
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12531-5
10.1016/j.heliyon.2024.e36500
e36500
Research Article
Duration of N1 sleep is a factor for excessive daytime sleepiness in epilepsy patients with interictal epileptiform discharges: A polysomnographic study
Wu Sangru a1
Wang Sihang a1
Wu Meina a
Lin Fang a
Ji Xiaolin a
Yan Jinzhu yanjinzhu@fjmu.edu.cn
a⁎
a Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
⁎ Corresponding author. Department of Neurology, Fujian Provincial Governmental Hospital, 67 Gupin Road, Gulou District, Fuzhou, China. yanjinzhu@fjmu.edu.cn
1 Drs Sangru Wu, and Sihang Wang contributed equally to this work and share co-first authorship.

16 8 2024
30 8 2024
16 8 2024
10 16 e365008 4 2024
24 6 2024
16 8 2024
© 2024 The Authors. Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Purpose

This study aimed to identify the occurrence of excessive daytime sleepiness (EDS) in epilepsy patients with interictal epileptiform discharges and to explore the impact of interictal sleep architecture and sleep-related events on EDS.

Methods

This study included 101 epilepsy patients with interictal epileptiform discharges (IED) and 100 control patients who underwent simultaneous polysomnography and video ambulatory electroencephalography for >7 h throughout a single night. Multiple sleep latency tests were used to assess EDS. Comorbid EDS was present in 25 and 11 patients in the IED epilepsy and control groups, respectively. In addition, univariate and multivariate logistic regression analyses were performed to explore the factors influencing EDS.

Results

The epilepsy group had a higher prevalence of comorbid EDS and shorter R sleep duration. Univariate logistic regression analysis indicated that an increased risk of EDS may be associated with prolonged N1 sleep duration, higher arousal index, lower mean saturation (mSaO2), higher oxygen desaturation index (ODI), and duration of wake after sleep onset (WASO). Multivariate logistic regression analysis revealed that N1 sleep duration was significantly correlated with EDS.

Conclusion

In epilepsy patients with IED, the arousal index, mSaO2, ODI, and duration of WASO were weakly correlated with EDS, and the duration of N1 sleep demonstrated a significant positive correlation with EDS, which requires further research.

Keywords

Excessive daytime sleepiness
Multiple sleep latency tests
Interictal epileptiform discharges
N1 sleep duration
Abbreviations

EDS excessive daytime sleepiness

IED interictal epileptiform discharges

MSLT multiple sleep latency tests

mSaO2 mean saturation

ODI oxygen desaturation index

NREM non-rapid eye movement

REM rapid eye movement

OSA obstructive sleep apnoea

PSG polysomnography

ASM antiseizure medication

BMI body mass index

TST total sleep time

AHI apnoea-hypopnea index

WASO wake after sleep onset

PLMI periodic limb movement index

PLMD period limb movement disorder

RBD REM sleep behaviour disorder

IQR interquartile range

EPV event per variable
==== Body
pmc1 Introduction

The relationship between sleep and epilepsy is complex, and various sleep stages have different effects on epilepsy. Seizures and epileptiform discharges may be promoted during non-rapid eye movement (NREM) sleep, possibly because of the synchronisation of neurons between the brainstem, thalamus, and cortex. In contrast, seizures and epileptiform discharges may be inhibited during rapid eye movement (REM) sleep [1]. Excessive daytime sleepiness (EDS) is primarily caused by frequent awakenings and fragmented sleep resulting from electroencephalographic (EEG) changes. Comorbid sleep disturbances are prevalent among patients with epilepsy. Compared with healthy individuals, the risk of EDS, insomnia, and obstructive sleep apnoea (OSA) is 2–3 times higher among patients with epilepsy, which substantially reduces their quality of life [2]. In addition to affecting social and occupational activities in the general population, hypersomnia and general sleep disturbance may exacerbate the condition of patients with epilepsy by accelerating or facilitating key events that complicate and aggravate cognitive and behavioral impairments [3]. Moreover, sleepiness is associated with an increased risk of accidents and imposes a considerable health and economic burden. Therefore, it is essential to identify the factors that influence sleepiness, particularly in patients with epilepsy. The aetiology of EDS in epilepsy is multifaceted, involving psychological distress, epilepsy-related factors, and concurrent sleep disruptions, often associated with undiagnosed sleep disorders [4]. EDS can be assessed using subjective or objective methods. From a subjective point of view, the Epworth Sleepiness Scale (ESS) is the most commonly used tool in sleep research and has been extensively used in most existing studies. However, the most objective and reliable diagnostic criterion for EDS is the multiple sleep latency test (MSLT) [5], although it requires considerable effort and time to complete. Therefore, it is critical to identify specific indicators in the nocturnal polysomnography (PSG) sleep architecture or sleep-related events that reflect the results of the MSLT. Although the relationship between epilepsy and EDS has been previously reported, only few studies have targeted individuals with interictal epileptiform discharges (IED). Excluding the confounding effect of seizures on EDS improves the reliability and robustness. Our study aimed to address these questions by analyzing the sleep structure characteristics of patients with IED and EDS. The factors influencing EDS were investigated using 16-channel video EEG and PSG to understand the distribution of EDS in patients with IED and to provide evidence for the early identification of high-risk groups and complications of EDS in patients with IED epilepsy.

