Gaps in treatment of epileptic seizures in a Zambian rural area.

BACKGROUND: Epilepsy is a multifactorial neurological disorder, including parasitic infections of the brain such as neurocysticercosis (NCC). People with epileptic seizures (PWES) in low and middle-income countries often do not receive appropriate treatment, which besides epileptic seizures, may also lead to reduced quality of life and possibly death. The objective of this study was to describe gaps in treatment of epileptic seizures in a Zambian rural area. METHODS: A cross-sectional study was conducted in Sinda district of Zambia between August and October 2018. PWES identified from clinic records and with the help of community healthcare workers were recruited. Two questionnaires, one to PWES and the other to local healthcare workers, were administered to describe the treatment gap. RESULTS: A total of 146 PWES and 43 healthcare workers were interviewed. Of the 146 PWES, 131 had taken anti-seizure medication (ASM) at some point since their seizure onset, of which 49.6% were on current treatment. Only 18.3% were on continuous ASM, an overall treatment gap of 83.6%. Over 55% of healthcare workers did not know the relationship between epilepsy and NCC. The risk factors associated with lack of appropriate treatment were stock-outs of ASMs, lack of diagnostic equipment, poor patient follow-up, and PWES opting for traditional medicine. CONCLUSION: The treatment gap is substantial in Sinda district. The causes are multifactorial, involving shortcomings at the level of healthcare facilities, communities, and individuals. Directed training of healthcare workers and significant improvements in the supply and dispensing of ASMs will be key in substantially reducing the gap.

Characteristics of electroencephalogram changes and correlation with seizures in hospitalised patients.

INTRODUCTION: Electroencephalogram (EEG) is an important investigational tool that is widely used in the hospital settings for numerous indications. The aim was to determine factors associated with abnormal EEG and its clinical correlations in hospitalised patients. MATERIALS AND METHODS: Patients with at least one EEG recording were recruited. The EEG and clinical data were collated. RESULTS: Two hundred and fifty patients underwent EEG and 154 (61.6%) were found to have abnormal EEG. The abnormal changes consist of theta activity (79,31.6%), delta activity (20, 8%), focal discharges (41,16.4%) and generalised discharges (14, 5.6%). Older patients had 3.481 higher risk for EEG abnormalities, p=0.001. Patients who had focal seizures had 2.240 higher risk of having EEG abnormalities, p<0.001. Low protein level was a risk for EEG abnormalities, p=0.003. CONCLUSION: This study emphasised that an abnormal EEG remains a useful tool in determining the likelihood for seizures in a hospital setting. The risk factors for EEG abnormality in hospitalised patients were age, focal seizures and low protein level. The EEG may have an important role as part of the workup in hospitalised patients to aid the clinician to tailor their management in a holistic manner.

Neuromonitoring in neonatal critical care part II: extremely premature infants and critically ill neonates.

Neonatal intensive care has expanded from cardiorespiratory care to a holistic approach emphasizing brain health. To best understand and monitor brain function and physiology in the neonatal intensive care unit (NICU), the most commonly used tools are amplitude-integrated EEG, full multichannel continuous EEG, and near-infrared spectroscopy. Each of these modalities has unique characteristics and functions. While some of these tools have been the subject of expert consensus statements or guidelines, there is no overarching agreement on the optimal approach to neuromonitoring in the NICU. This work reviews current evidence to assist decision making for the best utilization of these neuromonitoring tools to promote neuroprotective care in extremely premature infants and in critically ill neonates. Neuromonitoring approaches in neonatal encephalopathy and neonates with possible seizures are discussed separately in the companion paper. IMPACT: For extremely premature infants, NIRS monitoring has a potential role in individualized brain-oriented care, and selective use of aEEG and cEEG can assist in seizure detection and prognostication. For critically ill neonates, NIRS can monitor cerebral perfusion, oxygen delivery, and extraction associated with disease processes as well as respiratory and hypodynamic management. Selective use of aEEG and cEEG is important in those with a high risk of seizures and brain injury. Continuous multimodal monitoring as well as monitoring of sleep, sleep-wake cycling, and autonomic nervous system have a promising role in neonatal neurocritical care.

Status epilepticus in pregnancy.

