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Objective: Childhood trauma has been implicated as a risk factor for the etiology of psychogenic nonepileptic seizures (PNES). Relatively little attention has been paid to whether profiles of specific trauma types differ between patients with epilepsy and PNES. Investigating childhood trauma profiles in these patient groups may identify psychological vulnerabilities that predispose to developing PNES, and aid early diagnoses, prevention, and treatment., Methods: Data were collected from two cohorts (n Retrospective  = 203; n Prospective  = 209) admitted to video-electroencephalography (EEG) monitoring units in Melbourne Australia. The differences in Childhood Trauma Questionnaire domain score between patient groups were investigated using standardized effect sizes and general linear mixed-effects models (GLMMs). Receiver-operating characteristic curves were used to investigate classification accuracy., Results: In the retrospective cohort, patients diagnosed with PNES reported greater childhood emotional abuse, emotional neglect, physical abuse, sexual abuse, and physical neglect relative to patients with epilepsy. These differences were replicated in the prospective cohort, except for physical abuse. GLMMs revealed significant main effects for group in both cohorts, but no evidence for any group by domain interactions. Reported sexual abuse showed the best screening performance of PNES, although no psychometric scores were adequate as isolated measures., Significance: Patients with PNES report a greater frequency of childhood trauma than patients with epilepsy. This effect appears to hold across all trauma types, with no strong evidence emerging for a particular trauma type that is more prevalent in PNES. From a practical perspective, inquiry regarding a history of sexual abuse shows the most promise as a screening measure., (© 2022 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Objective: This study was undertaken to identify factors that predict discordance between the screening instruments Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) and Generalized Anxiety Disorder scale (GAD-7), and diagnoses made by qualified psychiatrists among patients with seizure disorders. Importantly, this is not a validation study; rather, it investigates clinicodemographic predictors of discordance between screening tests and psychiatric assessment., Methods: Adult patients admitted for inpatient video-electroencephalographic monitoring completed eight psychometric instruments, including the NDDI-E and GAD-7, and psychiatric assessment. Patients were grouped according to agreement between the screening instrument and psychiatrists' diagnoses. Screening was "discordant" if the outcome differed from the psychiatrist's diagnosis, including both false positive and false negative results. Bayesian statistical analyses were used to identify factors associated with discordance., Results: A total of 411 patients met inclusion criteria; mean age was 39.6 years, and 55.5% (n = 228) were female. Depression screening was discordant in 33% of cases (n = 136/411), driven by false positives (n = 76/136, 56%) rather than false negatives (n = 60/136, 44%). Likewise, anxiety screening was discordant in one third of cases (n = 121/411, 29%) due to false positives (n = 60/121, 50%) and false negatives (n = 61/121, 50%). Seven clinical factors were predictive of discordant screening for both depression and anxiety: greater dissociative symptoms, greater patient-reported adverse events, subjective cognitive impairment, negative affect, detachment, disinhibition, and psychoticism. When the analyses were restricted to only patients with psychogenic nonepileptic seizures (PNES) or epilepsy, the rate of discordant depression screening was higher in the PNES group (n = 29, 47%) compared to the epilepsy group (n = 70, 30%, Bayes factor for the alternative hypothesis = 4.65)., Significance: Patients with seizure disorders who self-report a variety of psychiatric and other symptoms should be evaluated more thoroughly for depression and anxiety, regardless of screening test results, especially if they have PNES and not epilepsy. Clinical assessment by a qualified psychiatrist remains essential in diagnosing depressive and anxiety disorders among such patients., (© 2021 International League Against Epilepsy.)

