SUMMARYStress is one of the most frequently self-identified seizure triggers in patients with epilepsy; however, most previous publications on stress and epilepsy have focused on the role of stress in the initial development of epilepsy. This narrative review explores the causal role of stress in triggering seizures in patients with existing epilepsy. Findings from human studies of psychological stress, as well as of physiologic stress responses in humans and animals, and evidence from nonpharmacologic interventions for epilepsy are considered. The evidence from human studies for stress as a trigger of epileptic seizures is inconclusive. Although retrospective self-report studies show that stress is the most common patient-perceived seizure precipitant, prospective studies have yielded mixed results and studies of life events suggest that stressful experiences only trigger seizures in certain individuals. There is limited evidence suggesting that autonomic arousal can precede seizures. Interventions designed to improve coping with stress reduce seizures in some individuals. Studies of physiologic stress using animal epilepsy models provide more convincing evidence. Exposure to exogenous and endogenous stress mediators has been found to increase epileptic activity in the brain and trigger overt seizures, especially after repeated exposure. In conclusion, stress is likely to exacerbate the susceptibility to epileptic seizures in a subgroup of individuals with epilepsy and may play a role in triggering "spontaneous" seizures. However, there is currently no strong evidence for a close link between stress and seizures in the majority of people with epilepsy, although animal research suggests that such links are likely. Further research is needed into the relationship between stress and seizures and into interventions designed to reduce perceived stress and improve quality of life with epilepsy.
Epilepsy is a neurological disorder that causes changes in the autonomic nervous system. Heart rate variability (HRV) reflects the regulation of cardiac activity and autonomic nervous system tone. The early detection of epileptic seizures could foster the use of new treatment approaches. This study presents a new methodology for the prediction of epileptic seizures using HRV signals. Eigendecomposition of HRV parameter covariance matrices was used to create an input for a support vector machine (SVM)-based classifier. We analyzed clinical data from 12 patients (9 female; 3 male; age 34.5 ± 7.5 years), involving 34 seizures and a total of 55.2 h of interictal electrocardiogram (ECG) recordings. Data from 123.6 h of ECG recordings from healthy subjects were used to test false positive rate per hour (FP/h) in a completely independent data set. Our methodological approach allowed the detection of impending seizures from 5 min to just before the onset of a clinical/electrical seizure with a sensitivity of 94.1%. The FP rate was 0.49 h−1 in the recordings from patients with epilepsy and 0.19 h−1 in the recordings from healthy subjects. Our results suggest that it is feasible to use the dynamics of HRV parameters for the early detection and, potentially, the prediction of epileptic seizures.
The results showed clear impairments of emotion processing in patients with PNES compared to healthy individuals, which were associated with greater psychological distress and reduced mental health functioning. These findings seem to support the face validity of the EPS-25 as a measure for PNES patients and its potential as a tool to assess the effectiveness of psychological interventions.
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