Heart Rate Variability Parameters During Psychogenic Non-epileptic Seizures: Comparison Between Patients With Pure PNES and Comorbid Epilepsy

Re-PROGRAM: The evaluation of a brief intervention program for patients with functional seizures in an outpatient hospital setting

OBJECTIVE

Functional seizures (FS) account for 20%-25% of referrals to specialist epilepsy clinics. They are associated with major disability, increased mortality, and frequent and costly health care use. Current guidelines emphasize the importance of implementing clinical pathways to coordinate and deliver effective treatment, but there are few targeted evidence-based interventions that reliably improve patient outcomes, and treatment resources are limited. We conducted a retrospective evaluation of Re-PROGRAM, a novel, brief intervention for functional seizure patients, to assess its feasibility in an outpatient setting.

METHODS

Twenty-nine patients with FS undertook Re-PROGRAM between August 2020 and January 2022 at the Alfred Hospital Functional Seizures Clinic, Melbourne, Australia. The intervention comprised five 60-90-min consecutive weekly appointments via telehealth, where psychologists engaged patients in a structured program of seizure management skills, lifestyle modification, and behavioral activation strategies. Following the intervention, patient feedback was collected in routine clinical follow-up as well as with a 24-item self-report pre-/postintervention comparison questionnaire.

RESULTS

All 29 patients who enrolled in Re-PROGRAM completed the scheduled sessions. Of those who returned the postintervention questionnaire (n = 16), 15 reported a reduction in seizure frequency. Four patients were lost to follow-up. Of the remaining nine, eight reported seizure frequency reduction during clinical follow-up. Qualitative analysis of the feedback revealed the majority of patients reported reduced seizure duration, intensity, and bothersomeness, and patients felt improvements in their sense of control over seizures, confidence to use seizure control strategies, assertive communication, problem solving, coping skills, relationships with others, and their day-to-day functioning.

SIGNIFICANCE

This retrospective evaluation demonstrates the feasibility and acceptability of Re-PROGRAM as a brief intervention for individuals diagnosed with FS delivered in a clinical outpatient setting and warrants further investigation in larger scale, randomized controlled studies.

Heartbeat evoked potentials and autonomic arousal during dissociative seizures: insights from electrophysiology and neuroimaging

Introduction

Dissociative seizures often occur in the context of dysregulated affective arousal and entail dissociative symptoms such as a disintegration of bodily awareness. However, the interplay between affective arousal and changes in interoceptive processing at the onset of dissociative seizures is not well understood.

Methods

Using retrospective routine data obtained from video-electroencephalography telemetry in a university hospital epilepsy monitoring unit, we investigate ictal changes in cardiac indices of autonomic arousal and heartbeat evoked potentials (HEPs) in 24 patients with dissociative seizures.

Results

Results show autonomic arousal during seizures with increased heart rate and a shift towards sympathetic activity. Compared with baseline, ictal HEP amplitudes over central and right prefrontal electrodes (F8, Fz) were significantly less pronounced during seizures, suggesting diminished cortical representation of interoceptive information. Significant correlations between heart rate variability measures and HEPs were observed at baseline, with more sympathetic and less parasympathetic activity related to less pronounced HEPs. Interestingly, these relationships weakened during seizures, suggesting a disintegration of autonomic arousal and interoceptive processing during dissociative seizures. In a subgroup of 16 patients, MRI-based cortical thickness analysis found a correlation with HEP amplitudes in the left somatosensory association cortex.

Conclusions

These findings possibly represent an electrophysiological hint of how autonomic arousal could negatively impact bodily awareness in dissociative seizures, and how these processes might be related to underlying brain structure.

Content or context? A study protocol for a three-arm parallel randomised controlled trial of Re-PROGRAM, a brief internet-based intervention for patients with functional seizures

INTRODUCTION

Functional seizures (FS) mimic epilepsy but are not caused by epileptic electrical activity in the brain and are believed to have a psychological origin. There is a well-documented gap between the needs of patients with FS and available therapeutic resources. While there is potential for reducing seizure burden in patients via psychosocial intervention, there is no evidence-based care pathway or consistent availability of treatment and no effective pharmacological treatment. The objective of this study is to investigate the clinical efficacy and tolerability of a novel internet-based intervention in reducing seizure frequency.