2 Methods

2.1 Research design and objectives

This single-centre retrospective case-control study included a control group and an epilepsy group comprising patients with IED who had undergone 16-channel video EEG, including PSG between July 1, 2018 and October 1, 2022 at the Department of Neurology and Sleep Medicine Centre of Fujian Provincial Governmental Hospital. The study protocol was approved by the Institutional Ethics Committee. Patients who met the following criteria were included in the case group: age ≥16 years, with written consent from themselves (and their guardians if necessary) to be included in the study; a diagnosis of epilepsy according to the International League Against Epilepsy 2017 criteria [6]; nighttime sleep monitoring time >7 h; and a diagnosis of IED [7]. The exclusion criteria were as follows: patients with a known history of alcoholism, consumption of coffee and other beverages affecting sleep, intake of other medications affecting sleep (except antiepileptic drugs) in the past 2 weeks; mental disorders, disorders of the circulatory system, or other diseases that affect sleep; those who had epileptic seizures or did not have epileptiform discharges during the monitoring period; those with drug-resistant epilepsy or epilepsy syndrome; those who could not cooperate with the examination; those with incomplete PSG monitoring data; and those lacking MSLT data. The control group consisted of volunteers who visited the Sleep Medicine Centre or the Department of Neurology of Fujian Provincial Governmental Hospital during the same period. The participants were randomly recruited and had no relationship to the epilepsy group. Patients aged ≥16 years who provided written consent from themselves (and their guardians if necessary) to be included in the study and underwent nighttime sleep monitoring for >7 h were included in the control group. Patients with a history of alcoholism, consumption of coffee and other caffeinated drinks, intake of drugs that affect sleep in the past 2 weeks; those with mental disorders, disorders of the circulatory system, or other diseases that affect sleep; those who could not cooperate with the examination; those with incomplete PSG data; and those lacking MSLT data were excluded. The demographic data of each patient, including age, sex, body mass index (BMI), sleep structure, sleep progression, sleep-related events, type of seizure, site of epileptic discharge, number of medications taken, and medical history, were recorded.

2.2 PSG parameters

To minimise undesired interference from the surroundings, each patient underwent at least 7 h of PSG (Alice 6 LDxS; Philips) at the sleep medicine centre throughout the night. The monitoring items included EEG (16 leads), electrooculogram (2 leads), electromyogram (EMG) from the submental and peroneal anterior muscles, thoracoabdominal respiration, body position change, leg movement, blood oxygen saturation from the index finger, snoring, oral-nasal airflow, and electrocardiogram. Infrared video was also used to record any seizures or abnormal sleeping behaviour that the patient may have experienced. The outcomes of the PSG test included total sleep time, sleep latency duration, duration of wake after sleep onset (WASO), sleep efficiency, mean saturation (mSaO2), oxygen desaturation index (ODI), arousal index, and apnoea-hypopnea index (AHI), in accordance with the American Academy of Sleep Medicine 2.3 scoring standard. The ODI was defined as the number of desaturations ≥3 % per hour of sleep [8]. Based on the AHI, obstructive sleep apnoea (OSA) was graded as follows: Grade 0: AHI <5 events/h; Grade 1: 5 events/h ≤ AHI <15 events/h; Grade 2: AHI ≥15 events/h [9]. A mean sleep latency of less than 8 min indicated EDS, which was determined using MSLT [10].