Objective: Epilepsy and psychogenic nonepileptic seizures (PNES) are serious conditions, associated with substantial morbidity and mortality. Although prompt diagnosis is essential, these conditions are frequently misdiagnosed, delaying appropriate treatment. We developed and validated the Anxiety, Abuse, and Somatization Questionnaire (AASQ), a quick and clinically practical tool to differentiate PNES from epilepsy., Method: We retrospectively identified psychological variables that differentiated epilepsy from PNES in a discovery cohort of patients admitted to a video-electroencephalography monitoring (VEM) unit from 2002 to 2017. From these findings, we developed the AASQ and prospectively validated it in an independent cohort of patients with gold-standard VEM diagnosis., Results: One thousand two hundred ninety-one patients were included in the retrospective study; mean age was 39.5 years (range: 18-99), 58% were female, 67% had epilepsy, and 33% had PNES. Psychometric data for 192 instrument items were reviewed, receiver operating characteristic curves were computed, and a 20-item AASQ was created. Prospective validation in 74 patients showed that a one-point increase in the AASQ score was associated with 11 times increase in the odds of having PNES compared with epilepsy. Low scores on the AASQ were associated with a low probability of PNES with a negative predictive value of 95%., Significance: The AASQ is quick, inexpensive, and clinically useful for workup of seizure disorders. The AASQ excludes PNES with a high degree of confidence and can predict PNES with significance when combined with basic clinicodemographic variables. Future research will investigate diagnostic performance of the AASQ in relevant clinical subgroups, such as patients with comorbid epilepsy and PNES., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Inc. All rights reserved.)

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 5,508 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 1,595 (29.0%) received other diagnoses or had no diagnosis made. The standardized mortality ratio (SMR) of patients diagnosed with PNES was 2.5 (95% confidence interval [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., (© 2020 American Academy of Neurology.)

Objective: To identify factors associated with subjective cognitive complaints in people with presumed seizure disorders referred for video electroencephalogram monitoring (VEM)., Methods: Adult patients admitted for inpatient VEM were recruited. Objective cognitive function was measured with the Neuropsychiatry Unit Cognitive Screening Tool, subjective cognitive function with the Quality of Life in Epilepsy Inventory-89 subscales, and anxiety and depressive symptoms with the Hospital Anxiety and Depression Scale. Multivariate Bayesian general linear models were used to identify predictors of subjective cognitive function., Results: 331 patients met inclusion criteria. Mean age was 39.3 years and 61.9 % patients were female. Diagnoses included epilepsy, psychogenic non-epileptic seizures (PNES) or both conditions. Depression, anxiety and objective cognitive function were predictors of subjective cognitive function across all domains. Depression was the strongest predictor of subjective memory and attention, whilst objective cognition was the strongest predictor of subjective language function. Mood also mediated the relationship between objective function and subjective function across all domains to varying extents; depression exerted the strongest effect of 22 % for the memory domain; conversely, language domain was least influenced by mood, with depression mediating 11 % and anxiety mediating only 9% of the subjective-objective relationship., Significance: Mood and objective cognitive function are both important contributors to subjective cognitive function for patients undergoing VEM. Clinicians should consider referring patients with cognitive complaints for both neurocognitive workup and neuropsychiatric evaluation. Future work may examine the effects of treating concomitant mood disorders on subjective cognitive function., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objective: Similarities in clinical presentations between epileptic seizures (ES) and psychogenic non-epileptic seizures (PNES) produces a risk of misdiagnosis. Video-EEG monitoring (VEM) is the diagnostic gold standard, but involves significant cost and time commitment, suggesting a need for efficient screening tools., Methods: 628 patients were recruited from an inpatient VEM unit; 293 patients with ES, 158 with PNES, 31 both ES and PNES, and 146 non-diagnostic. Patients completed the SCL-90-R, a standardised 90-item psychopathology instrument. Bayesian linear models were computed to investigate whether SCL-90-R domain scores or the overall psychopathology factor p differed between groups. Receiver operating characteristic (ROC) curves were computed to investigate the PNES classification accuracy of each domain score and p. A machine learning algorithm was also used to determine which subset of SCL-90-R items produced the greatest