METHODS AND ANALYSIS

A 3-arm parallel randomised controlled trial will compare the efficacy of brief guided internet-based therapy to unguided internet-based therapy and to standard care. Approximately 100 participants with FS will be recruited, with diagnostic criteria based on gold standard video-electroencephalogram (v-EEG) monitoring; patients will be randomly assigned to one of the three study arms. The primary study outcome will be FS frequency at 6 weeks and at follow-up (6 and 12 months) compared with baseline. Seizure frequency will be modelled using Poisson regression. Secondary outcomes include psychosocial functioning, healthcare resource usage, anxiety, depression, somatisation and life impact. Between-group differences will be evaluated using analysis of variance. Analysis of covariance will estimate within-group changes on secondary outcomes. Cognitive and psychological factors will be used as predictors of seizure reduction in exploratory analyses. A qualitative survey using a semi-structured interview will use thematic analyses to explore participants' treatment experiences, their impressions of FS management and perceived mechanisms for change.

ETHICS AND DISSEMINATION

The study was approved by the Human Research and Ethics Committee of the Alfred Hospital Human Research Ethics Committee as part of the Australian Multisite Ethics approval system. Results of the study will be presented at national and international conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ACTRN12622000262707.

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 peri‑ictal 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.

Differentiation of epilepsy and psychogenic nonepileptic events based on body fluid characteristics

OBJECTIVE

Differential diagnosis between epileptic seizures and psychogenic nonepileptic events (PNEEs) is a worldwide problem for neurologists. The present study aims to identify important characteristics from body fluid tests and develop diagnostic models based on them.

METHODS

This is a register-based observational study in patients with a diagnosis of epilepsy or PNEEs at West China Hospital of Sichuan University. Data from body fluid tests between 2009 and 2019 were used as a training set. We constructed models with a random forest approach in eight training subsets divided by sex and categories of tests, including electrolyte, blood cell, metabolism, and urine tests. Then, we collected data prospectively from patients between 2020 and 2022 to validate our models and calculated the relative importance of characteristics in robust models. Selected characteristics were finally analyzed with multiple logistic regression to establish nomograms.

RESULTS

A total of 388 patients, including 218 with epilepsy and 170 with PNEEs, were studied. The AUROCs of random forest models of electrolyte and urine tests in the validation phase achieved 80.0% and 79.0%, respectively. Carbon dioxide combining power, anion gap, potassium, calcium, and chlorine in electrolyte tests and specific gravity, pH, and conductivity in urine tests were selected for the logistic regression analysis. C (ROC) of the electrolyte and urine diagnostic nomograms achieved 0.79 and 0.85, respectively.

SIGNIFICANCE

The application of routine indicators of serum and urine may help in the more accurate identification of epileptic and PNEEs.

A systems biology approach for discovering the cellular and molecular aspects of psychogenic non-epileptic seizure

Objectives

Psychogenic non-epileptic seizure (PNES) is the most common non-epileptic disorder in patients referring to epilepsy centers. Contrary to common beliefs about the disease's harmlessness, the death rate of PNES patients is similar to drug-resistant epilepsy. Meanwhile, the molecular pathomechanism of PNES is unknown with very limited related research. Thus, the aim of this in silico study was to find different proteins and hormones associated with PNES via a systems biology approach.

Methods

Different bioinformatics databases and literature review were used to find proteins associated with PNES. The protein-hormone interaction network of PNES was constructed to discover its most influential compartments. The pathways associated with PNES pathomechanism were found by enrichment analysis of the identified proteins. Besides, the relationship between PNES-related molecules and psychiatric diseases was discovered, and the brain regions that could express altered levels of blood proteins were discovered.

Results

Eight genes and three hormones were found associated with PNES through the review process. Proopiomelanocortin (POMC), neuropeptide Y (NPY), cortisol, norepinephrine, and brain-derived neurotrophic factor (BDNF) were identified to have a high impact on the disease pathogenesis network. Moreover, activation of Janus kinase-signaling transducer and activator of transcription (JAK-STAT) and JAK, as well as signaling of growth hormone receptor, phosphatidylinositol 3-kinase /protein kinase B (PI3K/AKT), and neurotrophin were found associated with PNES molecular mechanism. Several psychiatric diseases such as depression, schizophrenia, and alcohol-related disorders were shown to be associated with PNES predominantly through signaling molecules.

