroencephalogram. However, video electroencephalogram is not available at many centers and not entirely independent of semiology. Recent studies have focused on semiological characteristics distinguishing these two circumstances. Clinical signs and symptoms provide important clues when making differential diagnosis. The purpose of this review is to help physicians differentiating psychogenic nonepileptic seizures better from epileptic seizures based on semiology, and improve care for those patients.

Presentation of psychogenic nonepileptic seizures in Hawaii's ethnoracially diverse population

PURPOSE

This exploratory study compared the semiology of psychogenic nonepileptic seizures (PNES) between a diverse group of patients in the state of Hawaii. This study may expand understanding of PNES across different ethnocultural and gender groups.

METHODS

A retrospective chart review of patients admitted to our Epilepsy Monitoring Unit (EMU) over a 4-year period was performed to compare semiology in different ethnic groups and gender.

RESULTS

A total of 139 patients were included in this study, 37% (n = 51) with PNES, 34% (n = 47) with epilepsy only, and 29% (n = 41) with other non-PNES, nonepilepsy diagnosis. The number of Asians with PNES were found to differ when compared with the patients with epilepsy and the patients with non-PNES, nonepilepsy diagnosis. A positive trend was found in the number of Native Hawaiians and Caucasians with PNES in comparison with patients with non-PNES, nonepilepsy diagnosis. In addition, three semiology of PNES in Native Hawaiians were found to differ in comparison with other ethnic groups with PNES: rhythmic motor, mixed semiology, and nonepileptic aura. There is a significant difference in all motor manifestation between males and females in Native Hawaiians. Between patients with PNES, patients with epilepsy, and patients with non-PNES, nonepilepsy diagnosis, significant correlation was found in psychiatric disorders including posttraumatic stress disorder (PTSD), anxiety, and any psychiatric disorder.

CONCLUSION

This cross-cultural study found significant differences in the expression of PNES across key ethnoracial groups for the Islands of Hawaii. These findings have implications to the diagnosis and treatment of PNES for Native Hawaiians and other Pacific Islanders in the United States.

A systematic study of stereotypy in epileptic seizures versus psychogenic seizure-like events

OBJECTIVE

The objective of this study was to quantify the features of stereotypy in epileptic seizures and compare it with that of stereotypy in psychogenic nonepileptic seizure-like events (PNES) confirmed by video-electroencephalography (VEEG) monitoring.

METHODS

Video-electroencephalography monitoring records of 20 patients with temporal lobe seizures (TLS) and 20 with PNES were retrospectively reviewed (n = 138 seizures, 48 TLS and 90 PNES). We analyzed the semiology of 59 behaviors of interest for their presence, duration, sequence, and continuity using quantified measures that were entered into statistical analysis.

RESULTS

We identified discontinuity as the parameter that was clearly distinct between PNES and epileptic TLS events: there were significantly more frequent pauses of behavior (i.e., "on-off" pattern) in PNES compared with TLS (P = 0.012). The frequency of pauses during an event was diagnostic of PNES events. For instance, the presence of 2 "pauses" during an episode determines a 69% probability of the seizure being nonepileptic. Moreover, PNES events had significantly greater duration (143 s) than TLS events (68 s) (excluding outliers, P = 0.002) and greater duration variability from one event to another in the same subject (P = 0.005).

SIGNIFICANCE

Our work provides the first quantified measure of behavioral semiology during epileptic and nonepileptic seizures and offers novel behavioral measures to differentiate them from each other.

