Psychogenic nonepileptic seizures (PNES) are paroxysms of altered sensory, cognitive, and/or motor manifestations with or without alteration of consciousness that may resemble epileptic seizures, but do not originate from epileptiform brain activity. One framework conceives PNES as arising from a biopsychosocial, multifactorial etiologic model. An unexpectedly high co-occurrence rate of PNES and mild traumatic brain injury (mTBI) has been reported. A causal relationship may be possible in many cases. In applying the biopsychosocial framework, this review discusses how TBI may subserve contributing roles as Predisposing, Precipitating, and Perpetuating factors in the development of PNES.

BACKGROUND AND PURPOSE:The aim of this study was to evaluate the quality of smartphone videos (SVs) of neurologic events in adult epilepsy outpatients. The use of home video recording in patients with neurological disease states is increasing. Experts interpretation of outpatient smartphone videos of seizures and neurological events has demonstrated similar diagnostic accuracy to inpatient video-electroencephalography (EEG) monitoring.METHODS:A prospective, multicenter cohort study was conducted to evaluate SV quality in patients with paroxysmal neurologic events from August 15, 2015 through August 31, 2018. Epileptic seizures (ESs), psychogenic nonepileptic attacks (PNEAs), and physiologic nonepileptic events (PhysNEEs) were confirmed by video-EEG monitoring. Experts and senior neurology residents blindly viewed cloud-based SVs without clinical information. Quality ratings with regard to technical and operator-driven metrics were provided in responses to a survey.RESULTS:Forty-four patients (31 women, age 45.1 years [r = 20-82]) were included and 530 SVs were viewed by a mean of seven experts and six residents; one video per patient was reviewed for a mean of 133.8 s (r = 9-543). In all, 30 patients had PNEAs, 11 had ESs, and three had PhysNEEs. Quality was suitable in 70.8% of SVs (375/530 total views), with 36/44 (81.8%) patient SVs rated as adequate by the majority of reviewers. Accuracy improved with the presence of convulsive features from 72.4% to 98.2% in ESs and from 71.1% to 95.7% in PNEAs. An accurate diagnosis was given by all reviewers (100%) in 11/44 SVs (all PNEAs). Audio was rated as good by 86.2% of reviewers for these SVs compared with 75.4% for the remaining SVs (p = 0.01). Lighting was better in SVs associated with high accuracy (p = 0.06), but clarity was not (p = 0.59). Poor video quality yielded unknown diagnoses in 24.2% of the SVs reviewed. Features hindering diagnosis were limited interactivity, restricted field of view and short video duration.CONCLUSIONS:Smartphone video quality is adequate for clinical interpretation in the majority of patients with paroxysmal neurologic events. Quality can be optimized by encouraging interactivity with the patient, adequate duration of the SV, and enlarged field of view during videography. Quality limitations were primarily operational though accuracy remained for SV review of ESs and PNEAs.

PURPOSE:Epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES) are difficult to differentiate when based on a patient's self-reported symptoms. This study proposes review of objective data captured by a surface electromyography (sEMG) wearable device for classification of events as ES or PNES. This may help clinicians accurately identify ES and PNES.METHODS:Seventy-one subjects were prospectively enrolled across epilepsy monitoring units at VA Epilepsy Centers of Excellence. Subjects were concomitantly monitored using video EEG and a wearable sEMG epilepsy monitor, the Sensing Portable sEmg Analysis Characterization (SPEAC) System. Three epileptologists independently classified ES and PNES that contained upper extremity motor activity based on video EEG. The sEMG data from those events were automatically processed to provide a seizure score for event classification. After brief training (60 minutes), the sEMG data were reviewed by a separate group of four epileptologists to independently classify events as ES or PNES.RESULTS:According to video EEG review, 17 subjects experienced 34 events (15 ES and 19 PNES with upper extremity motor activity). The automated process correctly classified 87% of ES (positive predictive value = 88%, negative predictive value = 76%) and 79% of PNES, and the expert reviewers correctly classified 77% of ES (positive predictive value = 94%, negative predictive value = 84%) and 96% of PNES. The automated process and the expert reviewers correctly classified 100% of tonic-clonic seizures as ES, and 71 and 50%, respectively, of non-tonic-clonic ES.CONCLUSIONS:Automated and expert review, particularly in combination, of sEMG captured by a wearable seizure monitor (SPEAC System) may be able to differentiate ES (especially tonic-clonic) and PNES with upper extremity motor activity.