Significance

This study was the first to gather the biochemicals associated with PNES. Multiple components and pathways and several psychiatric diseases associated with PNES, and some brain regions that could be altered during PNES were suggested, which should be confirmed in further studies. Altogether, these findings could be used in future molecular research on PNES patients.

Entropy Measures of Electroencephalograms towards the Diagnosis of Psychogenic Non-Epileptic Seizures

Psychogenic non-epileptic seizures (PNES) may resemble epileptic seizures but are not caused by epileptic activity. However, the analysis of electroencephalogram (EEG) signals with entropy algorithms could help identify patterns that differentiate PNES and epilepsy. Furthermore, the use of machine learning could reduce the current diagnosis costs by automating classification. The current study extracted the approximate sample, spectral, singular value decomposition, and Renyi entropies from interictal EEGs and electrocardiograms (ECG)s of 48 PNES and 29 epilepsy subjects in the broad, delta, theta, alpha, beta, and gamma frequency bands. Each feature-band pair was classified by a support vector machine (SVM), k-nearest neighbour (kNN), random forest (RF), and gradient boosting machine (GBM). In most cases, the broad band returned higher accuracy, gamma returned the lowest, and combining the six bands together improved classifier performance. The Renyi entropy was the best feature and returned high accuracy in every band. The highest balanced accuracy, 95.03%, was obtained by the kNN with Renyi entropy and combining all bands except broad. This analysis showed that entropy measures can differentiate between interictal PNES and epilepsy with high accuracy, and improved performances indicate that combining bands is an effective improvement for diagnosing PNES from EEGs and ECGs.

Psychogenic nonepileptic seizures: Are they a freeze reaction?

Psychogenic nonepileptic seizures (PNES) clinically resemble epileptic seizures (ES) but lack epileptic activity at the time of the seizure and are also not due to any other pathophysiological disorder. The integrative cognitive model (ICM) suggests that PNES is an automatic reaction generated from distorted memory and is perceived as uncontrollable and unwanted. Furthermore, the ICM model implies that a PNES event occurs due to an external or internal cue. Intrigued by this assumption, we wanted to examine why a PNES event occurs at a particular moment by investigating the pre-ictal behavior. This study is a retrospective study. We included all patients diagnosed with PNES or ES admitted to our long-term video-EEG monitoring unit (LTVEM) between 01/01/2018 and 30/08/2020. Using thorough video analysis, we checked the patient's state at the onset of the event and looked back to see what the patient was doing before the event onset. We defined 4 types of pre-ictal behavior A. Inactivity. B. Environment arrangement c. Other. D. No apparent pre-ictal behavior. Thirty patients with PNES and 30 patients with ES were included in the study. In total, 46 PNES events and 56 ES events were recorded and analyzed. In 33 /46 PNES seizures (72%), a type A, A + B or C pre-ictal behavior was observed compared to 1/56 ES (1.78%) with type A pre-ictal behavior. All other pre-ictal behavior in the ES group were of type D. Patients with PNES have a unique pre-ictal behavior before most PNES events with motor manifestations. Since the pre-ictal behavior consists mainly of inactivity, we believe it may imply that PNES represents a freeze reaction or a reconstruction of a freeze reaction.

