Fatigue,sleep quality,depression symptoms,and antiseizure medication resistance in patients with newly diagnosed epilepsy

Abstract

Background:

Complaints of fatigue and poor sleep quality are common in patients with epilepsy. Fatigue may precipitate seizures, and patients with poor sleep quality have higher frequency of seizures and are more likely to have symptoms of depression.

Objectives:

This study aims to determine the association of baseline fatigue and sleep quality with antiseizure medication (ASM) resistance in patients with newly diagnosed epilepsy (PWNDE). We also evaluate whether the association is mediated by depression symptoms.

Methods:

We performed a prospective cohort study of PWNDE at comprehensive epilepsy center in Northeast China between June 2020 and May 2024. Fatigue, sleep quality, and depression symptoms were assessed at baseline. All patients were followed for 24 months for ASM-resistant epilepsy. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) of ASM resistance. Models fitted with restricted cubic spline were performed to test for linear and nonlinear shapes of each association. Mediation analysis was used to estimate the mediating effects of depression severity on association between fatigue, sleep quality, and ASM resistance.

Results:

A total of 189 patients (59 ASM-resistant cases and 130 ASM-responsive controls) were included in the final analysis. Baseline fatigue (HR, 1.98; 95% confidence interval (CI), 1.094–3.583, p = 0.024) and poor sleep quality (HR, 2.193; 95% CI, 1.29–3.729, p = 0.004) were associated with an increased hazard of ASM resistance in PWNDE after full adjustments. There exists a nonlinear association between Fatigue Severity Scale score and the hazard of ASM resistance (P for nonlinear = 0.012). Depression severity partly mediated the effect of fatigue and sleep quality on ASM resistance, with mediated proportions of 18.5% for the fatigue and 23.7% for the sleep quality.

Conclusion:

Baseline fatigue and poor sleep quality were associated with an increased risk of ASM resistance. The association between fatigue, sleep quality, and ASM resistance were partly mediated by depression severity. These findings emphasize that patients with ASM-resistant epilepsy are more likely to have fatigue, depression, and poor sleep quality at baseline and this may be unrelated to ASM intake.

Plain language summary

Association between fatigue, sleep quality, depression symptoms, and antiseizure medication resistance in patients with newly diagnosed epilepsy

Why was the study done? Complaints of fatigue and poor sleep quality are common in patients with epilepsy. A crucial problem related to fatigue is that it may precipitate a single or multiple seizures. Patients with poor sleep quality also have high seizures frequency and depression symptoms. We wondered whether patients with fatigue or poor sleep quality have higher risk of developing resistance to anti-seizure medication. We also investigate the role of depression symptoms in the relationship.

What did the researchers do? The research team invited patients with newly diagnosed epilepsy to participate in this study in Northeast China. The participants were asked to complete questionnaires to assess fatigue, sleep quality and depression symptoms. Then the participants were treated with anti-seizure medications. The researchers observed how the patients responded to the anti-seizure medications over 24-month period.

What did the researchers find? A total of 189 patients participated in this study. We observed that 59 patients had resistance to anti-seizure medication and 130 responded well to drugs. Patients who had fatigue were more likely to experience drug resistance. Similarly, patients who had poor sleep quality were more likely to have drug resistance. Additionally, depression symptoms play an important in the effect of fatigue and sleep quality on drug responsiveness.

What do the findings mean? This study has some important findings. Patients who had fatigue or poor sleep quality were more likely to responded poorly to anti-seizure medications. We also observed the mediating role of depression severity. These findings tell us the importance of assessing fatigue, sleep quality and depression symptoms in patients with newly diagnosed epilepsy which may help identify those at greater risk of drug resistance.

Keywords

ASM resistance depression symptoms fatigue PWNDE sleep quality

Introduction

Epilepsy is one of the most common chronic brain diseases, affecting over 70 million people worldwide.¹ Epilepsy is characterized by a lasting predisposition to generate spontaneous epileptic seizures and has numerous neurobiological, cognitive, and psychosocial consequences.² Seizures cannot be fully controlled in about one-third of patients with epilepsy (PWE) despite the availability of over 20 antiseizure medications (ASMs) since the 1980s; this phenomenon is ASM resistance.^3,4 ASM-resistant epilepsy is associated with cognitive and psychiatric comorbidities, socioeconomic impairment, injuries, and a 9.3–13.4 times higher mortality rate than in seizure-free patients.⁵ These adverse events highlight the urgency of a better understanding of potential pathophysiological mechanisms and modifiable risk factors for ASM resistance. Identifying clinically useful predictors of individual responsiveness to ASM treatment would have major clinical benefits and may help to improve epilepsy management.⁶

