Psychogenic non-epileptic seizures - diagnostic issues: a critical review

In this review we systematically assess our current knowledge about psychogenic non-epileptic seizures (PNES), epidemiology, etiology, with an emphasis on the diagnostic issues. Relevant studies were identified by searching the electronic databases. Case reports were not considered. Articles were included when published after 1980 up till 2005 (26 years). A total of 84 papers were identified; 60 of which were actual studies. Most studies have serious methodological limitations. An open non-randomized design, comparing patients with PNES to patients with epilepsy is the dominant design. The incidence of PNES in the general population is low. However, a relatively high prevalence is seen in patients referred to epilepsy centres (15-30%). Caution is needed in the clinical interpretation of ictal features suggested to be pathognomic for PNES. Video-EEG is widely considered to be the gold standard for diagnosing PNES. Still the differential diagnosis epileptic/non-epileptic seizures can be difficult. Despite the current available technical facilities, the mean latency between onset of PNES and final diagnosis as being non-epileptic and psychogenic is approximately 7 years. One of the reasons for diagnostic delay is that the diagnosis of PNES is often limited to a 'negative' process and consequently PNES is characterized as a 'non-disease' (i.e. 'not epilepsy'). The psychological diagnosis is thus an important, although not a conclusive, 'second phase' aspect of medical decision making. Specific relations between seizure presentation and underlying psychological mechanisms are not conclusive. A classification between major motor manifestations and unresponsiveness is recognized. With respect to psychological etiology, a heterogeneous set of factors have been identified that may be involved in the causation, development and provocation of PNES

Subgroup classification in patients with psychogenic non-epileptic seizures

Introduction In this open non-controlled clinical cohort study, the applicability of a theoretical model for the diagnosis of psychogenic non-epileptic seizures (PNES) was studied in order to define a general psychological profile and to specify possible subgroups. Methods Forty PNES patients were assessed with a PNES "test battery" consisting of eleven psychological instruments, e.g., a trauma checklist, the global cognitive level, mental flexibility, speed of information processing, personality factors, dissociation, daily hassles and stress and coping factors. Results The total PNES group was characterized by multiple trauma, personality vulnerability (in a lesser extent, neuropsychological vulnerabilities), no increased dissociation, many complaints about daily hassles that may trigger seizures and negative coping strategies that may contribute to prolongation of the seizures. Using factor analysis, specific subgroups were revealed: a ‘psychotrauma subgroup’, a ‘high vulnerability somatizing subgroup’ (with high and low cognitive levels) and a ‘high vulnerability sensitive personality problem subgroup’. Conclusion Using a theoretical model in PNES diagnosis, PNES seem to be a symptom of distinct underlying etiological factors with different accents in the model. Hence, describing a general profile seems to conceal specific subgroups with subsequent treatment implications. This study identified three factors, representing two dimensions of the model, that are essential for subgroup classification: psychological etiology (psychotrauma or not), vulnerability, e.g., the somatization tendency, and sensitive personality problems/characteristics (‘novelty seeking’). For treatment, this means that interventions could be tailored to the main underlying etiological problem. Also, further research could focus on differentiating subgroups with subsequent treatment indications and possible different prognoses

Psychogenic nonepileptic seizures in adults with epilepsy and intellectual disability:A neglected area

\u3cp\u3ePURPOSE: To describe the main characteristics of psychogenic nonepileptic seizures (PNES) in adults with epilepsy and intellectual disability (ID), and to analyse the differences regarding psychosocial functioning, epilepsy severity and ID between patients with PNES and a control group without PNES.\u3c/p\u3e\u3cp\u3eMETHODS: Medical records of adults with ID and epilepsy living at an epilepsy care facility (N = 240) were screened for PNES and evaluated by a neurologist. A control group consisting of patients with epilepsy and ID, without PNES, was matched according to age, sex and level of ID. Characteristics of PNES and epilepsy were provided by the subject's nursing staff or retrieved from patient charts, psychosocial data were collected by standardised questionnaires and level of ID was individually assessed using psychometric instruments.\u3c/p\u3e\u3cp\u3eRESULTS: The point prevalence of PNES was 7.1%. The patients with PNES (n = 15) were most often female and had a mild or moderate level of ID. Compared to controls, they showed more depressive symptoms, experienced more negative life events and had more often an ID discrepancy (ID profile with one domain particularly more impaired than another). Stress-related triggers were recognised in a large majority by the nursing staff.\u3c/p\u3e\u3cp\u3eCONCLUSION: PNES appears to be a relatively rare diagnostic entity among inpatients with both epilepsy and ID. However, the complexity of diagnosing PNES in this population, and the similarities in stress-related triggers for PNES in patients with and without ID, suggest that PNES may be underdiagnosed in the ID population. Diagnostic challenges of PNES and, as subcategory, reinforced behavioural patterns are discussed.\u3c/p\u3