Echo state network models for nonlinear Granger causality

While Granger causality (GC) has been often employed in network neuroscience, most GC applications are based on linear multivariate autoregressive (MVAR) models. However, real-life systems like biological networks exhibit notable nonlinear behaviour, hence undermining the validity of MVAR-based GC (MVAR-GC). Most nonlinear GC estimators only cater for additive nonlinearities or, alternatively, are based on recurrent neural networks or long short-term memory networks, which present considerable training difficulties and tailoring needs. We reformulate the GC framework in terms of echo-state networks-based models for arbitrarily complex networks, and characterize its ability to capture nonlinear causal relations in a network of noisy Duffing oscillators, showing a net advantage of echo state GC (ES-GC) in detecting nonlinear, causal links. We then explore the structure of ES-GC networks in the human brain employing functional MRI data from 1003 healthy subjects drawn from the human connectome project, demonstrating the existence of previously unknown directed within-brain interactions. In addition, we examine joint brain-heart signals in 15 subjects where we explore directed interaction between brain networks and central vagal cardiac control in order to investigate the so-called central autonomic network in a causal manner. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Shame in patients with psychogenic nonepileptic seizure: A narrative review

Psychogenic Nonepileptic Seizures (PNES) have been linked to dysregulated emotions and arousal. However, the question which emotions may be most relevant has received much less attention. In this multidisciplinary narrative review, we argue that the self-conscious emotion of shame is likely to be of particular importance for PNES. We summarize current concepts of the development of shame processing and its relationship with other emotional states. We demonstrate the potential of acute shame to cause a sudden disruption of normal cognitive function and trigger powerful behavioral, cognitive, physiological and secondary emotional responses which closely resemble key components of PNES. These responses may lead to the development of shame avoidance strategies which can become disabling in themselves. We discuss how excessive shame proneness and shame dysregulation are linked to several psychopathologies often associated with PNES (including depression and PTSD) and how they may predispose to, precipitate and perpetuate PNES disorders, not least by interacting with stigma. We consider current knowledge of the neurobiological underpinnings of shame and PNES. We explore how shame could be the link between PNES and a heterogeneous range of possible etiological factors, and how it may link historical aversive experiences with individual PNES events occurring much later and without apparent external trigger. We argue that, in view of the potential direct links between shame and PNES, the well-documented associations of shame with common comorbidities of this seizure disorder and the well-characterized relationship between chronic shame and stigma, there is a compelling case to pay greater attention to shame in relation to PNES. Its role in the treatment of patients with PNES is discussed in a separate, linked review incorporating case vignettes to highlight the complex interactions of different but interlinked shame-related issues in individual patients.

Mood Disturbances, Anxiety, and Impact on Quality of Life in Patients Admitted to Epilepsy Monitoring Units

Introduction: The overall combined prevalence of anxiety and depression in patients with epilepsy has been estimated at 20.2 and 22.9%, respectively, and is considered more severe in drug-refractory epilepsy. Patients admitted to epilepsy monitoring units constitute a particular group. Also, patients with psychogenic non-epileptic seizures can reach more than 20% of all admissions. This study aims to characterize these symptoms in a large cohort of patients admitted for evaluation in a tertiary epilepsy center.

Materials and Methods: The study was conducted among 493 consecutive patients (age: 38.78 ± 12.7, 57% females) admitted for long-term video EEG from January 2013 to February 2021. Demographic, clinical, and mood disorder patients' data were collected. Anxiety and depression symptoms were assessed through the Hospital Anxiety Depression Scale (HADS-A and HADS-D), the State Trait Anxiety Inventory (STAI), and Beck Depression Inventory (BDI-II). Quality of life was determined using the QOLIE-10. Patients were divided into three groups: patients with epilepsy (n = 395), psychogenic non-epileptic seizures (PNES) (n = 56), and combined (n = 33). A univariate and multivariate regression analysis was performed for variables associated with quality of life.

Results: Of 493 patients, 45.0% had structural etiology, and considering epilepsy classification, 43.6% were of temporal lobe origin. In addition, 32.45% of patients had a previous psychiatric history, 49.9% of patients had depressive symptoms in BDI, and 30.9% according to HADS-D; 56.42 and 52.63% of patients presented pathological anxiety scores in STAI-T and STAI-S, respectively; and 44.78% according to HADS-A. PNES and combined groups revealed a higher incidence of pathologic BDI scores (64.29 and 78.79%, p < 0.001) as well as pathologic HADS-A scores (p = 0.001). Anxiety and depression pathologic results are more prevalent in females, HADS-A (females = 50.7%, males = 36.8%; p = 0.0027) and BDI > 13 (females = 56.6%, males = 41.0%; p = 0.0006). QOLIE-10 showed that 71% of the patients had their quality of life affected with significantly higher scores in the combined group than in the epilepsy and PNES groups (p = 0.0015).