Fatigue is a general feeling of being tired or drained of energy. Although the mechanism of fatigue remains unclear, complaint of fatigue is common in PWE and may be related with depression and sleep-related disorders.^7,8 A crucial problem related to fatigue is that it may precipitate a single or multiple seizures in PWE.^9,10 Fatigue was more severe in epilepsy patients than in controls without epilepsy, especially when seizures were not controlled.⁸ Sleep patterns have direct effects on fatigue, and good sleep provides an effective way to prevent fatigue.¹¹ Sleep and epilepsy share a complex and bidirectional relationship, as one can significantly influence the other, and vice versa.^12–14 Poor sleep quality may be related with high seizures frequency, symptoms of fatigue, and depression in PWE.¹⁵ Pharmacoresponsive PWE had a better sleep quality compared with pharmacoresistant patients.¹⁶ However, prior studies almost employed cross-sectional design, and definitive conclusions about causality cannot be made. The literature is sparse on the association between fatigue, sleep quality, and development of ASM resistance in a cohort of patients with newly diagnosed epilepsy (PWNDE). Understanding the complexities of this relationship is an important step toward improving epilepsy management.

Therefore, the main aim of this prospective study was to explore the association between fatigue, sleep quality, and the risk of ASM resistance in PWNDE. Additionally, depression has been identified as a significant predictor of ASM responsiveness.^17,18 Secondary aim was to determine whether the effect of fatigue and sleep quality on ASM resistance was mediated by depression severity.

Methods

Study design and participants

We performed a prospective cohort study that recruited patients aged ⩾18 years with newly diagnosed epilepsy who treated and followed at the epilepsy outpatient clinic of The First Hospital of Jilin University between June 2020 and May 2024. All patients had experienced ⩾2 seizures or a single seizure with an EEG showing epileptiform discharges or a focal lesion on magnetic resonance imaging (MRI) before ASM treatment. The diagnosis of epilepsy was determined by the treating physician in accordance with International League Against Epilepsy (ILAE) definitions.¹⁹ All patients completed detailed clinical assessment, questionnaires (described below), MRI, and video-EEG examinations at baseline. The decisions about the choice of ASMs use and method of drug titration were based on physicians’ experience and ILAE recommendations.^2,20 Patients were followed every 6 months for 24 months for ASM-resistant epilepsy. Patients who had previously been treated with ASM were excluded. Also excluded for this study were patients who had severe brain diseases other than epilepsy (e.g., dementia and Parkinson’s disease) or refused to participate. This study was approved by the ethics committee of The First Hospital of Jilin University (approval No: 2017-326), and written informed consent was obtained from all patients or the substitute decision-maker.

Neurological assessment

At the time of the first visit, baseline demographic information was collected, along with main epilepsy-related variables. Baseline demographic information included age (continuous), sex (categorized as female and male), and education level (categorized as university and above, middle school, and primary school and below). The epilepsy-related variables included epilepsy duration (continuous), epilepsy type (categorized as focal, generalized, and unknown), family history of epilepsy in a first-degree relative, >50% nocturnal seizures, >5 seizures pretreatment, symptomatic epilepsy, EEG spike-wave discharges (SWs) burden (categorized as none or rare, occasional, frequent, and abundant). We considered epilepsy duration to be an interval between first seizure day to date of diagnosis. The epilepsy type was determined by the treating physician according to the ILAE classification.²¹ More than 50% nocturnal seizures was defined as >50% of the patient’s seizures occurring during sleep, including daytime naps. Symptomatic epilepsy was determined according to the etiology of epilepsy.²² EEG findings were reported by a neurologist with EEG fellowship training, and these reports were subsequently reviewed by a second epileptologist, who made a final classification for this study. The burden of SW in EEG was determined using the American Clinical Neurophysiology Society critical care EEG terminology for sporadic epileptiform discharges as follows: (1) none or rare (<1 SW/h), (2) occasional (>1 SW/h but <1/min), (3) frequent (>1 SW/min but <1 every 10 s), and (4) abundant (>1 SW every 10 s).²³