Objective: Using video-EEG (v-EEG) diagnosis as a gold standard, we assessed the predictive diagnostic value of home videos of spells with or without additional limited demographic data in US veterans referred for evaluation of epilepsy. Veterans, in particular, stand to benefit from improved diagnostic tools given higher rates of PNES and limited accessibility to care. Methods: This was a prospective, blinded diagnostic accuracy study in adults conducted at the Houston VA Medical Center from 12/2015-06/2019. Patients with a definitive diagnosis of epileptic seizures (ES), psychogenic nonepileptic seizures (PNES), or physiologic nonepileptic events (PhysNEE) from v-EEG monitoring were asked to submit home videos. Four board-certified epileptologists blinded to the original diagnosis formulated a diagnostic impression based upon the home video review alone and video plus limited demographic data. Results: Fifty patients (30 males; mean age 47.7 years) submitted home videos. Of these, 14 had ES, 33 had PNES, and three had PhysNEE diagnosed by v-EEG. The diagnostic accuracy by video alone was 88.0%, with a sensitivity of 83.9% and specificity of 89.6%. Providing raters with basic patient demographic information in addition to the home videos did not significantly improve diagnostic accuracy when comparing to reviewing the videos alone. Inter-rater agreement between four raters based on video was moderate with both videos alone (kappa = 0.59) and video plus limited demographic data (kappa = 0.60). Significance: This study demonstrated that home videos of paroxysmal events could be an important tool in reliably diagnosing ES vs. PNES in veterans referred for evaluation of epilepsy when interpreted by experts. A moderate inter-rater reliability was observed in this study. Published by Elsevier Inc.

Importance Misdiagnosis of epilepsy is common. Video electroencephalogram provides a definitive diagnosis but is impractical for many patients referred for evaluation of epilepsy. Objective To evaluate the accuracy of outpatient smartphone videos in epilepsy. Design, Setting, and Participants This prospective, masked, diagnostic accuracy study (the OSmartViE study) took place between August 31, 2015, and August 31, 2018, at 8 academic epilepsy centers in the United States and included a convenience sample of 44 nonconsecutive outpatients who volunteered a smartphone video during evaluation and subsequently underwent video electroencephalogram monitoring. Three epileptologists uploaded videos for physicians from the 8 epilepsy centers to review. Main Outcomes and Measures Measures of performance (accuracy, sensitivity, specificity, positive predictive value, and negative predictive value) for smartphone video-based diagnosis by experts and trainees (the index test) were compared with those for history and physical examination and video electroencephalogram monitoring (the reference standard). Results Forty-four eligible epilepsy clinic outpatients (31 women [70.5%]; mean [range] age, 45.1 [20-82] years) submitted smartphone videos (530 total physician reviews). Final video electroencephalogram diagnoses included 11 epileptic seizures, 30 psychogenic nonepileptic attacks, and 3 physiologic nonepileptic events. Expert interpretation of a smartphone video was accurate in predicting a video electroencephalogram monitoring diagnosis of epileptic seizures 89.1% (95% CI, 84.2%-92.9%) of the time, with a specificity of 93.3% (95% CI, 88.3%-96.6%). Resident responses were less accurate for all metrics involving epileptic seizures and psychogenic nonepileptic attacks, despite greater confidence. Motor signs during events increased accuracy. One-fourth of the smartphone videos were correctly diagnosed by 100% of the reviewing physicians, composed solely of psychogenic attacks. When histories and physical examination results were combined with smartphone videos, correct diagnoses rose from 78.6% to 95.2%. The odds of receiving a correct diagnosis were 5.45 times greater using smartphone video alongside patient history and physical examination results than with history and physical examination alone (95% CI, 1.01-54.3; P = .02). Conclusions and Relevance Outpatient smartphone video review by experts has predictive and additive value for diagnosing epileptic seizures. Smartphone videos may reliably aid psychogenic nonepileptic attacks diagnosis for some people.

