Acton, Emily K

Abstract Emotional experiences during focal seizures are often misinterpreted as psychiatric disorders. We aimed to evaluate symptoms involving affective symptoms at seizure onset. We aimed to identify the most prevalent affective symptoms at seizure onset and characterize their localizing and lateralizing value. We performed a scoping review based on Preferred Reporting Items for Systematic reviews and Meta‐Analyses–extension for Scoping Reviews guidelines. A systematic search identified records from 4 databases: PubMed, Embase, CINAHL (via EBSCOhost), and Web of Science. Two reviewers independently screened titles/abstracts and full texts; discrepancies were resolved by consensus. This review focused on patients with focal seizures, as affective symptoms may occur in generalized epilepsies. The affective symptoms: fear, anxiety, panic, sadness, mystic, ecstatic, sexual, and mirth were identified, and semiology was evaluated in accordance with ILAE guidelines. Symptom onset, frequency, brain localization, and video‐EEG monitoring technique were evaluated to assess localization and lateralization of regional networks. Scalp EEG, invasive EEG recordings, and electrical stimulation were analyzed. A total of 1276 documents were identified, with 98 studies included for review. Fear was the most frequently reported ictal emotion, identified in 274 patients (66%), predominantly in temporal lobe epilepsy. Sadness and sexual, ecstatic symptoms were also consistently associated with temporal networks. Mirth was more frequently reported with frontal onset seizures. Evidence, primarily from Class IV studies, reported right hemispheric predominance for ecstasy, mystic, and sexual symptoms at seizure onset. Ictal affective symptoms at seizure onset yield localizing information. The limbic system, especially the temporal lobe, followed by the frontal lobe, was the most common site of origin. Fear was the most common spontaneous and electrically elicited symptom, followed by anxiety. While bi‐hemispheric lateralization occurred, right lateralization predominated. Recognizing paroxysmal affective symptoms as ictal phenomena may reduce misdiagnosis and aid presurgical evaluation in drug‐resistant focal epilepsy.

Abstract 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.

AbstractThe purpose of this case‐matched study was to determine how frequently fibromyalgia is associated with different paroxysmal neurological disorders and explore the utility of fibromyalgia as a predictor for the diagnosis of psychogenic non‐epileptic seizures. The billing diagnosis codes of 1,730 new, non‐selected patient encounters were reviewed over a three‐year period for an epileptologist in a neurology clinic to identify all patients with historical diagnoses of fibromyalgia. The frequency with which epileptic seizures, psychogenic non‐epileptic seizures, and physiological non‐epileptic events were comorbid with fibromyalgia was assessed. Age and gender case‐matched controls were used for a between‐group comparison. Wilcoxon tests were used to analyse interval data, and Chi‐square was used to analyse categorical data (p<0.05). Fibromyalgia was retrospectively identified in 95/1,730 (5.5%) patients in this cohort. Females represented 95% of the fibromyalgia sample (age: 53 years; 95% CI: 57, 51). Forty‐three percent of those with fibromyalgia had a non‐paroxysmal, neurological primary clinical diagnosis, most commonly chronic pain. Paroxysmal events were present in 57% of fibromyalgia patients and 54% of case‐matched controls. Among patients with fibromyalgia and paroxysmal disorders, 11% had epileptic seizures, 74% had psychogenic non‐epileptic seizures, and 15% had physiological non‐epileptic events, compared to case‐matched controls with 37% epileptic seizures, 51% psychogenic non‐epileptic events, and 12% physiological non‐epileptic events (p = 0.009). Fibromyalgia was shown to be a predictor for the diagnosis of psychogenic non‐epileptic seizures in patients with undifferentiated paroxysmal spells. However, our results suggest that the specificity and sensitivity of fibromyalgia as a marker for psychogenic non‐epileptic seizures in a mixed general neurological population of patients is less than previously described.