2.3 MSLT

The MSLT included five nap experiments, which started 1.5 h after waking up in the morning and were performed separately at 09:00, 11:00, 13:00, 15:00, and 17:00. The setting where the patient lies down should be calm, dark, and at a pleasant temperature. Naps begin with the lights out, signalling the start of sleep. The nap sessions are standardized to 20 min initially, with an extension of 15 min if sleep occurs. Sleep latency duration was defined as the duration from the lights off to the onset of sleep.

2.4 Statistical methods

Continuous variables with a normal distribution are expressed as the mean ± standard deviation (x ± SD), and those without a normal distribution are expressed as the median M (interquartile range P25–P75). Categorical variables are presented as frequencies and percentages. The analysis of differences between groups was performed as follows: t-test was used for normally-distributed continuous variables; Wilcoxon rank-sum test was applied for variables with non-normal distribution or ordered categorical variables; chi-squared test, continuity correction chi-squared test, Pearson chi-squared test, or Fisher's exact test were used for comparison of categorical variables between groups. The odds ratios (OR) and 95 % confidence intervals (CI) of the factors influencing EDS in patients with epilepsy and IED were calculated using univariate logistic regression. The variables included in the multivariate logistic regression were based on a combination of univariate logistic regression analysis and the findings of previous studies. All statistical analyses were performed using SPSS software for Windows (version 25.0, IBM Corp., Armonk, NY, USA), and statistical significance was set at P < 0.05 in two-tailed statistical tests.

3 Results

Between July 1, 2018 and October 1, 2022, 119 adult patients with epilepsy who had undergone synchronous video PSG and long-term video EEG at Fujian Provincial Governmental Hospital were enrolled in this study. Following the exclusion of nine patients without experimental MSLT data, five with epileptic seizures during the monitoring period, and four with no detectable epileptiform discharges (Fig. 1), 101 patients were included in the final analyses. Thirty patients received monotherapies, including valproic acid (n = 10), phenytoin (n = 1), carbamazepine (n = 5), oxcarbazepine (n = 12), and levetiracetam (n = 2). Ten patients were treated with a combination of two anti-seizure medications (ASMs), which included oxcarbazepine + clonazepam (n = 2), valproic acid + levetiracetam (n = 1), valproic acid + gabapentin (n = 1), valproic acid + lamotrigine (n = 2), valproic acid + oxcarbazepine (n = 2), topiramate + clonazepam (n = 1), and topiramate + lamotrigine (n = 1). Three patients received three ASMs, including topiramate + oxcarbazepine + levetiracetam (n = 1), lamotrigine + valproic acid + clonazepam (n = 1), and oxcarbazepine + topiramate + clonazepam (n = 1).Fig. 1 Flow chart of patient selection process Abbreviations: EDS, excessive daytime sleepiness; IED, interictal epileptiform discharges; MSLT, multiple sleep latency test.

Fig. 1

3.1 Participants’ characteristics

Table 1 summarises the demographic data of patients in the IED epilepsy and control groups. The differences in the average age 57.0 vs. 62.5 (IQR, 36.0–74.0 years vs. 49.0–71.8 years, P = 0.347), BMI 22.60 vs. 22.9 (IQR, 20.60–24.80 kg/m2 vs. 20.5–25.3 kg/m2, P = 0.873), and proportion of men 58 vs. 44 men (57.4 % vs. 44.0 %, P = 0.057) were not statistically significant between the epilepsy and control groups. Compared with the control group, the proportion of patients with hypertension in the epilepsy group was lower (20 [19.8 %] vs. 36 [36.0 %], P = 0.01) (Table 1).Table 1 Comparison of demographic data between the epilepsy and control groups.