Conclusions: Subjective anxiety, depression, and reduced quality of life are highly prevalent in patients with refractory epilepsy. These symptoms are more evident when PNES are associated with epilepsy and more severe among female patients. Most of the cases were not previously diagnosed. These factors should be considered in everyday clinical practice, and specific approaches might be adapted depending on the patient's profile.

Autonomic, Endocrine, and Inflammation Profiles in Functional Neurological Disorder: A Systematic Review and Meta-Analysis

OBJECTIVE

Functional neurological disorder (FND) is a core neuropsychiatric condition. To date, promising yet inconsistently identified neural circuit profiles have been observed in patients with FND, suggesting that gaps remain in our systems-level neurobiological understanding. As such, other important physiological variables, including autonomic, endocrine, and inflammation findings, need to be contextualized for a more complete mechanistic picture.

METHODS

The investigators conducted a systematic review and meta-analysis of available case-control and cohort studies of FND. PubMed, PsycINFO, and Embase databases were searched for studies from January 1, 1900, to September 1, 2020, that investigated autonomic, endocrine, and inflammation markers in patients with FND. Sixty-six of 2,056 screened records were included in the review, representing 1,699 patients; data from 20 articles were used in the meta-analysis.

RESULTS

Findings revealed that children and adolescents with FND, compared with healthy control subjects (HCs), have increased resting heart rate (HR); there is also a tendency toward reduced resting HR variability in patients with FND across the lifespan compared with HCs. In adults, peri-ictal HR differentiated patients with functional seizures from those with epileptic seizures. Other autonomic and endocrine profiles for patients with FND were heterogeneous, with several studies highlighting the importance of individual differences.

CONCLUSIONS

Inflammation research in FND remains in its early stages. Moving forward, there is a need for the use of larger sample sizes to consider the complex interplay between functional neurological symptoms and behavioral, psychological, autonomic, endocrine, inflammation, neuroimaging, and epigenetic/genetic data. More research is also needed to determine whether FND is mechanistically (and etiologically) similar or distinct across phenotypes.

Can Treating Patients With PNES Lower the Risk of Sudden Unexpected Death?

Mortality in Patients With Psychogenic Nonepileptic Seizures

Nightscales R, McCartney L, Auvrez C, et al. Neurology. 2020;95(6):e643-e652. doi:10.1212/WNL.0000000000009855

Objective:

To investigate the hypothesis that patients diagnosed with psychogenic nonepileptic seizures (PNES) on video-EEG monitoring (VEM) have increased mortality by comparison to the general population.

Methods:

This retrospective cohort study included patients evaluated in VEM units of 3 tertiary hospitals in Melbourne, Australia, between January 1, 1995, and December 31, 2015. Diagnosis was based on consensus opinion of experienced epileptologists and neuropsychiatrists at each hospital. Mortality was determined in patients diagnosed with PNES, epilepsy, or both conditions by linkage to the Australian National Death Index. Lifetime history of psychiatric disorders in PNES was determined from formal neuropsychiatric reports.

Results:

A total of 5508 patients underwent VEM. A total of 674 (12.2%) were diagnosed with PNES, 3064 (55.6%) with epilepsy, 175 (3.2%) with both conditions, and 1595 (29.0%) received other diagnoses or had no diagnosis made. The standardized mortality ratio (SMR) of patients diagnosed with PNES was 2.5 (95% CI: 2.0-3.3). Those younger than 30 had an 8-fold higher risk of death (95% CI: 3.4-19.8). Direct comparison revealed no significant difference in mortality rate between diagnostic groups. Among deaths in patients diagnosed with PNES (n = 55), external causes contributed 18%, with 20% of deaths in those younger than 50 years attributed to suicide, and “epilepsy” was recorded as the cause of death in 24%.

Conclusions:

Patients diagnosed with PNES have a SMR 2.5 times above the general population, dying at a rate comparable to those with drug-resistant epilepsy. This emphasizes the importance of prompt diagnosis, identification of risk factors, and implementation of appropriate strategies to prevent potential avoidable deaths.