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Fatigue and its Related Factors in Patients with Epilepsy and Psychogenic Non-epileptic Seizure: a Cross-Sectional Study

  • Mahtab Ramezani
  • Marjan Asadollahi
  • Elham Kashian
  • Pooya Payandemehr
  • Ehsan KarimialavijehEmail author
Medicine
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Abstract

The aim of the present study was to investigate the prevalence of fatigue and its related factors in patients with epilepsy and psychogenic non-epileptic seizures. From January 2017 to January 2018, a descriptive cross-sectional research study was conducted among adult (aged over 18) patients with epilepsy in the neurology clinic of a university-affiliated hospital in Tehran, Iran. The Fatigue Severity Scale was used to determine the prevalence of fatigue, and the relationships between fatigue, demographic characteristics, and clinical properties were evaluated. During the study period, 100 patients were included, comprising 70 (70%) patients diagnosed with epileptic seizures and 30 (30%) with psychogenic non-epileptic seizures. Fatigue affected 24 patients (34%) out of 70 individuals with epileptic seizures and six patients (20%) out of 30 patients with psychogenic non-epileptic seizures. There was no statistically significant relationship between the incidence of fatigue and age, gender, level of education, occupation, age at the onset of the seizures, duration of the disease, and time since the last seizure. However, fatigue was significantly correlated with the demographic variable of being unmarried (p = 0.007). Furthermore, there was a significant relationship between fatigue and taking carbamazepine and levetiracetam (p = 0.001). Our study revealed that fatigue was a prevalent problem (30%) in patients with epilepsy and psychogenic non-epileptic seizures. Moreover, fatigue was correlated with marital status and the consumption of carbamazepine and levetiracetam.

Keywords

Seizure Fatigue Epilepsy Cross-sectional study 

Introduction

Fatigue affects patients both physically and emotionally and is considered the most important bio-alert in human health [1]. Fatigue is associated with various types of neurological diseases such as multiple sclerosis (MS) [2, 3], Parkinson’s disease [3, 4], stroke [3, 5, 6], and epilepsy [3, 7, 8]. Epilepsy is a common neurological disease and is the second most commonly reported disorder of the central nervous system in the world [9]. The frequency of fatigue in patients suffering from epilepsy is 29.5%. Fatigue can be more severe in epileptic patients and it can even worsen the incidence of seizures [9]. Psychogenic non-epileptic seizures (PNES) are considered to be attacks similar to epilepsy with no physical origins. Epilepsy affects all aspects of daily life and uncontrolled seizures can lead to irreversible brain damage [10]. Studies have shown that patients with epilepsy experience a lower quality of life than patients with other chronic diseases such as asthma or diabetes [6, 11]. According to the current literature, the frequency of fatigue in patients with PNES is higher than that in normal individuals, which can lead to a low quality of life in these patients [12, 13].

In 2006, Yan et al. [14] indicated that the frequency of fatigue in patients with epilepsy is high and has determining effects on patients’ lives. Similarly, the results of a systematic review by Kwon et al. [15] showed a significant prevalence of fatigue among patients with epilepsy. Some studies have reported that fatigue in epilepsy patients is associated with depression, anxiety, sleep disorders, and suicide [7, 15, 16, 17], while other epilepsy-related factors, such as the duration of epilepsy, the time since the last seizure, the frequency of seizures per month, the duration of treatment with anti-epileptic drugs (AEDs), the number of AEDs, and the type of AEDs have not been correlated with fatigue [7, 15]. One study [7] observed an increased frequency of fatigue among patients who had multiple seizures, but did not find any statistical significance. Nevertheless, the association between fatigue and epilepsy-related factors remains unclear. The early diagnosis and treatment of fatigue can promote an improved quality of life in patients with epilepsy, enabling both patients and caregivers to effectively manage the course of the disease.

The purpose of our study was to determine the frequency of fatigue among a group of patients with epilepsy and PNES. The secondary objective was to identify the patient-, illness-, and treatment-related factors that are associated with fatigue.

Method

Participants

Patients who were referred to the epilepsy clinic at a university-affiliated hospital in Tehran, Iran, were recruited. The inclusion criteria for patients comprised experiencing seizures or the diagnosis of PNES and an age of over 18 years. The exclusion criteria included mental retardation and the presence of another illness based on the patients’ prior medical records, including neurological disorders (multiple sclerosis, Parkinson’s disease, movement disorders, etc.), psychological disorders (major depression, generalized anxiety disorder, psychosis, etc.), and chronic diseases (renal failure, cirrhosis, heart failure, chronic obstructive pulmonary disease, etc.).