Objective: Patients with psychogenic nonepileptic events (PNEE) exhibit heterogenous symptoms and are best diagnosed with long-term video-electroencephalogram (vEEG) data. While extensive univariate data suggest psychological tests may confirm the etiology of PNEE, the multivariate discriminant utility of psychological tests is less clear. The current study aggregated likelihood ratios of multiple psychological tests to evaluate incremental and discriminant utility for PNEE. Methods: Veterans with vEEG-diagnosed PNEE (n = 166) or epileptic seizures (n = 92) completed self-report measures and brief neuropsychological evaluations during the 4-day vEEG hospitalization. Receiver operating characteristic (ROC) curves identified discriminating psychological tests and corresponding cut-scores (0.85 minimum specificity). Likelihood ratios from the remaining cut-scores were sequentially linked using the sample base rate of PNEE (64%) and alternative base rates (10%, 20%, 30%, 40%) to estimate posttest probabilities (PTP) of test combinations. Results: The Health Attitudes Survey, Health History Checklist, and Minnesota Multiphasic Personality Inventory-2-Restructured Form scales FBS-r, RC1, MLS, and NUC were identified as discriminating indicators of PNEE. Average PTPs were >= 90% when three or more indicators out of six administered were present at the sample base rate. Regardless of PNEE base rate, PTP for PNEE was >= 98% when all discriminating indicators were present and 92-99% when five of six indicators administered were present. PTPs were largely consistent with observed positive predictive values, particularly as indicators present increased. Significance: Aggregating psychological tests identified PNEE with a high degree of accuracy, regardless of PNEE base rate. Combining psychological tests may be useful for confirming the etiology of PNEE. (C) 2020 Published by Elsevier Inc.

Patients with coexisting epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES) pose a diagnostic challenge. In such cases, ES and PNES usually occur independently across separate times and demonstrate distinguishable semiologies. More enigmatic would be rarer clinical scenarios when ES and PNES occur closely together temporally, whereby the end of one seizure type is not easily demarcated from the start of the other. We present two cases with sequential occurrences of ES and PNES within close temporal proximity -- one with ES followed by PNES; and, one with PNES followed by ES.

Psychiatric disorders can be identified in 25–50% of patients with epilepsy, with higher prevalence among patients with poorly controlled seizures. These disturbances include depression, anxiety, psychotic disorders, and cognitive and personality changes occurring in the inter-ictal or peri-ictal (pre-ictal, ictal, post-ictal) states. We focus on four areas in patients with epilepsy: (1) more frequent comorbid psychiatric disorders, (2) integrated symptoms secondary to epilepsy, (3) stigma and psychosocial consequences of epilepsy, and (4) non-epileptic seizures. In this chapter, we will call attention to pertinent elements of the history in the patient with seizures, diagnostic work-up, assessment of comorbidities, and consequences of treatment of the seizure disorder (including medications, resective surgery, and neuromodulation) and of the psychiatric comorbidity.

Objectives: We aimed to evaluate whether potential changes in the patient's illness perception can significantly influence short-term seizure burden following video-electroencephalography (EEG) confirmation/explanation of psychogenic nonepileptic seizures (PNES). Methods: Patients with PNES were dichotomized to two groups based on a five-point Symptom Attribution Scale: (a) those who prior to diagnosis perceived their seizures to be solely ("5") ormainly ("4") physical in origin (physical group) and (b) the remainder of patients with PNES (psychological group). The physical group (n = 32), psychological group (n = 40), and group with epilepsy (n = 26) also completed the Brief Illness Perception Questionnaire (BIPQ) prior to diagnosis, and were followed up at 3 months as well as at 6 months postdiagnosis. Results: At 3 months postdiagnosis, the physical group experienced significantly greater improvement in seizure intensity (p = 0.002) and seizure frequency (p = 0.016) when compared with the psychological group. The physical group was significantly more likely to have modified their symptom attribution toward a greater psychological role to their seizures (p = 0.002), and their endorsement on the BIPQ item addressing "consequences" (How much do your seizures affect your life?) was significantly less severe (p' = 0.014) when compared with that of the psychological group and the group with epilepsy. At 6 months postdiagnosis, the physical group continued to experience significantly greater improvement in seizure intensity (p = 0.007) while their seizure frequency no longer reached significant difference (p = 0.078) when compared with the psychological group. The physical group continued to be significantly more likely to have modified their symptom attribution toward a greater psychological role to their seizures (p = 0.005), and their endorsement on the BIPQ item addressing "consequences" remained significantly less severe (p' = 0.037) when compared with the psychological group and the group with epilepsy. Conclusions: Among patients with PNES, prediagnosis perception of seizures as "solely" or "mainly" physical in cause may be associated with greater likelihood of early postdiagnosis improvement in seizure burden. Within this physical group postdiagnosis, we uncovered preliminary evidence for significantly greater attribution toward psychological roles in seizures as well as reduction in cognitive distortion surrounding the adverse consequences of seizures. These findings portend particular impact of such changes in illness perception for this group. Published by Elsevier Inc.