Table 1	Epilepsy group (n = 101)	Control group (n = 100)	P-value	
Age, M (IQR)	57.0 (36.0–74.0)	62.5 (49.0–71.8)	0.347a	
BMI, M (IQR)	22.60 (20.60–24.80)	22.9 (20.5–25.3)	0.873a	
Sex			0.057b	
 Male (%)	58 (57.4)	44 (44.0)		
 Female (%)	43 (42.6)	56 (56.0)		
Hypertension (%)	20 (19.8)	36 (36.0)	0.01cb	
Diabetes (%)	11 (10.9)	12 (12.0)	0.805b	
Cerebrovascular disease (%)	19 (18.8)	14 (14.0)	0.357b	
Parkinson's disease or cognitive impairment (%)	3 (3.0)	4 (4.0)	0.989b	
Abbreviations: BMI, Body mass index; IQR, interquartile range.

a Wilcoxon rank-sum test.

b Chi-square test.

c P < 0.05.

3.2 Comparison of sleep architecture and sleep-related events between the epilepsy and control groups

Table 2 summarises the comparison of PSG results between the IED epilepsy and control groups. Compared with the controls, patients in the epilepsy group had a higher incidence of EDS as a comorbid condition (25 [24.8 %] vs. 11 [11.0 %], P = 0.01) and shorter R sleep duration (P = 0.019).Table 2 Comparison of polysomnography results between epilepsy and control groups.

Table 2	Epilepsy group (n = 101)	Control group (n = 100)	P-value	
Sleep latency (min), M (IQR)	12.0 (5.5–18.0)	11.5 (5.6–23.5)	0.610a	
TST (min), M (IQR)	393.0 (347.8–469.8)	409.8 (348.8–454.4)	0.772a	
R sleep duration (min), M (IQR)	55.0 (36.8–78.5)	71.0 (53.1–86.6)	0.019ca	
N1 sleep duration (min), M (IQR)	56.0 (42.0–81.8)	52.0 (35.1–79.0)	0.322a	
N2 sleep duration (min), M (IQR)	233.0 (187.0–285.0)	243.8 (206.6–284.9)	0.345a	
N3 sleep duration (min), M (IQR)	24.0 (1.0–56.5)	24.8 (7.5–58.0)	0.695a	
Arousal index, M (IQR)	11.9 (7.5–15.3)	10.5 (6.6–13.3)	0.231a	
AHI, M (IQR)	10.8 (4.4–28.2)	10.1 (4.2–24.2)	0.464a	
mSaO2, M (IQR)	94.0 (93.0–96.0)	94.0 (93.3–95.0)	0.558a	
ODI, M (IQR)	11.0 (4.9–32.4)	10.0 (4.1–24.4)	0.252a	
Minimum blood oxygen saturation, M (IQR)	86.0 (80.0–90.5)	87.0 (83.0–90.0)	0.212a	
WASO (min), M (IQR)	95.0 (55.3–146.3)	98.0 (53.3–142.3)	0.726a	
Sleep efficiency, M (IQR)	81.4 (70.7–90.0)	80.9 (72.3–89.2)	0.675a	
PLMI, M (IQR)	2.8 (0–15.4)	6.6 (1.0–19.8)	0.072a	
OSA (%)			0.935b	
 0	27 (26.7)	28 (28.0)		
 1	30 (29.7)	31 (31.0)		
 2	44 (43.6)	41 (41.0)		
PLMD (%)	26 (25.8)	31 (31.0)	0.408b	
RBD (%)	8 (7.9)	8 (8.0)	0.983b	
EDS (%)	25 (24.8)	11 (11.0)	0.010cb	
Abbreviations: TST, total sleep time; AHI, apnoea-hypopnoea index; mSaO2, mean saturation; ODI, oxygen desaturation index; WASO, wake after sleep onset; PLMI, periodic limb movement index; OSA, obstructive sleep apnoea; PLMD, periodic limb movement disorder; RBD, REM sleep behaviour disorder; EDS, excessive daytime sleepiness; IQR, Interquartile range.

a Wilcoxon rank-sum test.

b Chi-square test.

c P <0.05.