Status epilepticus is a frequent neurological emergency associated with a case fatality of about 10-15% depending on age, cause, and other factors, and a high burden for patients, caregivers, and society. In pregnancy, it can occur in two different clinical constellations: (1) In women with a history of epilepsy and (2) as new onset status epilepticus in pregnancy (NOSEP). Both entities are relatively rare but differ in terms of etiology. Here we describe the epidemiology, etiologies, diagnosis, clinical course with the maternal and fetal outcome, and the suggested management strategies for either manifestation. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.

Nonpharmacologic Interventions and Seizure Frequency in Patients With Psychogenic Nonepileptic Seizures: An Integrative Review.

BACKGROUND: Psychogenic nonepileptic seizures (PNES) pose a heavy burden on patients' lives and the health care system. The symptoms of PNES are often debilitating and cause high rates of disability and poor quality of life. Many treatment options are available, but there is no clear consensus on best practices. AIM: To critique and synthesize the current literature on nonpharmacologic interventions and effects on seizure frequency in patients with PNES. METHODS: An integrative review guided by the Whittemore and Knafl approach. RESULTS: The review included 24 studies published from 2010 to 2020. Interventions for PNES included individualized psychotherapies, group therapies, multimodal psychotherapies, self-help therapies, and complementary and alternative medicine therapies. Individual psychotherapies such as cognitive behavioral therapy and psychoeducation were the most used treatment modalities. The most effective treatments for seizure frequency reduction were those that included multiple psychotherapy sessions with a health care provider and covered multiple domains (e.g., understanding of diagnosis, identifying triggers, and developing effective coping strategies). CONCLUSIONS: Seizure frequency can be reduced in patients with PNES with multiple nonpharmacologic interventions. However, seizure frequency is not considered a comprehensive outcome measure and provides little insight into other important life domains. Further research is needed on nonpharmacologic interventions for PNES and effects on other areas of life such as sleep, employment status, global functioning, and self-efficacy.

Epidemiology, methods of diagnosis, and clinical management of patients with arginase 1 deficiency (ARG1-D): A systematic review.

BACKGROUND: Arginase 1 Deficiency (ARG1-D) is a rare, progressive, metabolic disorder that is characterized by devastating manifestations driven by elevated plasma arginine levels. It typically presents in early childhood with spasticity (predominately affecting the lower limbs), mobility impairment, seizures, developmental delay, and intellectual disability. This systematic review aims to identify and describe the published evidence outlining the epidemiology, diagnosis methods, measures of disease progression, clinical management, and outcomes for ARG1-D patients. METHODS: A comprehensive literature search across multiple databases such as MEDLINE, Embase, and a review of clinical studies in ClinicalTrials.gov (with results reported) was carried out per PRISMA guidelines on 20 April 2020 with no date restriction. Pre-defined eligibility criteria were used to identify studies with data specific to patients with ARG1-D. Two independent reviewers screened records and extracted data from included studies. Quality was assessed using the modified Newcastle-Ottawa Scale for non-comparative studies. RESULTS: Overall, 55 records reporting 40 completed studies and 3 ongoing studies were included. Ten studies reported the prevalence of ARG1-D in the general population, with a median of 1 in 1,000,000. Frequently reported diagnostic methods included genetic testing, plasma arginine levels, and red blood cell arginase activity. However, routine newborn screening is not universally available, and lack of disease awareness may prevent early diagnosis or lead to misdiagnosis, as the disease has overlapping symptomology with other diseases, such as cerebral palsy. Common manifestations reported at time of diagnosis and assessed for disease progression included spasticity (predominately affecting the lower limbs), mobility impairment, developmental delay, intellectual disability, and seizures. Severe dietary protein restriction, essential amino acid supplementation, and nitrogen scavenger administration were the most commonly reported treatments among patients with ARG1-D. Only a few studies reported meaningful clinical outcomes of these interventions on intellectual disability, motor function and adaptive behavior assessment, hospitalization, or death. The overall quality of included studies was assessed as good according to the Newcastle-Ottawa Scale. CONCLUSIONS: Although ARG1-D is a rare disease, published evidence demonstrates a high burden of disease for patients. The current standard of care is ineffective at preventing disease progression. There remains a clear need for new treatment options as well as improved access to diagnostics and disease awareness to detect and initiate treatment before the onset of clinical manifestations to potentially enable more normal development, improve symptomatology, or prevent disease progression.

Treatment of Psychogenic Nonepileptic Seizures.