Objective: Performance validity testing is an increasingly vital component of neuropsychological evaluation, though administration of stand-alone performance validity tests (PVTs) can be time-consuming. As the Test of Memory Malingering (TOMM) is among the most commonly used and researched PVTs, much work has focused on creating abbreviated versions while preserving diagnostic accuracy. A recent addition to this effort, errors on the first 10 items of Trial 1 (TOMMe10), was analyzed for its utility in predicting TOMM performance. Method: Subjects were 180 veterans seen on a long-term epilepsy monitoring unit. TOMM learning trials, Word Memory Test (WMT), and WAIS-IV Digit Span (for Reliable Digit Span; RDS) were administered as part of a larger battery. Performance invalidity was classified using established cut scores. Diagnostic classification statistics were calculated predicting TOMM, WMT, and RDS performance, including sensitivity, specificity, receiver operating characteristics (ROC), and positive and negative predictive values for multiple TOMMe10 cut scores. Results: A cut score of2 errors on TOMMe10 yielded the highest sensitivity (.88) while maintaining.90 specificity when predicting TOMM (also supported by ROC analysis). This cut score was also optimal when validated against combinations of PVTs (e.g. two of TOMM, WMT, and RDS; WMT and/or RDS). Conclusions: TOMMe10 shows great promise in predicting future TOMM performance. In settings where time with patients is at a premium, 2 errors on TOMMe10 may be used as an early TOMM discontinue criteria, allowing examiners to use their limited time more effectively. The use of TOMMe10 in settings with varying TOMM failure base rates was discussed.

We aim to demonstrate, in a sufficiently powered and standardized study, that the success rate of inducing psychogenic nonepileptic seizures (PNES) without placebo (saline infusion) is noninferior to induction with placebo. The clinical data of 170 consecutive patients with suspected PNES who underwent induction with placebo from January 21, 2009 to March 31, 2013 were pair-matched with 170 consecutive patients with suspected PNES who underwent the same induction technique but without addition of placebo from April 1, 2013 to February 7, 2018 at the same center. The success rates of induction were 79.4% (135/170) without placebo and 73.5% (125/170) with placebo. The difference of these two proportions was 5.9%, with two-sided 95% confidence interval ranging from -3.6% to 15.2%, indicating a non-statistically significant difference. The lower bound of the 95% confidence interval (-3.6%) was above the noninferiority margin (delta = -5%), hence inferring noninferiority of induction without versus with placebo. The greater cumulative induction experiences of the clinician performer (influencing the manner/presentation of induction) may supplant the potential advantage from addition of placebo (the means utilized). Among experienced performers, provocative induction without placebo should be the preferred diagnostic approach, given more ethically acceptable transparency and the noninferior success rate when compared to the same induction technique with placebo.

Nonepileptic events (NEE) represent important differential diagnoses in patients with neurobehavioral paroxysms, especially those with apparent drug-resistant epilepsy. Errant recognition of NEE may not only subject the patient to potential complications of unnecessary epilepsy treatment, but delay the delivery of treatment that properly addresses the underlying pathology. For many patients with NEE, such as those with the conversion disorder psychogenic nonepileptic seizures (PNES) or with physiologic NEE (e.g., cardiac-induced syncope), delays in the provision of proper treatment have been shown to be associated with significant morbidity. This review focuses on clinical evaluations aiming to enhance the recognition of the different etiologies of NEE and distinguish between NEE and epilepsy, as well as between NEE of varying pathologies. Evidence-based treatments and management of NEE, particularly those pertaining to PNES, will also be discussed.