3.3 Comparison of demographic data and PSG results between EDS and no-EDS groups and the impact of demographic data and PSG results on the incidence of EDS within patients in the epilepsy group

The demographic data and PSG results between the EDS and no-EDS subgroups in the epilepsy group were compared (Table 3). Among the 25 patients with epilepsy and EDS included in the study, 14 were men (56.0 %) and 11 were women (44.0 %). The mean age of the patients in the EDS group was 65.0 (49.0–79.5) years, and the mean course of disease was 2.0 (0.4–9.0) years. Regarding the distribution of epileptic discharge, seven patients (28.0 %) had epileptic discharges originating predominantly from the left hemisphere of the brain. Similarly, seven patients (28.0 %) had epileptic discharges predominantly from the right hemisphere. Bilateral synchronous discharge and bilateral alternating discharge was reported in five (20.0 %) and six (24.0 %) patients, respectively. Most patients (n = 18, 72.0 %) were diagnosed with focal epilepsy, and seven (18.0 %) had generalized epilepsy. Among the 11 patients treated with ASMs, eight received one ASM (carbamazepine, n = 2; oxcarbazepine, n = 2; and valproic acid, n = 4), one received a combination of two ASMs (valproic acid + gabapentin), and two received a combination of three ASMs (lamotrigine + valproic acid + clonazepam and oxcarbazepine + topiramate + clonazepam). Of the 76 patients in the no-EDS group, 44 were men (57.9 %) and 32 were women (42.1 %). The mean age of the patients in the no-EDS group was 55.0 (34.3–69.8) years, and the mean course of disease was 1.0 (0.5–4.75) years. Epileptic discharge from the left and right sides was reported in 24 (31.6 %) and 25, (32.9 %) patients, respectively. Bilateral synchronous discharge and bilateral alternating discharge were observed in 10 (13.2 %) and 17 (22.4 %) patients, respectively. Most patients (n = 50, 65.8 %) were diagnosed with focal epilepsy, and 26 (34.2 %) had generalized epilepsy. ASM use was reported in 36 patients. Among them, 20 patients received monotherapy with one of the following ASMs: levetiracetam (n = 2), oxcarbazepine (n = 10), carbamazepine (n = 3), valproic acid (n = 6), and phenytoin (n = 1); nine patients received combination therapy with two ASMs, including levetiracetam + valproic acid (n = 1), oxcarbazepine + valproic acid (n = 2), oxcarbazepine + clonazepam (n = 2), topiramate + lamotrigine (n = 1), topiramate + clonazepam (n = 1), and lamotrigine + valproic acid (n = 2); and one patient received combination therapy with three ASMs (levetiracetam + oxcarbazepine + topiramate).Table 3 Demographic data and PSG results between the EDS and no-EDS groups and univariate logistic regression analysis on the incidence of EDS within patients in the epilepsy group.