PURPOSE OF REVIEW: Psychogenic nonepileptic seizures (PNES) are the most common Functional Neurological Disorder/Conversion Disorder subtype. Significant advances have been made related to diagnosis, neurobiology, and treatment. In this review, we summarize updates in diagnosis and management over the past 3 years. RECENT FINDINGS: Although evidence is mixed for the treatment of PNES, psychotherapeutic modalities remain a powerful instrument to empower patients and reduce seizures. A multidisciplinary, holistic approach is beneficial. While seizure freedom in all patients may not be the achieved endpoint in this chronic, paroxysmal disorder, quality of life can be improved with treatment. Additional treatment modalities and further research are needed for patients who are refractory to current treatment. Evidence-based therapies exist for PNES, and recent findings represent an increased understanding of the clinical and neurophysiologic aspects of PNES.

Forecasting seizure clusters from chronic ambulatory electrocorticography.

Seizure clusters are seizures that occur in rapid succession during periods of heightened seizure risk and are associated with substantial morbidity and sudden unexpected death in epilepsy. The objective of this feasibility study was to evaluate the performance of a novel seizure cluster forecasting algorithm. Chronic ambulatory electrocorticography recorded over an average of 38 months in 10 subjects with drug-resistant epilepsies was analyzed pseudoprospectively by dividing data into training (first 85%) and validation periods. For each subject, the probability of seizure clustering, derived from the Kolmogorov-Smirnov statistic using a novel algorithm, was forecasted in the validation period using individualized autoregressive models that were optimized from training data. The primary outcome of this study was the mean absolute scaled error (MASE) of 1-day horizon forecasts. From 10 subjects, 394 ± 142 (mean ± SD) electrocorticography-based seizure events were extracted for analysis, representing a span of 38 ± 27 months of recording. MASE across all subjects was .74 ± .09, .78 ± .09, and .83 ± .07 at .5-, 1-, and 2-day horizons. The feasibility study demonstrates that seizure clusters are quasiperiodic and can be forecasted to clinically meaningful horizons. Pending validation in larger cohorts, the forecasting approach described herein may herald chronotherapy during imminent heightened seizure vulnerability.

Fluctuations in EEG band power at subject-specific timescales over minutes to days explain changes in seizure evolutions.

Epilepsy is recognised as a dynamic disease, where both seizure susceptibility and seizure characteristics themselves change over time. Specifically, we recently quantified the variable electrographic spatio-temporal seizure evolutions that exist within individual patients. This variability appears to follow subject-specific circadian, or longer, timescale modulations. It is therefore important to know whether continuously recorded interictaliEEG features can capture signatures of these modulations over different timescales. In this study, we analyse continuous intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over timescales ranging from minutes up to 12 days. As expected and in agreement with previous studies, we find that all subjects show a circadian fluctuation in their iEEG band power. We additionally detect other fluctuations of similar magnitude on subject-specific timescales. Importantly, we find that a combination of these fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level. These results suggest that subject-specific fluctuations in iEEG band power over timescales of minutes to days may serve as markers of seizure modulating processes. We hope that future study can link these detected fluctuations to their biological driver(s). There is a critical need to better understand seizure modulating processes, as this will enable the development of novel treatment strategies that could minimise the seizure spread, duration or severity and therefore the clinical impact of seizures.

Anterior nucleus of the thalamus seizure detection in ambulatory humans.

There is a paucity of data to guide anterior nucleus of the thalamus (ANT) deep brain stimulation (DBS) with brain sensing. The clinical Medtronic Percept DBS device provides constrained brain sensing power within a frequency band (power-in-band [PIB]), recorded in 10-min averaged increments. Here, four patients with temporal lobe epilepsy were implanted with an investigational device providing full bandwidth chronic intracranial electroencephalogram (cEEG) from bilateral ANT and hippocampus (Hc). ANT PIB-based seizure detection was assessed. Detection parameters were cEEG PIB center frequency, bandwidth, and epoch duration. Performance was evaluated against epileptologist-confirmed Hc seizures, and assessed by area under the precision-recall curve (PR-AUC). Data included 99 days of cEEG, and 20, 278, 3, and 18 Hc seizures for Subjects 1-4. The best detector had 7-Hz center frequency, 5-Hz band width, and 10-s epoch duration (group PR-AUC = .90), with 75% sensitivity and .38 false alarms per day for Subject 1, and 100% and .0 for Subjects 3 and 4. Hc seizures in Subject 2 did not propagate to ANT. The relative change of ANT PIB was maximal ipsilateral to seizure onset for all detected seizures. Chronic ANT and Hc recordings provide direct guidance for ANT DBS with brain sensing.