Semiological characteristics of patients with psychogenic nonepileptic seizures: Gender-related differences

Psychogenic nonepileptic seizures (PNES) are more prevalent among women, and diagnosis may sometimes be delayed by as much as seven years. Understanding the effect of gender on the presentation of a PNES may assist with diagnosis based on semiological details in the clinical setting. Although video-EEG monitoring (VEM) is the gold standard for diagnosing PNES, determining gender-related seizure semiology through careful history may prevent diagnostic delay while waiting for VEM. The aim of this study was to investigate gender-related differences in the semiology of PNES. Patients, all aged at least 16 years, diagnosed with PNES following VEM between December 2005 and November 2016 were included in this study. All patients' medical records and video-EEG-documented PNES were reviewed, and the presence or absence of semiological signs was recorded for each documented attack. Demographic features and semiological signs of PNES were compared between female and male patients. Forty-one patients (31 females, 10 males) aged 27.2 ± 12.2 years (range: 16-65) were included in the study. Mean age at onset of PNES was higher for female patients than males, at 24.3 ± 11.5 versus 17.5 ± 3.2 years (p = 0.005). The median duration of PNES was longer for female patients than males, at 10 min (range: 5 s-120 min) versus 2 min (range: 10 s-60 min) (p = 0.016). The most common symptom was forced eye closure in both genders. No significant gender-specific differences were observed in terms of the type or semiology of PNES. Although there are no major gender-related differences in PNES semiology, our findings highlight the importance of greater caution, especially in male patients, when diagnosing PNES, remembering that onset may also occur at young ages and that a short seizure duration does not exclude PNES.

An Overview of Psychogenic Non-Epileptic Seizures: Etiology, Diagnosis and Management

The purpose of this review is to provide an update of the research regarding the etiology, diagnosis and management of psychogenic non-epileptic seizures (PNES). A literature search using Pubmed, Ovid MEDLINE and EMBASE database was performed from 2000 up to August 2017. We have evaluated the different factors leading to PNES as well as the diagnostic approach and management of this disorder which continue to be very difficult. The coexistence of epilepsy and PNES poses special challenges and requires the coordinated efforts of the family physicians, psychiatrists, psychologists and neurologists. Although this condition has an overall poor prognosis, a multidisciplinary approach in the diagnosis and management of this disorder would likely improve the outcomes. We have proposed a diagnostic and treatment algorithm for PNES and suggested a national registry of patients suffering from this condition. The registry would contain data regarding treatment and outcomes to aid in the understanding of this entity.

Are the clinical classifications for psychogenic nonepileptic seizures reliable?

BACKGROUND

Psychogenic nonepileptic seizures (PNESs) are episodes that resemble epileptic seizures but are of psychological origin. A few studies have attempted to describe different types of PNES as a combination of clinical signs but their validation and robustness have not yet been reached. The aim of this study was to assess the inter-rater reliability (IRR) of five existing clinical PNES classifications.

METHODS

A total of 107 PNESs from 54 patients were retrospectively analyzed independently by two trained epileptologists, who were blinded to each other's findings. The recorded events were grouped according to the five chosen classifications systems. The IRR was measured using a kappa (κ) coefficient for each PNES classification. We also report category-specific κ values.

RESULTS

Our study demonstrated a mild to moderate IRR (κ from 0.44-0.68) for classifying PNES using the 5 proposed classification schemes. Within these classifications, the most reproducible classes are the subjective ones followed by the dialeptic group. Classes based on motor signs are the least reproducible.

CONCLUSION

The IRR for current clinical classifications of PNES was only moderate. The difficulty to analyze motor signs could explain this poor reliability. It is necessary to ensure the reliability of clinical classifications of PNES in order for them to be a relevant tool in clinical practice or to explore correlations in clinical research. Future research would benefit from increased precision of diagnostic criteria specific to each class.

Semiology of psychogenic nonepileptic seizures: An international cross-cultural study

PURPOSE

We compared the semiology of psychogenic nonepileptic seizures (PNES) between patients from the USA and Brazil. This international cross-cultural comparative study may expand understanding of PNES across the borders.

METHODS

We retrospectively investigated all patients with PNES admitted to one epilepsy center in the USA and one in Brazil. We classified their seizures into four classes: generalized motor, akinetic, focal motor, and subjective symptoms. All patients were interviewed by an epileptologist in both countries and were administered psychological assessment measures, including questions about PNES risk factors. For the statistical analyses, we compared patients from the two nations.

