Differentiating Frontal Lobe Epilepsy from Psychogenic Nonepileptic Seizures

Functional seizures and their mimics: a retrospective service review of cases from a tertiary video telemetry database

ABSTRACT

Objective

Identify the proportion of patients referred with putative functional seizures (FS) that were subsequently re-diagnosed as epileptic seizures (ES), or an alternative diagnosis, following video telemetry EEG (VTEEG). In addition, describe the characteristics of those seizures.

Methods

The VTEEG reports from patients admitted to the Chalfont Centre for Epilepsy between 2019 and 2022 were reviewed. Pre-VTEEG and post-VTEEG diagnoses were compared to identify whether a diagnostic revision was made from suspected FS to ES or another diagnosis. Diagnostic revision cases were then grouped into cohorts with associated features and reviewed to characterise and describe FS mimics.

Results

444 VTEEG reports where patients had habitual events were identified. 4.7% of patients were referred with FS and were subsequently diagnosed with ES or another diagnosis. In this group, several cohorts could be identified including frontal lobe epileptic seizures, ES with functional overlay, insular or temporal lobe epileptic seizures associated with autonomic or marked experiential peri-ictal symptoms, and individuals who had both ES and FS but whose ES were revealed on medication withdrawal.

Conclusion

In patients referred to a tertiary epilepsy unit, a small minority of cases had seizures diagnosed as functional and reclassified as epileptic or an alternative diagnosis. It is clinically important to be aware of these FS mimics.

Functional Neurological Disorder: Diagnostic Pitfalls and Differential Diagnostic Considerations

Functional neurologic disorder (FND) is a "rule-in" diagnosis, characterized by positive examination signs or semiological features. Similar to other clinical diagnoses, providers should ideally see robustly present features, including if possible the identification of multiple features consistent with FND for the diagnosis to be made with a high degree of certainty. Diagnostic pitfalls need to be guarded against and vary depending on FND symptom subtype and the specific patient presentation. This perspective article aims to review pitfalls based on an FND symptom subtype, as well as discuss differential diagnostic considerations with respect to both neurologic and psychiatric entities.

Clinical Reasoning: A Young Adult With New Seizures and Chapeau de Gendarme

The evaluation of new seizures is a common clinical query for neurologists. It can be challenging to delineate between the numerous etiologies of new focal or generalized seizures and, if focal, to localize their onset. In this case report, we present a 26-year-old patient with a new onset of stereotyped events concerning for seizures featuring facial grimacing, dystonic left-hand posturing, and convulsions with immediate return to baseline. Throughout the case, we highlight a stepwise diagnostic approach to the evaluation of new-onset seizures, discuss clues that seizure semiology can provide for localization of ictal onset, and review a novel and atypical presentation of a disease entity frequently encountered by neurologists.

Psychogenic Nonepileptic Seizures-High Mortality Rate Is a 'Wake-Up Call'

Patients with epilepsy have an elevated mortality rate compared to the general population and now studies are showing a comparable death ratio in patients diagnosed with psychogenic nonepileptic seizures. The latter is a top differential diagnosis for epilepsy and the unexpected mortality rate in these patients underscores the importance of an accurate diagnosis. Experts have called for more studies to elucidate this finding but the explanation is already available, embedded in the existing data. To illustrate, a review of the diagnostic practice in epilepsy monitoring units, of the studies examining mortality in PNES and epilepsy patients, and of the general clinical literature on the two populations was conducted. The analysis reveals that the scalp EEG test result, which distinguishes a psychogenic from an epileptic seizure, is highly fallible; that the clinical profiles of the PNES and epilepsy patient populations are virtually identical; and that both are dying of natural and non-natural causes including sudden unexpected death associated with confirmed or suspected seizure activity. The recent data showing a similar mortality rate simply constitutes more confirmatory evidence that the PNES population consists largely of patients with drug-resistant scalp EEG-negative epileptic seizures. To reduce the morbidity and mortality in these patients, they must be given access to treatments for epilepsy.