Epileptic Seizure Detection on an Ultra-Low-Power Embedded RISC-V Processor Using a Convolutional Neural Network.

The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either by drug release or electrostimulation is a highly attractive option. For such implantable medical devices, efficient and low energy consumption, small size, and efficient processing architectures are essential. To meet these requirements, epileptic seizure detection by analysis and classification of brain signals with a convolutional neural network (CNN) is an attractive approach. This work presents a CNN for epileptic seizure detection capable of running on an ultra-low-power microprocessor. The CNN is implemented and optimized in MATLAB. In addition, the CNN is also implemented on a GAP8 microprocessor with RISC-V architecture. The training, optimization, and evaluation of the proposed CNN are based on the CHB-MIT dataset. The CNN reaches a median sensitivity of 90% and a very high specificity over 99% corresponding to a median false positive rate of 6.8 s per hour. After implementation of the CNN on the microcontroller, a sensitivity of 85% is reached. The classification of 1 s of EEG data takes t=35 ms and consumes an average power of P≈140 µW. The proposed detector outperforms related approaches in terms of power consumption by a factor of 6. The universal applicability of the proposed CNN based detector is verified with recording of epileptic rats. This results enable the design of future medical devices for epilepsy treatment.

Clinico-laboratory characteristics and outcome of patients with eucalyptus oil-induced/provoked seizures: A case series and systematic review of the published patients.

Seizures triggered by skin application, inhalation or ingestion of over-the-counter medications containing eucalyptus oil are known. We report five children who suffered likewise. We made a systematic search for all reported cases and performed a pooled analysis to provide a comprehensive estimate of the type of seizures, their management and outcome. In 110 cases (49 children), inhalational use was the most predominant, generalised tonic-clonic (the commonest semiology) and levetiracetam was the most common anti-convulsant treatment used. Most cases had an uneventful recovery. Adults were less likely to have prolonged and multiple seizures, requiring intensive care or mechanical ventilation.

Oxygen toxicity seizure mimics.

INTRODUCTION: Oxygen toxicity seizures (OTS) are a well-recognised complication of hyperbaric oxygen treatment (HBOT). As such, seizure-like activity during HBOT is usually presumed to be a result of central nervous system oxygen toxicity (CNS-OT). Four cases are reported here where causes other than CNS-OT were determined as being the likely cause of the seizure; causes we have labelled 'OTS mimics'. Through review of the current literature, and our hyperbaric medicine unit's experience to date, we aimed to highlight the relevance of these OTS mimics, as the potential for significant morbidity and mortality exists with incorrect diagnoses. METHODS: A retrospective review of the medical records of all patients treated at the Fiona Stanley Hospital and Fremantle Hospital hyperbaric medicine units who had a seizure during HBOT between November 1989 and June 2020. These events were reviewed to determine whether causes for seizures other than oxygen toxicity were evident. RESULTS: Four OTS mimics were identified: posterior reversible encephalopathy syndrome, pethidine toxicity, previous subarachnoid haemorrhage with resultant epilepsy, and severe hypoglycaemia. CONCLUSIONS: This case series highlights the need for caution when diagnosing an apparent OTS. Multiple conditions may mimic the signs and symptoms of oxygen toxicity. This creates scope for misdiagnosis, with potential for consequent morbidity and mortality. A pragmatic approach is necessary to any patient exhibiting seizure-like activity during HBOT, with suspicion for other underlying pathologies.

The inside experience of epilepsy: An essay about the importance of subjectivity.

This essay addresses three aspects of the inside experience of epilepsy, i) the high semiological significance of subjective seizure symptoms, ii) the therapeutic consequences, both positive and negative, of subjective seizure experiences, and iii) the importance of recognizing the patient as the 'inside expert' of epilepsy. Subjective symptoms are often not spontaneously reported but ignoring them may be associated with serious risks. They can be experienced as neutral, negative or positive, and this can have important consequences for therapy. Only patients have full and first-hand knowledge of subjective symptoms but an understanding of these symptoms and an adequate response to them requires expert assistance. The inside and outside views of seizures are different but of equal importance. To get the full picture, both are needed to supplement each other.