Questionnaires

Fatigue was assessed at baseline using the Fatigue Severity Scale (FSS), a nine-item questionnaire designed to measure fatigue severity in multiple medical and neurological conditions.^24,25 Each item is a statement on fatigue that the subject rates from 1 to 7 points, and higher scores indicate greater fatigue severity. The total score produced by the FSS ranges from 9 to 63, and the total is divided by 9 to determine the mean. Patients with a mean score of >4 were defined as having significant fatigue.^7,24 Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), a self-report questionnaire measuring the patient’s perception of his or her sleep quality and disturbances over the last 4 week time period.²⁶ The scale assessed seven aspects related to sleep quality, with total scores ranging from 0 (best) to 21 (worst); higher scores indicate poorer sleep quality. The PSQI could distinguish “good quality” (PSQI score ⩽5) from “poor quality” (PSQI score >5) with sensitivity of 89.6% and specificity of 86.5%.^26,27 The Neurological Disorder Depression Inventory for Epilepsy (NDDI-E) is an epilepsy-specific self-rating screening instrument designed to rapidly determine major depression in neurology clinics.²⁸ It was designed to identify depression symptoms that can be set apart from ASM side effects. The total score of NDDI-E ranged from 6 to 24, and total score greater than 13 was considered “positive” for depression.^29,30 Furthermore, the Chinese version of FSS, PSQI, and NDDI-E were both validated.^31–33

Follow-up and outcome

Patients were prospectively followed up for 24 months by their treating physicians. Over a 24-month follow-up period, patients were interviewed every 6 months regarding seizure recurrence, medication compliance and changes, and potential adverse effects via the phone or/and clinical visit. Additionally, patients were asked to contact the researchers within days of experiencing a breakthrough seizure. The outcome variable was a binary variable of ASM-resistant versus ASM-responsive epilepsy. We eventually identified two groups of patients: (1) ASM-resistant cases and (2) ASM-responsive controls. According to the ILAE definition, ASM resistance requires failure of two or more appropriately used ASMs due to inefficacy, with failure being defined as not achieving a sustained period of seizure freedom (i.e., freedom from all seizure types for 12 months or 3 times the longest preintervention interseizure interval).³⁴ Consequently, ASM-responsive would mean that patients are free from all seizure types for 12 months or 3 times the longest preintervention interseizure interval, whether having failed 0 or 1 appropriately used ASM.³⁴ To ensure that patients had an opportunity to fail ASM due to inefficacy, we required that an ASM had to be used continuously for ⩾6 months.

Statistical analyses

Descriptive statistical analyses were conducted to analyze demographic and clinical characteristics, using frequencies and percentages to describe categorical variables and median and interquartile range to describe continuous variables. Statistical significance was determined using the Chi-square test or Fisher’s exact test for categorical variables and Wilcoxon rank-sum test for continuous variables. Probability levels of p < 0.05 were considered statistically significant. To examine the association between fatigue, sleep quality, and ASM resistance, Cox proportional hazard regression model was performed with the length of the follow-up period as the basis for measuring time; hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. The variables included in the multivariable model were those clinically relevant and potentially associated (p < 0.1) in the univariate analysis. Multivariable Cox model was adjusted for age, sex, family history, symptomatic epilepsy, EEG SW burden, and depression. To explore the potential nonlinear effects and visualize the dose–response association, restricted cubic spline (RCS) terms were applied, and nonlinear model was adjusted. Then, mediation model analysis was conducted to investigate whether the association between fatigue, sleep quality, and ASM resistance was affected by a mediator, and we here analyzed the mediating effect of depression severity. Ordinary least squares regression path analyses were conducted to estimate total, direct, and indirect effects in a simple singular mediation model. The R version 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria) was used for all statistical analyses and data visualization.

Results

A total of 189 patients (59 ASM-resistant cases and 130 ASM-responsive controls) were included in the final analysis. Demographic and clinical characteristics for study cohort, as well as results from the bivariate analyses are shown in Table 1. Symptomatic epilepsy and higher EEG SW burden were more frequent among ASM-resistant cases than among controls. ASM-resistant cases were more likely to have fatigue, poor sleep quality, and depression at baseline compared to controls. ASM-resistant cases tended to report family history (p = 0.096). Additionally, the median number of ASM ever used in ASM-resistant group was 3. This was significantly more than median number of ASM ever used in ASM-responsive group which was only 1 (p < 0.001). Patients with fatigue were more likely to take more numbers of ASMs than those without fatigue (p = 0.028). Similarly, patients with poor sleep quality were more likely to take more numbers of ASMs than those with good sleep quality (p < 0.001).