Lessons from the video-EEG telemetry unit

Epilepsy is a clinical diagnosis, based primarily on patient and witness histories. Where there is diagnostic uncertainty or when epilepsy surgery is being considered, long-term video-EEG monitoring in a telemetry unit remains the gold standard investigation for diagnostic clarification or presurgical localisation. We present six illustrative cases, highlighting important points that emerged during video-EEG review including potential pitfalls in video-EEG interpretation, and how the investigation helped with diagnosis and subsequent management. The diagnostic process strongly emphasises seizure semiology, more so than EEG.

Dissoziative Anfälle frühzeitig erkennen

Wenn dissoziative Anfälle, also psychogene, nichtepileptische Anfälle als epileptische Anfälle fehlgedeutet werden, führt dies zu frustraner medikamentöser Therapie und verzögert die Einleitung der erforderlichen psychotherapeutischen Maßnahmen. Folgende Anfallssymptome sollten an dissoziative Anfälle denken lassen: unrhythmisches, wildes Hin- und Herbewegen des Kopfes oder der Extremitäten, geschlossene Augen, lange Dauer und undulierender Verlauf. Ein unauffälliges Elektroenzephalogramm (EEG) spricht für dissoziative Anfälle, aber erst ein negativer EEG-Befund während eines Anfalls ist beweisend. Im Arztgespräch ist es entscheidend, dass die Betroffenen die Möglichkeit bekommen, frei zu schildern. Betroffene mit dissoziativen Anfällen zeigen dann Besonderheiten, die als Diagnosekriterien genutzt werden sollten: Sie fokussieren auf Begleitumstände und lassen in ihren Schilderungen den Moment des Bewusstseinsverlusts aus. Sie machen eher allgemeine Angaben und unterscheiden einzelne Anfälle kaum.

Digital Semiology: A Prototype for Standardized, Computer-Based Semiologic Encoding of Seizures

Video-EEG monitoring (VEM) is imperative in seizure classification and presurgical assessment of epilepsy patients. Analysis of VEM is currently performed in most institutions using a freeform report, a time-consuming process resulting in a non-standardized report, limiting the use of this essential diagnostic tool. Herein we present a pilot feasibility study of our experience with “Digital Semiology” (DS), a novel seizure encoding software. It allows semiautomated annotation of the videos of suspected events from a predetermined, hierarchal set of options, with highly detailed semiologic descriptions, somatic localization, and timing. In addition, the software's semiologic extrapolation functions identify characteristics of focal seizures and PNES, sequences compatible with a Jacksonian march, and risk factors for SUDEP. Sixty episodes from a mixed adult and pediatric cohort from one level 4 epilepsy center VEM archives were analyzed using DS and the reports were compared with the standard freeform ones, written by the same epileptologists. The behavioral characteristics appearing in the DS and freeform reports overlapped by 78–80%. Encoding of one episode using DS required an average of 18 min 13 s (standard deviation: 14 min and 16 s). The focality function identified 19 out of 43 focal episodes, with a sensitivity of 45.45% (CI 30.39–61.15%) and specificity of 87.50% (CI 61.65–98.45%). The PNES function identified 6 of 12 PNES episodes, with a sensitivity of 50% (95% CI 21.09–78.91%) and specificity of 97.2 (95% CI 88.93–99.95%). Eleven events of GTCS triggered the SUDEP risk alert. Overall, these results show that video recordings of suspected seizures can be encoded using the DS software in a precise manner, offering the added benefit of semiologic alerts. The present study represents an important step toward the formation of an annotated video archive, to be used for machine learning purposes. This will further the goal of automated VEM analysis, ultimately contributing to wider utilization of VEM and therefore to the reduction of the treatment gap in epilepsy.

Prolactin levels as a criterion to differentiate between psychogenic non-epileptic seizures and epileptic seizures: A systematic review

OBJECTIVE

Psychogenic non-epileptic seizures (PNES) are conversion disorders with functional neurological symptoms that can resemble epileptic seizures (ES). We conducted a systematic review to obtain an overview of the value of prolactin (PRL) levels in the differential diagnosis between PNES and ES.

METHODS

We searched PubMed, EMBASE, and Cochrane Library databases for studies published up to June 4th, 2020. Published studies were included if they fulfilled the following criteria: original research on PRL changes after ES and PNES. By applying Bayes' theorem, we calculated the predicted values of PRL with pretest probabilities of 90 % and 75 % in ES.