Study Design

This was a descriptive cross-sectional study conducted between June 2017 and June 2018.

Convenience sampling was used to enroll the participants. Given the frequency of fatigue in 60% of epileptic patients, the sample size in this study was calculated as 100 patients. The local ethics committee of Shahid Beheshti University of Medical Sciences approved the study.

Psychometric Instruments

The Fatigue Severity Scale (FSS) was used to evaluate fatigue severity and the impact of fatigue on performance and quality of life.

A self-administered questionnaire based on the FSS was used in which the internal consistency of the questionnaire items was calculated by Cronbach’s alpha coefficient as 0.96. The minimum score of the questionnaire was nine and the maximum was 63. A score of 36 and higher was considered to indicate fatigue [15].

Study Procedure

All patients were diagnosed by an epilepsy specialist using long-term electroencephalography (EEG) monitoring (LTM). After obtaining informed consent, a researcher recorded the demographic characteristics of the participants, including age, gender, levels of education, occupation, marital status, accompanying diseases, age at the onset of seizures, duration of epilepsy, and the frequency of seizures, seizure type and taking AEDs, including the dosage and type of AED. Then, patients were asked to complete the questionnaire.

Statistical Analyses

To provide descriptive statistics for the quantitative and qualitative variables, the mean ± standard deviation (SD) were used. To analyze the quantitative variables, Student’s t test was employed. A Mann-Whitney U test was used in the absence of parametric conditions. To analyze the qualitative variables, a chi-square test (K2) and Fisher’s exact test were employed. Multivariate regression analysis was performed to identify the factors associated with fatigue.

All the tests were performed using SPSS Statistics (Version 19.0, SPSS Inc., Chicago, IL, USA) and a p value < 0.05 was considered to be the level of significance.

Results

A total of 100 patients including 38 men (38%) and 62 women (62%) with an age of 31.6 ± 10.08 (mean ± SD) were included in the study. The demographic characteristics of the participants, including levels of education, occupation, and marital status, are illustrated in Table 1.

Based on the opinion of an epilepsy specialist using an LTM method, 70 patients (70%) were diagnosed with epileptic seizures and 30 other patients (30%) were diagnosed with psychogenic non-epileptic seizures. Fatigue affected 24 patients (34%) out of 70 with epileptic seizures and six patients (20%) out of 30 with PNES (p = 0.23). There was no statistically significant relationship between fatigue and age (p = 0.21), gender (p = 0.12), levels of education (p = 0.11), occupation (p = 0.24), age at the onset of seizures (p = 0.11), the duration of epilepsy (p = 0.16), the time since the last seizure (p = 0.13), the frequency of seizures (p = 0.15), and the duration of treatment with AEDs (p = 0.07). However, there was a significant relationship between fatigue and marital status; fatigue was significantly correlated with being unmarried (p = 0.007). Moreover, a significant relationship was observed between the incidence of fatigue symptoms and the consumption of carbamazepine and levetiracetam (p = 0.001) (Table 1).

We found that marital status and taking carbamazepine and levetiracetam in monotherapy were independently predictive of fatigue (Table 2).
Table 1.

Correlation of fatigue and the characteristics of epilepsy and PNES patients.

Characteristic

Mean ± SD/n (%)

Fss > 36

(p value)

Age (years)

31.6 ± 10.08

0.21

Gender

  Male

  Female

38 (38)

62 (62)

012

Education level

  Uneducated

  Primary school

  High school

  Academic education

4 (4)

31 (31)

42 (42)

23 (23)

0.11

Marital Status

  Married

  Single

42 (42)

58 (58)

0.007

Employment status

  Unemployed

  Employed full-time

  Employed part-time

63 (63)

20 (20)

17 (17)

0.24

Duration of epilepsy or PNES (year)

15 ± 12.5

0.16

Age at the onset of epilepsy or PNES (year)

25.1 ± 13.1

0.11

Last seizure (day)

74 ± 116.3

0.13

Seizure frequency/month

16.4 ± 30.2

0.15

Duration of taking AEDs (month)

166 ± 136.8

0.07

Number of taken AEDs

  No AEDs

  Monotherapy

  Dual therapy

  Triple therapy

  Multitherapy

7(7)

42 (42)

35 (35)

14 (14)

2 (2)