Purpose of Review In this review, we elucidate the evaluation process involved in the diagnosis of psychogenic non-epileptic seizures (PNES). Minimum clinical criteria required to attain this diagnosis via a staged approach are delineated. The psychological underpinnings and management of PNES from the neurologists' perspective are also explored.Recent Findings Helpful clues can be deduced from historytaking, seizure semiology, ictal/peri-ictal physical exam, and ictal/inter-ictal EEG data. No single clinical data point is definitively diagnostic of PNES. Instead, the level of certainty for PNES diagnosis is contingent upon concordance of the composite clinical evidence available. Robust neurologistpatient alliance not only facilitates the evaluation process but can influence therapeutic impact.Summary While diagnosis of PNES can be challenging, this diagnosis can be reliably made upon establishing concordance of the historical, physical exam, and video-EEG findings. Evidence-based treatments are available for pa-tients with PNES. Continued efforts remain necessary to enhance timely diagnosis and interdisciplinary management for patients with PNES.

To assess how good is the home video in distinguishing epileptic seizures from other paroxysmal events by assessing its sensitivity/specificity/positive predictive value(PPV)/negative predictive value(NPV) of events diagnoses based on home video (Video-EEG diagnoses of events as gold standard).

PURPOSE OF REVIEW:This article details the evaluation process involved in the diagnosis of psychogenic nonepileptic seizures (PNES). The psychological underpinnings, prognostic factors, and recent treatment advances of PNES are also reviewed.RECENT FINDINGS:The diagnosis of PNES is determined based on concordance of the composite evidence available, including historical and physical examination findings, seizure symptoms and signs, and ictal/interictal EEG. No single clinical data point is definitively diagnostic of PNES. The diagnosis of PNES can be challenging at times, such as when seizure documentation on video-EEG cannot be readily obtained. Yet, delayed diagnosis of PNES portends poor outcome. A multicomponent approach to the diagnosis of PNES, with use of an aggregate of available evidence, may facilitate diagnosis and then care of patients with PNES. Emerging evidence supports the effectiveness of cognitive-behavioral-based therapy in the treatment of these patients.SUMMARY:The diagnosis of PNES can be made reliably, and evidence-based treatment now exists. Continued efforts remain necessary to enhance prompt recognition and interdisciplinary management for patients with PNES.

OBJECTIVE:Prior to establishing the correct diagnosis, patients with psychogenic nonepileptic seizures (PNES) frequently endure significant costs and morbidities associated with utilization of health care resources. In this study of the US veterans population, we aimed to investigate for potential changes in health resource utilization before versus after video-EEG (VEEG) confirmation and disclosure of the PNES diagnosis. METHODS:We prospectively studied 65 veterans with VEEG confirmed diagnosis of PNES, and followed their health care utilization during the subsequent 3 years after the diagnosis. Primary outcomes entailed comparing the quantities of post-VEEG outpatient visits and diagnostic procedures versus those during the 3-year span prior to the diagnosis. Secondary outcome involved specifically the measures of seizure-related antiepileptic drug (AED) use from time points before and after VEEG. RESULTS:Within the category of non-psychiatric outpatient visits, we observed significant post-diagnostic decrease in the utilization of PNES-related outpatient visits (p < 0.001). Contrastingly, we found significant post-diagnostic increase in the utilization of non-PNES-related outpatient visits (p = 0.004). When examining exclusively for psychiatric outpatient visits, we further observed a trend toward increased attendance of outpatient visits (p = 0.056) after VEEG. Utilization of diagnostic procedures was not significantly different before versus after VEEG (p = 0.293). 52.3% of the patients were prescribed AEDs for seizure-related purpose during the one-year period leading up to VEEG. By comparison, only 7.7%, 12.3%, and 10.8% of the patients were still on AEDs for seizure-related purpose at the one-year, two-year, and three-year time points after VEEG, respectively. CONCLUSION:We demonstrate new evidence that VEEG confirmation of the PNES diagnosis among US veterans can significantly reduce key measures of non-psychiatric/PNES-related resource utilization, while also potentially associating with appropriate enhancement of psychiatric outpatient visits. However, our results suggest that within this patient population, further efforts are necessary to address heightened demands for non-PNES-related outpatient visits after VEEG.