RESULTS

Sixteen studies were included in this review. All the studies showed that PRL levels increase after ES, especially 10-20 min after ES, when the elevation was most obvious. In studies where capillary PRL level measurements were included, the median sensitivity in the diagnosis of ES (all epileptic seizure types), generalized tonic clonic seizures (GTCS), focal impaired awareness seizures (FIAS), and focal aware seizures (FAS) was 67.3 %, 66.7 %, 33.9 %, and 11.1 %, respectively. The median specificity in the diagnosis of ES was 99.1 %. By using Bayes' theorem, when we used the median specificity and sensitivity for predictive value calculation, assuming a pretest probability of 90 %, a positive PRL measure was highly predictive (99 %) of all types of ES, and negative predictive values were all below 30 %. When we used the lowest specificity and sensitivity for predictive value calculation, assuming a pretest probability of 75 %, ES and GTCS had positive predictive values of 77.2 % and 81.0 %, respectively; the negative predictive values of PRL in ES and GTCS were 26.2 % and 29.6 %, respectively.

CONCLUSIONS

The use of PRL could be a useful adjunct to differentiate GTCS from PNES. However, PRL levels are of limited use for differentiating FIAS or FAS from PNES, and a negative PRL measure is not predictive of PNES.

Current challenges in the pathophysiology, diagnosis, and treatment of paroxysmal movement disorders

INTRODUCTION

Paroxysmal movement disorders mostly comprise paroxysmal dyskinesia and episodic ataxia, and can be the consequence of a genetic disorder or symptomatic of an acquired disease.

AREAS COVERED

In this review, the authors focused on certain hot-topic issues in the field: the respective contribution of the cerebellum and striatum to the generation of paroxysmal dyskinesia, the importance of striatal cAMP turnover in the pathogenesis of paroxysmal dyskinesia, the treatable causes of paroxysmal movement disorders not to be missed, with a special emphasis on the treatment strategy to bypass the glucose transport defect in paroxysmal movement disorders due to GLUT1 deficiency, and functional paroxysmal movement disorders.

EXPERT OPINION

Treatment of genetic causes of paroxysmal movement disorders is evolving towards precision medicine with targeted gene-specific therapy. Alteration of the cerebellar output and modulation of the striatal cAMP turnover offer new perspectives for experimental therapeutics, at least for paroxysmal movement disorders due to selected causes. Further characterization of cell-specific molecular pathways or network dysfunctions that are critically involved in the pathogenesis of paroxysmal movement disorders will likely result in the identification of new biomarkers and testing of innovative-targeted therapeutics.

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.

Clinical Classifications of Children With Psychogenic Non-epileptic Seizure

Objective: To analyze the clinical features of children with psychogenic non-epileptic seizures in one tertiary center in China. Methods: Clinical data including medical records and video- electroencephalograph (video-EEG) monitoring records of 88 pediatric PNES patients hospitalized in the pediatric department of Xuanwu Hospital, Beijing, China from April, 2012 to April, 2018 were collected in this study. Demographic information of patients, semiological classification, duration, and frequency of symptoms, risk factors as well as comorbidity were summarized and analyzed. Results: For semiological classification, all PNES related symptoms were divided into different categories: motor symptoms, unresponsiveness, sensory symptoms, visceral symptoms, and abnormal behaviors, among which motor symptoms were the most prevalent form. Risk factors were reviewed and categorized into two groups: persistent factors and predisposing factors, and patients were most frequently affected by the influences of families. The duration and frequency of symptoms varied substantially within PNES patients while the average time of duration was relatively longer than epilepsy as reported previously. Epilepsy was considered as the most frequent comorbidity of PNES and PNES patients misdiagnosed as epilepsy often mistreated with antiseizure medication. Significance: Our study showed that motor PNES are the most frequent seizure type. Family issues were a risk factor for PNES. Epilepsy was the most frequent co-existing neurological comorbidity.