Table 1.

Demographics and clinical characteristics of ASM-resistant cases and ASM-responsive controls.

Characteristic	ASM-responsive controls	ASM-resistant cases	p
Total	130	59
Age (years)	32 (23–41)	32 (23–39)	0.863
Sex
Male	70 (53.8)	30 (50.8)	0.823
Female	60 (46.2)	29 (49.2)
Education level
University and above	65 (50.0)	27 (45.8)	0.344
Middle school	59 (45.4)	26 (44.1)
Primary school and below	6 (4.6)	6 (10.2)
Epilepsy duration (months)	3 (1, 7)	4 (1, 8)	0.827
Epilepsy type
Focal	96 (73.8)	50 (84.7)	0.233
Generalized	28 (21.5)	8 (13.6)
Unknown	6 (4.6)	1 (1.7)
Family history
Yes	10 (7.7)	10 (16.9)	0.096
No	120 (92.3)	49 (83.1)
>50% nocturnal seizures
Yes	61 (46.9)	25 (42.4)	0.671
No	69 (53.1)	34 (57.6)
>5 seizures pretreatment
Yes	58 (44.6)	26 (44.1)	0.999
No	72 (55.4)	33 (55.9)
Symptomatic epilepsy
Yes	39 (30.0)	28 (47.5)	0.031
No	91 (70.0)	31 (52.5)
EEG SW burden
None or rare	26 (20.0)	3 (5.1)	0.023
Occasional	35 (26.9)	18 (30.5)
Frequent	45 (34.6)	19 (32.2)
Abundant	24 (18.5)	19 (32.2)
Number of ASMs use	1 (1–2)	3 (3–4)	<0.001
Fatigue
Yes	22 (16.9)	23 (39.0)	0.002
No	108 (83.1)	36 (61.0)
FSS score	1.89 (1.33–3.11)	3.33 (2.22–4.39)	<0.001
Sleep quality
Poor	48 (36.9)	36 (61.0)	0.003
Good	82 (63.1)	23 (39.0)
PSQI score	4 (2–7)	6 (4–9)	0.005
Depression
Yes	24 (18.5)	23 (39.0)	0.004
No	106 (81.5)	36 (61.0)
NDDI-E score	7 (6, 10)	10 (6–12)	0.004

ASM, antiseizure medication; FSS, Fatigue Severity Scale; NDDI-E, Neurological Disorder Depression Inventory for Epilepsy; PSQI, Pittsburgh Sleep Quality Index; SW, spike-wave discharges.

In Cox proportional hazard regression model, baseline fatigue (HR, 1.98; 95% CI, 1.094–3.583, p = 0.024; Table 2) and FSS score (HR, 1.352; 95% CI, 1.139–1.604, p < 0.001) were associated with an increased hazard of ASM resistance in PWNDE after full adjustments. Compared to patients without fatigue, patients with fatigue had nearly a 2-fold increased hazard for ASM resistance in adjusted model. Each 1 point increase in the mean FSS score was associated with a 35.2% risk increase in ASM resistance. Baseline sleep quality (HR, 2.193; 95% CI, 1.29–3.729, p = 0.004) and PSQI score (HR, 1.083; 95% CI, 1.002–1.172, p < 0.001) were also associated with an increased hazard of ASM resistance. Compared to patients with good sleep quality, patients with poor sleep quality had a 2.193-fold increased hazard for ASM resistance. Each 1 point increase in the PSQI score was associated with a 8.3% risk increase in ASM resistance.

Table 2.

Association of fatigue and sleep quality with ASM resistance.

Variable	Nonadjusted model			Adjusted model^a
Variable	HR	95% CI	p	HR	95% CI	p
Fatigue
Yes	2.363	1.4–3.991	0.001	1.98	1.094–3.583	0.024
No	Ref			Ref
FSS score	1.417	1.216–1.65	<0.001	1.352	1.139–1.604	<0.001
Sleep quality
Poor	2.259	1.338–3.816	0.002	2.193	1.29–3.729	0.004
Good	Ref			Ref
PSQI score	1.105	1.028–1.188	0.007	1.083	1.002–1.172	0.045

Adjusted for age, sex, family history, symptomatic epilepsy, EEG SW burden, and depression.

ASM, antiseizure medication; CI, confidence interval; FSS, Fatigue Severity Scale; HR, hazard ratios; PSQI, Pittsburgh Sleep Quality Index; SW, spike-wave discharges.