0.17

Type of AEDs

  Sodium valproate

  Carbamazepine

  Phenytoin

  Phenobarbital

  Lamotrigine

  Levetiracetam

  Topiramate

50(50)

39(39)

5(5)

13(13)

28(28)

23(23)

3(3)

0.001*

*Correlation was significant for levetiracetam and carbamazepine

PNES, psychogenic non-epileptic seizures; AEDs, anti-epileptic drugs

Table 2

Multiple linear regression analysis for participant variables

Variable

Coefficient

Standard error

p value

R 2

1. Marital status

− 1.2

0.2

0.001

0.35

2. Marital status

Carbamazepine

− 0.87

0.17

0.001

0.43

3. Marital status

Carbamazepine

Levetiracetam

− 0.8

0.18

0.001

0.48

Discussion

The results of the present study indicate that fatigue is prevalent among patients with epilepsy and PNES (30%). Factors that had a significant correlation with fatigue were being single and taking carbamazepine and levetiracetam.

In a study conducted in 2006 in China by Yan et al. [14], 105 patients (45 women and 60 men) with seizures were investigated. The findings of this investigation revealed that 29.5% of the patients were suffering from fatigue. No relationship was found between fatigue and the demographic characteristics of the participants, while a low quality of sleep, depression, and anxiety were cited as factors affecting the incidence of fatigue symptoms. The frequency of fatigue in our study was similarly reported as 30%, which was consistent with the values in the study by Yan et al. In a systematic review, Kwon et al. [15] included 12 studies on fatigue and epilepsy. The results of this investigation also indicated a significant increase in fatigue among patients with epilepsy. The frequency of fatigue in 700 patients in seven studies was reported as 47.1% and sleep disorders and depression were mentioned as risk factors affecting fatigue. In addition, seven studies out of 12 investigations demonstrated a significant relationship between depression and the incidence of fatigue symptoms [15]. In 2006, Senol et al. [18] reported that the most important factors affecting the quality of life of patients with epilepsy were fatigue, depression, and the frequency of seizures. They also mentioned fatigue as an independent predictor of the quality of life of these patients. A few studies showed that the frequencies of fatigue in patients with PNES were higher than those in normal populations and even in patients with epilepsy. In the present study, fatigue was frequent among PNES patients (20%) but we did not find a significant difference between patients with epilepsy and PNES in terms of the frequency of fatigue.

Fatigue is a prevalent problem among patients with epilepsy and PNES and has detrimental effects on the quality of life of these patients. Early diagnosis and treatment can effectively promote an improved quality of life in patients with epilepsy [18].

Validated fatigue measurements can help to screen fatigue in patients with epilepsy and PNES and make necessary interventions, such as talking therapies, lifestyle modifications (healthy diet, physical activities, good sleep routine), providing more social support, and the adjustment of AED regimens [15]. We recommend that future comparison studies compare the effects of AEDs on fatigue in these patients. We also propose that policy-makers provide more social support and facilities for patients with epilepsy to decrease the effects of the illness on the social performance of these patients.

The limitation of the present study was the small sample size, so there is a need to conduct studies with a larger sample size in order to determine the risk factors of fatigue in patients with epilepsy and PNES. In addition, we did not measure the dosing and plasma concentration of AEDs and this will affect our results regarding fatigue in patients who take levetiracetam and carbamazepine.

Conclusion

According to the findings of this study, fatigue is prevalent among patients with epilepsy and PNES. Additionally, being single and taking carbamazepine and levetiracetam were the factors associated with fatigue.

Notes

Author Contributions

Study design: Asadollahi M

Data collection and analysis: Kashian E, Ramezani M

Manuscript writing: Karimialavijeh E and Ramezani M

Final proof and revision: Payandemehr P

Compliance with Ethical Standards

The study was approved by the Institutional Review Board of the Shahid Beheshti of Medical Sciences.

Conflict of Interest

The authors have declared that there is no conflict of interest.

Research Involving Human Participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all participants included in the study.

Supplementary material

42399_2019_133_MOESM1_ESM.pdf (1.6 mb)
ESM 1 (PDF 1606 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mahtab Ramezani
    • 1
  • Marjan Asadollahi
    • 1
  • Elham Kashian
    • 1
  • Pooya Payandemehr
    • 2
  • Ehsan Karimialavijeh
    • 2
    Email author
  1. 1.Loghman HospitalShahid Beheshti University of Medical SciencesTehranIran
  2. 2.Department of Emergency Medicine, Shariati HospitalTehran University of Medical SciencesTehranIran

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