The Role of EEG in the Erroneous Diagnosis of Epilepsy

Errors in diagnosis are relatively common in medicine and occur in all specialties. The consequences can be serious for both patients and physicians. Errors in neurology are often because of the overemphasis on 'tests' over the clinical picture. The diagnosis of epilepsy in general is a clinical one and is typically based on history. Epilepsy is more commonly overdiagnosed than underdiagnosed. An erroneous diagnosis of epilepsy is often the result of weak history and an 'abnormal' EEG. Twenty-five to 30% of patients previously diagnosed with epilepsy who did not respond to initial antiepileptic drug treatment do not have epilepsy. Most patients misdiagnosed with epilepsy turn out to have either psychogenic nonepileptic attacks or syncope. Reasons for reading a normal EEG as an abnormal one include over-reading normal variants or simple fluctuations of background rhythms. Reversing the diagnosis of epilepsy is challenging and requires reviewing the 'abnormal' EEG, which can be difficult. The lack of mandatory training in neurology residency programs is one of the main reasons for normal EEGs being over-read as abnormal. Tests (including EEG) should not be overemphasized over clinical judgment. The diagnosis of epilepsy can be challenging, and some seizure types may be underdiagnosed. Frontal lobe hypermotor seizures may be misdiagnosed as psychogenic events. Focal unaware cognitive seizures in elderly maybe be blamed on dementia, and ictal or interictal psychosis in frontal and temporal lobe epilepsies may be mistaken for a primary psychiatric disorder.

SUDEP in patients with epilepsy and nonepileptic seizures

We report 13 SUDEP cases in the North American SUDEP Registry with both psychogenic nonepileptic seizures (PNES) and epileptic seizures (ES) among a consecutive series of 231 cases (excluding epileptic encephalopathies). On average, cases of PNES + ES died at a younger age (23 ± 11 years) than the ES-only cohort (30 ± 14 years), and died an average of 3 years after PNES diagnosis. We found no statistically significant confounding cardiac, respiratory, or psychiatric comorbidities and equal rates of anti-seizure medication adherence, although there was a trend for higher rates of psychiatric disorders in the PNES group. Our findings confirm that patients with comorbid ES and PNES can die from SUDEP and that there may be a high-risk period after the diagnosis of PNES is made in patients with comorbid ES. Such patients should be closely monitored and provided with coordinated care of both their epilepsy and psychiatric disorder(s).

Improving first responders' psychogenic nonepileptic seizures diagnosis accuracy: Development and validation of a 6-item bedside diagnostic tool

OBJECTIVE

Epileptic seizures (ES) are often seen as a medical emergency, and their immediate and accurate recognition are pivotal in providing acute care. However, a number of clinical situations may mimic ES, potentially leading to misdiagnosis at the emergency room and to inappropriate prescription of antiepileptic drugs (AED) in the acute and chronic settings. Psychogenic nonepileptic seizures (PNES) play a major role in this scenario and often delay the correct diagnosis and increase treatment morbidity and cost. First responders often conduct the initial assessment of these patients, and their impression may be decisive in the prehospital approach to seizures. We sought to investigate and improve the accuracy of PNES diagnosis among professionals involved in the initial assistance to patients with seizures.

METHODS

Fifty-three registered nurses, 34 emergency physicians, 33 senior year medical students, and 12 neurology residents took a short training program consisting of an initial video-based seizure assessment test (pretest), immediately followed by a 30-minute presentation of a 6-item bedside diagnostic tool and then a video-based reassessment (posttest). Baseline status and learning curves were determined.

RESULTS

The distinct professional categories showed no significant differences in their ability to diagnose PNES on both pretests and posttests. All groups improved diagnostic skills after the instructional program.

SIGNIFICANCE

The findings helped determine the best identifiable PNES clinical signs and to provide initial validation to a novel diagnostic instrument. In addition, our results showed that educational measures might help in the identification of PNES by first responders, which may decrease the treatment gap.