RESULTS

Eighty-nine patients (49 from the USA and 40 from Brazil) were studied. Patients from the two countries were not significantly different with regard to sex and age, but patients from Brazil had earlier age at onset (26years vs. 34years; P=0.004) and a significantly greater delay in diagnosis (9.9years vs. 5.6years; P=0.001). Some characteristics of PNES were different between the two groups; patients from the USA had generally more seizure types and more often reported subjective seizures (55% in the USA vs. 10% in Brazil; P=0.0001). Clinical and historical characteristics of the patients were not significantly different.

CONCLUSION

Delay in diagnosis of PNES may represent a major factor in resource-limited countries. Large multicenter cross-cultural studies may reveal subtle but significant cross-cultural differences with respect to the semiological, clinical, and historical aspects of PNES; however, patients with PNES share more similarities than differences.

Semiological classification of psychogenic nonepileptic seizures

PURPOSE

We classified patients with psychogenic nonepileptic seizures (PNESs) according to a newly proposed classification system. Then, we investigated the demographic and clinical differences between various classes of the patients.

METHODS

We retrospectively investigated all patients with PNESs admitted to the Jefferson Comprehensive Epilepsy Center from 2012 through 2016. We classified the patients into four distinct classes: patients with generalized motor seizures, patients with akinetic seizures, patients with focal motor seizures, and patients with seizures with subjective symptoms. All patients were interviewed by a neuropsychologist and were administered psychological assessment measures, including questions about PNES risk factors. For the statistical analyses, we compared patients who had generalized motor seizures with patients who had nonmotor seizures.

RESULTS

Sixty-three patients were studied. Thirty-five (55.6%) patients had generalized motor seizures, 14 (22.2%) had seizures with subjective symptoms, 12 (19%) had akinetic seizures, and two (3.2%) patients had focal motor seizures. Patients with generalized motor seizures (35 patients) demonstrated a trend for later age at onset (p=0.06), more frequently had a history of substance abuse (p=0.001), and more often had loss of responsiveness with their seizures (p=0.04) compared with patients who had nonmotor seizures (26 patients).

CONCLUSION

The recently proposed PNES classification system is useful and practical. This proposed classification of PNESs may address proper diagnosis and provide standardization across future studies. This may also potentially shed light on the etiologic understanding and management of various classes of patients affected with PNESs.

Post-epilepsy surgery psychogenic nonepileptic seizures

OBJECTIVES

We investigated the prevalence of post-epilepsy surgery psychogenic nonepileptic seizures (PNES) in patients with drug-resistant epilepsy and the possible influence of risk factors on these seizures.

METHODS

In this retrospective study, we examined data from all patients with a clinical diagnosis of drug-resistant epilepsy who underwent epilepsy surgery at Graduate Hospital and the Jefferson Comprehensive Epilepsy Center between 1986 and 2016. Postsurgical outcome was identified for up to 15 years after surgery. Diagnosis of PNES was verified in the epilepsy monitoring unit with video-electroencephalography (EEG) ictal recording. Potential associated factors were assessed by comparing patients with or without postoperative PNES.

RESULTS

A total of 1,105 patients were studied; 697 patients had postoperative seizures, and, of these, 27 patients (3.9%) had documented PNES after surgery. A full-scale intelligence quotient (IQ) <80 was significantly associated with post-epilepsy surgery PNES (odds ratio [OR] 2.89, p = 0.007, 95% confidence interval [CI] 1.33-6.29). A history of a preoperative psychiatric diagnosis was also significantly associated with post-epilepsy surgery PNES (OR 4.67, p = 0.0001, 95% CI 2.01-10.82). Other factors were not significantly associated with post-epilepsy surgery PNES.

SIGNIFICANCE

Post-epilepsy surgery PNES should be considered when patients report recurrent seizures after epilepsy surgery. Although these seizures probably occur relatively infrequently, attention to factors such as appearance of new ictal behaviors, a preoperative history of a psychiatric disorder, and a low full-scale IQ should raise suspicion and lead to appropriate diagnostic measures.