Autonomic nervous system functioning associated with psychogenic nonepileptic seizures: analysis of heart rate variability

\u3cp\u3eObjective: Psychogenic nonepileptic seizures (PNESs) resemble epileptic seizures but originate from psychogenic rather than organic causes. Patients with PNESs are often unable or unwilling to reflect on underlying emotions. To gain more insight into the internal states of patients during PNES episodes, this study explored the time course of heart rate variability (HRV) measures, which provide information about autonomic nervous system functioning and arousal. Methods: Heart rate variability measures were extracted from double-lead electrocardiography data collected during 1-7. days of video-electroencephalography monitoring of 20 patients with PNESs, in whom a total number of 118 PNESs was recorded. Heart rate (HR) and HRV measures in time and frequency domains (standard deviation of average beat-to-beat intervals (SDANN), root mean square of successive differences (RMSSD), high-frequency (HF) power, low-frequency (LF) power, and very low-frequency (VLF) power) were averaged over consecutive five-minute intervals. Additionally, quantitative analyses of Poincaré plot parameters (SD1, SD2, and SD1/SD2 ratio) were performed. Results: In the five-minute interval before PNES, HR significantly (p <0.05) increased (d = 2.5), whereas SDANN (d = - 0.03) and VLF power (d = - 0.05) significantly decreased. During PNES, significant increases in HF power (d = 0.0006), SD1 (d = 0.031), and SD2 (d = 0.016) were observed. In the five-minute interval immediately following PNES, SDANN (d = 0.046) and VLF power (d = 0.073) significantly increased, and HR (d = - 5.1) and SD1/SD2 ratio (d = - 0.14) decreased, compared to the interval preceding PNES. Conclusion: The results suggest that PNES episodes are preceded by increased sympathetic functioning, which is followed by an increase in parasympathetic functioning during and after PNES. Future research needs to identify the exact nature of the increased arousal that precedes PNES.\u3c/p\u3

Resting-state networks and dissociation in psychogenic non-epileptic seizures

\u3cp\u3eObjective: Psychogenic non-epileptic seizures (PNES) are epilepsy-like episodes which have an emotional rather than organic origin. Although PNES have often been related to the process of dissociation, the psychopathology is still poorly understood. To elucidate underlying mechanisms, the current study applied independent component analysis (ICA) on resting-state fMRI to investigate alterations within four relevant networks, associated with executive, fronto-parietal, sensorimotor, and default mode activation, and within a visual network to examine specificity of between-group differences. Methods: Twenty-one patients with PNES without psychiatric or neurologic comorbidities and twenty-seven healthy controls underwent resting-state functional MR imaging at 3.0T (Philips Achieva). Additional neuropsychological testing included Raven's Matrices test and dissociation questionnaires. ICA with dual regression was used to identify resting-state networks in all participants, and spatial maps of the networks of interest were compared between patients and healthy controls. Results: Patients displayed higher dissociation scores, lower cognitive performance and increased contribution of the orbitofrontal, insular and subcallosal cortex in the fronto-parietal network; the cingulate and insular cortex in the executive control network; the cingulate gyrus, superior parietal lobe, pre- and postcentral gyri and supplemental motor cortex in the sensorimotor network; and the precuneus and (para-) cingulate gyri in the default-mode network. The connectivity strengths within these regions of interest significantly correlated with dissociation scores. No between-group differences were found within the visual network, which was examined to determine specificity of between-group differences. Conclusions: PNES patients displayed abnormalities in several resting-state networks that provide neuronal correlates for an underlying dissociation mechanism.\u3c/p\u3