Inter-ictal fatigue and antiepileptic drugs in patients with epilepsy

Seizure-related stress and arousal responses mediate a relationship between anxiety trait and state in epilepsy

BACKGROUND

Epilepsy causes substantial psychological distress and anxiety, primarily due to seizures. However, the impact of stress responses and changes in arousal and their association with anxiety patterns in patients with epilepsy (PWE) remains unclear. This study aimed to investigate the relationships among seizures, stress and arousal characteristics, and trait and state anxiety characteristics in PWE.

METHODS

Our sample consisted of 159 outpatients with epilepsy recruited from five institutions in Japan in 2020. Participants completed the State-Trait Anxiety Inventory-Form JYZ (STAI) and the Japanese-Stress Arousal Check List (J-SACL). We analyzed the correlations between inventory scores and clinical information. Using principal component analysis (PCA), we derived epilepsy-specific stress/arousal characteristics, which accounted for high arousal and low-stress levels, termed epilepsy-specific stress or arousal response (ESAR), from the J-SACL scores. We conducted a mediation analysis to assess the mediating role of ESAR in the relationship between traits and state anxiety.

RESULTS

We found significant correlations between J-SACL stress and arousal factors (r = -0.845, p < 0.001), ESAR and seizure frequency (r = -0.29, p < 0.001), ESAR and trait anxiety scores on the STAI (r = -0.77, p < 0.0001), and ESAR and state anxiety scores on the STAI (r = -0.60, p < 0.0001). Mediation analysis supported by the Monte Carlo method revealed that ESAR significantly mediated the association between trait and state anxiety.

CONCLUSIONS

These findings elucidate the epilepsy-specific stress and arousal characteristics and their roles in mediating traits and state anxiety. These results may reflect the long-term clinical course and unique emotion recognition tendencies in epilepsy.

Rasch analysis of fatigue severity scale in patients with epilepsy

OBJECTIVE

To utilize the Rasch model to validate and assess the psychometric properties of the Fatigue Severity Scale (FSS) in patients with epilepsy.

METHODS

A total of 307 patients (age > 18 years) with a confirmed diagnosis of epilepsy were consented to participate. Exclusion criteria included patients with psychogenic nonepileptic events, cognitive disabilities, and patients who did not speak/understand English. The nine-step FSS was programmed into software administered to patients on electronic tablets, and patient responses were auto-scored. The Rasch rating scale model (RSM) was used to evaluate the unidimensionality, reliability, and targeting of the FSS. To assess unidimensionality, we examined infit and outfit mean squares. We also assessed unidimensionality of the FSS using a principal component analysis of Rasch residuals, where residuals are understood as the difference between observed and expected data values. We evaluated the internal consistency of person and item performance by examining separation reliability estimates and separation ratio. Differential Item Functioning (DIF) was calculated for gender.

RESULTS

There was mixed evidence regarding the extent to which the FSS fit the Rasch model. Outfit values ranged from 0.52 to 2.72 and infit values were 0.60 to 2.18, strongly suggesting the presence of misfitting items: Item 1 ("My motivation is lower when I am fatigued") and Item 2 ("Exercise brings on my fatigue").

SIGNIFICANCE

The nine-item FSS showed fair psychometric properties in this sample of patients with epilepsy. Our study provides unique, supportive information for the use of a modified version of the FSS, omitting the first two items, in patients with epilepsy. Given the prevalence of fatigue and other neuropsychiatric comorbidities of epilepsy, having a validated fatigue scale can aid healthcare providers to identify moderate-to-severe fatigue levels in patients with epilepsy and address the plausible risk factors.