Nonepileptic seizures - objective phenomena

This chapter describes the evaluation process for the diagnosis of psychogenic nonepileptic seizures (PNES), which is determined based on concordance of the composite evidence available, including historic and physical exam findings, seizure semiology, and ictal/interictal electroencephalogram (EEG). No single clinical feature is pathognomonic of PNES. The diagnosis of PNES can be at times challenging, such as when seizure documentation on video-EEG cannot be readily achieved. A multicomponent approach to the diagnosis of PNES, with use of all available evidence, may facilitate diagnosis and then care of patients with PNES. Emerging evidence supports the use of symptom identification by the patient as part of the treatment of these patients. With advances in diagnostic methods and criteria, the diagnosis of PNES can be made reliably.

Medical comorbidities in patients with psychogenic nonepileptic spells (PNES) referred for video-EEG monitoring

Differentiating between psychogenic nonepileptic spells (PNES) and epileptic seizures without video-EEG monitoring is difficult. The presence of specific medical comorbidities may discriminate the two, helping physicians suspect PNES over epilepsy earlier. A retrospective analysis comparing the medical comorbidities of patients with PNES with those of patients with epilepsy was performed in 280 patients diagnosed with either PNES (N = 158, 74.7% females) or epilepsy (N = 122, 46.7% females) in the Epilepsy Monitoring Unit (EMU) of the University of Pittsburgh Medical Center over a two-year period. Patients with PNES, compared to those with epilepsy, were mostly female, significantly more likely to have a history of abuse, had more functional somatic syndromes (fibromyalgia, chronic fatigue syndrome, chronic pain syndrome, tension headaches, and irritable bowel syndrome), and had more medical illnesses that are chronic with intermittent attacks (migraines, asthma, and GERD). The presence of at least of one these disorders may lead physicians to suspect PNES over epilepsy and expedite appropriate referral for video-EEG monitoring for diagnosis.

Computer-Aided Diagnosis and Localization of Lateralized Temporal Lobe Epilepsy Using Interictal FDG-PET

Interictal FDG-PET (iPET) is a core tool for localizing the epileptogenic focus, potentially before structural MRI, that does not require rare and transient epileptiform discharges or seizures on EEG. The visual interpretation of iPET is challenging and requires years of epilepsy-specific expertise. We have developed an automated computer-aided diagnostic (CAD) tool that has the potential to work both independent of and synergistically with expert analysis. Our tool operates on distributed metabolic changes across the whole brain measured by iPET to both diagnose and lateralize temporal lobe epilepsy (TLE). When diagnosing left TLE (LTLE) or right TLE (RTLE) vs. non-epileptic seizures (NES), our accuracy in reproducing the results of the gold standard long term video-EEG monitoring was 82% [95% confidence interval (CI) 69-90%] or 88% (95% CI 76-94%), respectively. The classifier that both diagnosed and lateralized the disease had overall accuracy of 76% (95% CI 66-84%), where 89% (95% CI 77-96%) of patients correctly identified with epilepsy were correctly lateralized. When identifying LTLE, our CAD tool utilized metabolic changes across the entire brain. By contrast, only temporal regions and the right frontal lobe cortex, were needed to identify RTLE accurately, a finding consistent with clinical observations and indicative of a potential pathophysiological difference between RTLE and LTLE. The goal of CADs is to complement - not replace - expert analysis. In our dataset, the accuracy of manual analysis (MA) of iPET (∼80%) was similar to CAD. The square correlation between our CAD tool and MA, however, was only 30%, indicating that our CAD tool does not recreate MA. The addition of clinical information to our CAD, however, did not substantively change performance. These results suggest that automated analysis might provide clinically valuable information to focus treatment more effectively.

Psychogenic nonepileptic seizures: a current overview

Psychogenic nonepileptic seizures (PNES) resemble epilepsy, but no pathophysiological explanation has been established. Although there have been recent advances in PNES research and various hypotheses as to the psychopathology, no theory has achieved general acceptance. In this overview of selected literature on PNES, we highlight the often contradictory findings that underline the challenges that confront both practitioner and researcher. We first provide a synopsis of the history, diagnosis, treatment, and outcomes, as well as patient characteristics of PNES and the relevance of communication in the clinical context. In the subsequent sections we discuss recent research that may advance the understanding and diagnosis of this disorder. These themes include the use of qualitative methods as a viable research option, the application of nonlinear methods to analyze heterogeneous observations during diagnosis, recent advances in neuroimaging of PNES, and the development of international databases.