We employed a Cox proportional hazards regression model with RCSs and smooth curve fitting (penalized spline method) to further explore the potential nonlinear effects on the association. Interestingly, the adjusted smoothed plots displayed a nonlinear association between FSS score and the hazard of ASM resistance (P for nonlinear = 0.012; Figure 1(a)). However, positive linear association was demonstrated between PSQI score and the hazard of ASM resistance (P for nonlinear = 0.555; Figure 1(b)), and increment in PSQI score was associated with a stepwise rise of ASM resistance risk.

Figure 1.

Association of FSS (a) and PSQI (b) scores with ASM resistance using a RCS regression model.

The above findings identified baseline fatigue and poor sleep quality as predictors of ASM resistance as well as modulators for depression symptoms. Thus, we investigated whether fatigue and sleep quality contributed to ASM resistance by modulating depression severity. We found that depression severity partly mediated the effect of fatigue on ASM resistance, with mediated proportions of 18.5% for the fatigue (Figure 2(a)). Depression severity also partly mediated the effect of sleep quality on ASM resistance, with mediated proportions of 23.7% for the sleep quality (Figure 2(b)).

Figure 2.

Mediating role of depression severity in association of fatigue (a) and sleep quality (b) with ASM resistance.

Discussion

This is the first study to follow a representative cohort of PWNDE to assess whether baseline fatigue and sleep quality are associated with risk of ASM resistance, and whether the association is mediated by depression severity. We found that baseline fatigue and poor sleep quality were associated with an increased risk of ASM resistance. Furthermore, the association between fatigue, sleep quality, and ASM resistance were partly mediated by depression severity. The present study offers novel insights into the relationship between fatigue, sleep quality, depression symptoms, and risk of ASM resistance. These findings emphasize that patients with ASM-resistant epilepsy are more likely to have fatigue, depression, and poor sleep quality at baseline and this may be unrelated to ASM intake.

Fatigue represents a common complaint in PWE mostly due to high prevalence of comorbid sleep disorders and ASM-related adverse events.^8,35 A systematic review found that the overall frequency of fatigue was 47.1% in PWE that may be closely correlated with depression.⁷ In total, 23.8% patients had fatigue in our cohort that was much lower than the reported fatigue incidence by other researchers. It may be due to that fatigue was identified as dose-related side effect of some ASMs,³⁶ whereas the participants of this study were not treated with ASM at baseline. Prior literature have relative consistent results on the relationship between fatigue, seizure risk, and severity.^10,37 A cross-sectional survey found a significant association between fatigue and seizure severity.³⁷ Ferlisi et al. reported fatigue as the most frequently seizure precipitants, and patients with psychological comorbidities had a greater percentage of fatigue and further seizures.⁹ Similarly, another study found that fatigue was one of the most common triggering factors of further seizures in PWE.¹⁰ Additionally, fatigue was more severe in epilepsy patients than in healthy controls without epilepsy, especially when seizures were not controlled.⁸ Thus, the persistence of fatigue may increase the risk of further uncontrolled seizure and ASM resistance. We also found that patients with fatigue or poor sleep quality were more likely to take more numbers of ASMs, which was in line with a previous study showing that the presence of insomnia and poor quality of life were higher in patients who receive polytherapy.³⁸ However, prior studies employed cross-sectional design, and definitive conclusions about causality cannot be made. Here, in a cohort of PWNDE, we found that patients with ASM-resistant epilepsy are more likely to have fatigue, depression, and poor sleep quality at baseline and this may be unrelated to ASM intake. There are some biologically plausible explanations for our findings. One hypothesis relates to stress, which has long been recognized as predisposing and perpetuating factors in chronic fatigue.³⁹ Chronic stress has been shown to determine changes in brain structure and function, and activate the hypothalamic-pituitary-adrennal (HPA) axis.^40,41 These changes may increase in epileptiform activity and aggravate seizures.¹⁷ Another mechanism may be due to the high likelihood of coexisting depression with fatigue.^7,8 Depression may aggravate seizures or epileptogenesis, with studies showing that neuropsychiatric symptomatology often predate the onset of the seizures and may act as a predictor^18,42 and work in animal models showing that enhanced depressive-like behavior increase the vulnerability to epileptogenesis.⁴³