Machine learning approach to detect focal-onset seizures in the human anterior nucleus of the thalamus.

Objective.There is an unmet need to develop seizure detection algorithms from brain regions outside the epileptogenic cortex. The study aimed to demonstrate the feasibility of classifying seizures and interictal states from local field potentials (LFPs) recorded from the human thalamus-a subcortical region remote to the epileptogenic cortex. We tested the hypothesis that spectral and entropy-based features extracted from LFPs recorded from the anterior nucleus of the thalamus (ANT) can distinguish its state of ictal recruitment from other interictal states (including awake, sleep).Approach. Two supervised machine learning tools (random forest and the random kitchen sink) were used to evaluate the performance of spectral (discrete wavelet transform-DWT), and time-domain (multiscale entropy-MSE) features in classifying seizures from interictal states in patients undergoing stereo-electroencephalography (EEG) evaluation for epilepsy surgery. Under the supervision of IRB, field potentials were recorded from the ANT in consenting adults with drug-resistant temporal lobe epilepsy. Seizures were confirmed in the ANT using line-length and visual inspection. Wilcoxon rank-sum method was used to test the differences in spectral patterns between seizure and interictal (awake and sleep) states.Main results.79 seizures (10 patients) and 158 segments (approx. 4 h) of interictal stereo-EEG data were analyzed. The mean seizure detection latencies with line length in the ANT varied between seizure types (range 5-34 s). However, the DWT and MSE in the ANT showed significant changes for all seizure types within the first 20 s after seizure onset. The random forest (accuracy 93.9% and false-positive 4.6%) and the random kitchen sink (accuracy 97.3% and false-positive 1.8%) classified seizures and interictal states.Significance.These results suggest that features extracted from the thalamic LFPs can be trained to detect seizures that can be used for monitoring seizure counts and for closed-loop seizure abortive interventions.

Cenobamate (XCOPRI): Can preclinical and clinical evidence provide insight into its mechanism of action?

Approximately one-third of people living with epilepsy are unable to obtain seizure control with the currently marketed antiseizure medications (ASMs), creating a need for novel therapeutics with new mechanisms of action. Cenobamate (CBM) is a tetrazole alkyl carbamate derivative that received US Food and Drug Administration approval in 2019 for the treatment of adult partial onset (focal) seizures. Although CBM displayed impressive seizure reduction in clinical trials across all seizure types, including focal aware motor, focal impaired awareness, and focal to bilateral tonic-clonic seizures, the precise mechanism(s) through which CBM exerts its broad-spectrum antiseizure effects is not known. Experimental evidence suggests that CBM differentiates itself from other ASMs in that it appears to possess dual modes of action (MOAs); that is, it predominately blocks persistent sodium currents and increases both phasic and tonic γ-aminobutyric acid (GABA) inhibition. In this review, we analyze the preclinical efficacy of CBM alongside ASMs with similar MOAs to better understand the mechanism(s) through which CBM achieves such broad-spectrum seizure protection. CBM's preclinical performance in tests, including the mouse 6-Hz model of treatment-resistant seizures, the chemoconvulsant seizure models of generalized epilepsy, and the rat hippocampal kindling model of focal epilepsy, was distinct from other voltage-gated sodium channel blockers and GABAA modulators. This distinction, in light of its proposed mechanism(s) of action, provides insight into the impressive clinical efficacy of CBM in the adult patient with focal onset epilepsy. The results of this comparative reverse translational analysis suggest that CBM is a mechanistically distinct ASM that offers an important advancement in drug development for treatment of therapy-resistant epilepsy.

A new era in electroencephalographic monitoring? Subscalp devices for ultra-long-term recordings.

Inaccurate subjective seizure counting poses treatment and diagnostic challenges and thus suboptimal quality in epilepsy management. The limitations of existing hospital- and home-based monitoring solutions are motivating the development of minimally invasive, subscalp, implantable electroencephalography (EEG) systems with accompanying cloud-based software. This new generation of ultra-long-term brain monitoring systems is setting expectations for a sea change in the field of clinical epilepsy. From definitive diagnoses and reliable seizure logs to treatment optimization and presurgical seizure foci localization, the clinical need for continuous monitoring of brain electrophysiological activity in epilepsy patients is evident. This paper presents the converging solutions developed independently by researchers and organizations working at the forefront of next generation EEG monitoring. The immediate value of these devices is discussed as well as the potential drivers and hurdles to adoption. Additionally, this paper discusses what the expected value of ultra-long-term EEG data might be in the future with respect to alarms for especially focal seizures, seizure forecasting, and treatment personalization.