classification accuracy., Results: Evidence was found for elevated scores in PNES compared to ES groups in the symptom domains of anxiety (b = 0.47, 95%HDI = [0.10, 0.80]), phobic anxiety (b = 1.32, 95%HDI = [0.98, 1.69]), somatisation (b = 0.84, 95%HDI = [0.49, 1.20]), and the general psychopathology factor p (b = 1.35, 95%HDI = [0.86, 1.82]). Of the SCL-90-R domain scores, somatisation produced the highest classification accuracy (AUC = 0.74, 95%CI = [0.69, 0.79]). The genetic algorithm produced a 6-item subset from the SCL-90-R, which produced comparable classification accuracy to the somatisation scores (AUC = 0.73, 95%CI = [0.64, 0.82])., Significance: Compared to patients with ES, patients with PNES report greater symptoms of somatisation, general anxiety, and phobic anxiety against a background of generally elevated psychopathology. While self-reported psychopathology scores are not accurate enough for diagnosis in isolation, elevated psychopathology in these domains should raise the suspicion of PNES in clinical settings., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Purpose: Psychogenic non-epileptic seizures (PNES) and epileptic seizures (ES) are often difficult to differentiate, leading to incorrect or delayed diagnosis. The aim of the study was to determine whether patients of these two diagnostic groups possess different personality profiles, and whether they could be used to efficiently screen for PNES in clinical settings., Methods: Collection of data was conducted on 305 patients who completed the NEO-Five Factor Inventory questionnaire during a Video EEG Monitoring admission to the Royal Melbourne Hospital between 2002-2017. Personality differences were investigated using Bayesian linear mixed effects models, with receiver operating characteristic curve analysis computed to evaluate diagnostic accuracy., Results: The 'openness to experience' domain (BF 10  = 21.55, d = -0.43 [95% CI -0.71, -0.17]) and the 'aesthetic interest' facet (B 10 = 7.98, d= -0.39 [95% CI -0.66, -0.12]) were the only personality factors demonstrating strong evidence for a group difference, with patients with PNES having higher scores compared to the ES group. ES patients had lower scores on these measures compared to the normal population, while PNES patients did not. Both openness to experience and aesthetic interest showed poor sensitivities (53%, 46% respectively) and specificities (69%, 46% respectively) for classifying PNES and ES patients., Conclusion: While openness and aesthetic interests differ greatly between PNES and ES groups, low sensitivity and specificity suggests their use is limited in a clinical setting. Nevertheless, these findings open up new avenues of research using modern personality models to further understand patients with epilepsy and related presentations., (Copyright © 2019 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

Purpose: Psychopathology is common in patients undergoing investigation for seizure-related disorders. Psychometric examination using self-report instruments, such as the Symptom Checklist 90 - Revised (SCL-90-R), can assist diagnosis. The SCL-90-R, however, is a lengthy instrument and might not be tolerated by all patients. We assessed several abbreviated forms of the SCL-90-R in patients undergoing video encephalographic monitoring (VEM)., Method: Six hundred eighty-seven patients completed the SCL-90-R, and scores were computed for the full SCL-90-R and five abbreviated forms. Correlations and mean differences were computed between different forms. Classification accuracy was assessed via receiver operating characteristic (ROC) curves, and measurements models were examined using confirmatory factor analysis (CFA)., Results: All abbreviated forms were strongly correlated with the SCL-90-R for general psychopathology (r = 0.93-0.99), depression (r = 0.89-0.95), anxiety (r = 0.97-0.98), psychosis (r = 0.95-0.99), and obsessive-compulsive symptoms (r = 0.97). Classification performance was similar across forms for depression and anxiety, with high negative predictive values (0.90-0.94) and lower positive predictive values (0.34-0.38). Classification performance for psychotic and obsessive-compulsive disorders was poor. Differences were observed between the full SCL-90-R and its abbreviated forms across most domains (d = 0.00-0.65). The published measurement model was most strongly validated for the SCL-27, SCL-14, and the SCL-K-9., Conclusions: These five SCL-90-R abbreviated forms show high convergent validity with the full version. In patients undergoing investigation for seizure-related disorders, the Brief Symptom Inventory full form (BSI) or short form (BSI-18) is most appropriate where screening for both depression and anxiety is required. The SCL-K-9 is appropriate when only a single measure of global psychological distress is required. None of the instruments were able to detect psychotic or obsessive-compulsive symptoms with great accuracy. Caution should be exercised when making direct comparisons across the different forms., (Copyright © 2019 Elsevier Inc. All rights reserved.)