Sleep and epilepsy are mutually related in a complex, bidirectional manner.^12,13 Sleep disturbances are common in PWE that may contribute to poor sleep quality and increased seizure activity.^44,45 Our findings are partly consistent with prior cross-sectional studies that indicate poor sleep quality was associated with high frequency of seizures in PWE.^15,46 Our analysis expands on these studies by examining the association between baseline sleep quality and ASM resistance in a large cohort of PWNDE. This association was a positive linear shaped, and increment in PSQI score was associated with a stepwise rise of ASM resistance risk. The literature of the neurobiological basis of the interactions between sleep and epilepsy provided clear evidence. First, sleep appears to play an important role in synaptic plasticity that could be involved in epileptogenesis.^47,48 Second, sleep and epilepsy share the same thalamus and thalamocortical pathways.^49,50 Third, most of neurotransmitters and neuromodulators such as adenosine, melatonin, serotonin, and histamine are found to regulate the sleep–wake behavior and also considered to have antiepilepsy effects.⁵⁰

Our results replicated prior literature demonstrating the importance of depression symptoms in influencing ASM responsiveness and seizure outcome in PWE.^17,18,42 The underlying pathological mechanism of the association between fatigue, sleep quality, and ASM responsiveness was not fully understood, and depression symptoms may play a key role. Pathological cascades arising from depression are suggested to lead to both fatigue, poor sleep quality, and cause ASM resistance.^42,51,52 Mechanisms behind depression including neuroinflammation, oxidative stress, neurotransmitter, and hormone levels may link the pathophysiology between fatigue, sleep quality, and ASM resistance.^17,51,53 By conducting mediation analysis, we confirmed that the association of fatigue and sleep quality with ASM resistance are partially mediated by depression severity. Although the mediation effects should be considered with caution since they can hardly represent the causality of the relationship, these findings provide a probable view of the potential mechanism on the way fatigue and sleep quality affect ASM responsiveness.

Despite its contributions, this study has some limitations. First, fatigue, sleep quality, and depression symptoms were only assessed at baseline; and trajectories of these comorbidities during follow-up were not identified, which may be related with ASM resistance. Some ASMs might worsen the comorbid conditions.^2,54 However, we had no access to more detailed information on ASM treatment, and the effects of ASMs on these comorbidities could not be evaluated. Small sample size may limit the reliability of results when exploring the potential nonlinear relationship. Furthermore, we relied on the NDDI-E score >13 to determine depression, which while having a high sensitivity (0.81) and specificity (0.90).²⁸ NDDI-E is a screening tool for the “presence” of depression in epilepsy but is not designed to assess “severity” of depression. While we found the mediating effect of depression severity as a result, it should be considered as the “expansive” use of NDDI-E. Second, follow-up information on seizure outcome and medication adherence was collected based on self-report. Studies found that seizures are under-reported if they are subtle, as the patient may be less aware of them.⁵⁵ The incidence of ASM-resistant epilepsy may be underestimated due to the relatively short follow-up period. Third, the study’s sample size and single-center setting may affect the generalizability of the findings to broader populations. Additionally, it was not possible to collect all predictors of ASM resistance because of insufficient funding.

In conclusion, baseline fatigue and poor sleep quality were associated with an increased risk of ASM resistance. The association between fatigue, sleep quality, and ASM resistance were partly mediated by depression severity. These findings emphasize that patients with ASM-resistant epilepsy are more likely to have fatigue, depression, and poor sleep quality at baseline, and this may be unrelated to ASM intake. There remains a need for well-designed and statistically powered studies to determine whether early interventions for these comorbidities reduce the risk of ASM resistance in PWNDE.

Supplemental Material

sj-docx-1-tan-10.1177_17562864251325338 – Supplemental material for Fatigue, sleep quality, depression symptoms, and antiseizure medication resistance in patients with newly diagnosed epilepsy

Supplemental material, sj-docx-1-tan-10.1177_17562864251325338 for Fatigue, sleep quality, depression symptoms, and antiseizure medication resistance in patients with newly diagnosed epilepsy by Rui Zhong, Teng Zhao, Nan Li, Jing Li, Guangjian Li, Xinyue Zhang and Weihong Lin in Therapeutic Advances in Neurological Disorders

Footnotes

Acknowledgements

The authors thank all participants of the present study as well as all members of staff of the cohort study for their role in data collection.

Author’s note

We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

Declarations

ORCID iDs

Xinyue Zhang

Weihong Lin

Supplemental material

Supplemental material for this article is available online.

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