Auricular acupuncture for the treatment of nonepileptic seizures: A pilot study.

OBJECTIVE: The aim of this pilot study was to examine the safety and tolerability of an eight-week treatment of twice weekly auricular acupuncture as a therapeutic intervention for the treatment of psychogenic nonepileptic seizures (PNES). The secondary aim was to determine if auricular acupuncture was effective at reducing PNES event frequency. Psychogenic nonepileptic seizures are as common as multiple sclerosis and are highly resistant to intervention. Unfortunately, there is no standard of care therapy, although mental health treatment referrals are commonly made. Acupuncture is felt to be a safe and cost-effective treatment for many diseases and symptoms including mental health disorders such as posttraumatic stress disorder (PTSD), anxiety, and conversion disorders. We propose to examine auricular acupuncture as a treatment for PNES. METHODS: A single-center, 16-week trial of auricular acupuncture was designed: a four-week baseline period, followed by an eight-week active treatment period during which subjects received twice weekly auricular acupuncture, then followed by a four-week washout period. Tolerability was defined as completion of 12 of 16 treatments. Successful compliance with seizure diary was defined as >80%, or 100 of 120 days completed. Safety profile was established and seizure count per week was also calculated. RESULTS: A total of 29 subjects enrolled from a consecutive sample of 73 PNES diagnoses discharging from our epilepsy unit. Twenty-two subjects entered the study with 91% completing more than 12 of 16 treatments, 91% meeting the endpoint of completing >80% of diary entries. Adverse events were mild, and only two subjects were withdrawn due to increased PNES frequency. Although short-term in design, using one-way repeated measures analysis of variance (ANOVA), we observed a statistically significant reduction in seizure count from baseline at treatment month one, treatment month two, and at the washout period (p = 0.0083). Eleven of 12 subjects (52.3%) who received at least one treatment recorded a 50% frequency reduction. Three of 21 subjects (14%) were PNES-free at the end of the study. SIGNIFICANCE: Auricular acupuncture is well-tolerated in a population with PNES and exhibits similar event frequency reductions as cognitive behavioral therapy (CBT). We believe that this is the first literature report examining auricular acupuncture for the treatment of PNES.

Suggestive seizure induction for inpatients with suspected psychogenic nonepileptic seizures.

OBJECTIVE: To determine the utility of suggestive seizure induction for inpatient work-up of suspected psychogenic nonepileptic seizures (PNES). METHODS: Prospective study of epilepsy center inpatient admissions with suspected PNES. Patients were randomized to undergo suggestive induction first (group A) and then, if necessary, long-term video-electroencephalography (EEG) monitoring, or vice versa (group B). Diagnostic pathways were compared. Potential clinical predictors for diagnostic success were evaluated. RESULTS: Length of in-hospital stay did not significantly differ between groups. Suspicion of PNES was confirmed in 43 of 77 (56%) patients, evenly distributed between group A (22 of 39) and group B (21 of 38). In nine patients, recorded habitual seizures were epileptic and in 25 cases, no diagnostic event could be recorded. Diagnosis of PNES was ascertained primarily by recording a typical seizure through suggestive induction in 24 patients and through long-term monitoring in 19 patients. In group A (induction first), monitoring was not deemed necessary in 21% of cases. In group B (monitoring first), 13% would have remained inconclusive without suggestive induction. Patients who reported triggers to their habitual seizures were not more likely to have spontaneous or provoked PNES during monitoring or suggestive inducion, respectively. Patients with subjective seizure prodromes (auras) were significantly more likely to have a PNES during suggestive induction than those without (odds ratio [OR] 3.4, 95% confidence interval [CI] 1.1-10.4). There was no significant difference in seizure frequency between patients with spontaneous PNES during long-term monitoring and those with nondiagnostic monitoring sessions. SIGNIFICANCE: Our results support the notion that suggestive seizure induction can reduce the number of inconclusive inpatient workups, and can obviate resource-intensive long-term monitoring in one fifth of cases. Patients who are aware of prodromes might have a higher chance of having seizures induced through suggestion.