Table 3			EDS	
EDS (n = 25)	No-EDS (n = 76)	B	SD	OR	95 % CI	P-value	
Age, years	65.0 (49.0–79.5)	55.0 (34.3–69.8)	0.017	0.011	1.018	0.996–1.039	0.103	
BMI, kg/m2	23.1 (20.8–24.7)	22.4 (20.5–24.8)	0.034	0.070	1.035	0.902–1.187	0.628	
Sex	
 Male	14 (56.0)	44 (57.9)						
 Female	11 (44.0)	32 (42.1)	−0.077	0.465	0.926	0.372–2.303	0.868	
Hypertension	4 (16.0)	16 (21.1)	0.336	0.614	1.400	0.420–4.663	0.584	
Diabetes	4 (16.0)	7 (9.2)	0.630	0.675	0.533	0.142–1.998	0.350	
Cerebrovascular disease	7 (28.0)	12 (15.8)	0.730	0.545	0.482	0.166–1.404	0.181	
Parkinson's disease or cognitive impairment	1 (4.0)	2 (2.6)	0.433	1.247	0.649	0.056–7.473	0.729	
Epileptic discharge distribution	
 Left side	7 (28.0)	24 (31.6)						
 Right side	7 (28.0)	25 (32.9)	−0.191	0.640	0.826	0.236–2.899	0.766	
 Bilateral synchronous discharge	5 (20.0)	10 (13.2)	−0.232	0.639	0.793	0.227–2.776	0.717	
 Bilateral alternating discharge	6 (24.0)	17 (22.4)	−0.348	0.725	1.417	0.342–5.866	0.631	
Epilepsy types	
 Generalized	7 (28.0)	26 (34.2)						
 Focal	18 (72.0)	50 (65.8)	−0.291	0.507	0.748	0.277–2.019	0.566	
Course of disease	2.0 (0.4–9.0)	1.0 (0.5–4.75)	−0.001	0.031	1.001	0.942–1.063	0.985	
IED index	0.6 (0.3–2.1)	0.5 (0.3–1.2)	0.150	0.172	1.162	0.830–1.626	0.382	
Receiving ASM	11 (44.0)	32 (42.1)	−0.077	0.465	0.926	0.372–2.303	0.868	
Type of ASM therapy	
 0	14 (56.0)	44 (57.9)						
 1 (Monotherapy)	8 (32.0)	22 (28.9)	−1.838	1.263	0.159	0.013–1.890	0.145	
 2 (Combination of two ASMs)	1 (4.0)	9 (11.8)	−1.705	1.292	0.182	0.014–2.290	0.187	
 3 (Combination of three ASMs)	2 (8.0)	1 (1.3)	−2.890	1.616	0.056	0.002–1.319	0.074	
Sleep latency (min)	9.50 (5.0–17.0)	12.3 (6.0–19.9)	−0.001	0.012	0.999	0.976–1.023	0.927	
TST (min)	405.5 (355.5–481.8)	391.0 (342.4–454.6)	0.002	0.002	1.002	0.997–1.006	0.437	
R sleep duration (min)	44.5 (16.5–63.5)	61.3 (38.5–82.6)	−0.014	0.008	0.986	0.971–1.000	0.056	
N1 sleep duration (min)	70.5 (49.8–129.0)	53.5 (38.8–75.5)	0.019	0.006	1.019	1.007–1.031	0.002a	
N2 sleep duration (min)	237.0 (188.5–328.3)	232.8 (186.5–277.6)	0.001	0.003	1.001	0.996–1.007	0.719	
N3 sleep duration (min)	16.5 (0.3–60.0)	27.5 (1.1–56.8)	−0.003	0.006	0.997	0.985–1.009	0.617	
Arousal index	13.4 (9.1–17.4)	10.8 (7.3–14.4)	0.047	0.022	1.048	1.004–1.094	0.033a	
AHI	18.5 (7.6–49.6)	10.0 (3.9–24.1)	0.019	0.010	1.020	0.999–1.040	0.058	
mSaO2 (%)	94.0 (92.0–95.0)	95.0 (93.3–96.0)	−0.260	0.112	0.771	0.620–0.960	0.020a	
ODI	24.1 (6.5–55.5)	9.9 (4.5–24.8)	0.026	0.010	1.026	1.006–1.047	0.011a	
Minimum blood oxygen saturation (%)	81.0 (78.0–86.5)	87.0 (81.3–91.0)	−0.021	0.020	0.980	0.942–1.019	0.303	
WASO (min)	112.0 (55.3–230.8)	84.3 (54.9–135.1)	0.007	0.003	1.007	1.001–1.013	0.014a	
Sleep efficiency	77.6 (63.4–89.7)	81.9 (71.9–90.3)	−0.026	0.016	0.975	0.944–1.006	0.114	
PLMI	4.6 (0–18.3)	2.45 (0–15.0)	0.002	0.011	1.002	0.980–1.025	0.865	
OSA (%)	
 0	3 (12.0)	24 (31.6)						
 1	8 (32.0)	22 (28.9)	−1.317	0.693	0.268	0.069–1.041	0.057	
 2	14 (56.0)	30 (39.5)	−0.249	0.525	0.779	0.279–2.179	0.634	
PLMD (%)	7 (28.0)	19 (25.0)	−0.154	0.518	0.857	0.310–2.367	0.766	
RBD (%)	3 (12.0)	5 (6.6)	−0.661	0.770	0.516	0.114–2.336	0.391	
Abbreviations: BMI, Body mass index; IED, interictal epileptiform discharge; TST, total sleep time; AHI, apnoea-hypopnoea index; mSaO2, mean saturation; ODI, oxygen desaturation index; WASO, wake after sleep onset; PLMI, periodic limb movement index; OSA, obstructive sleep apnoea; PLMD, period limb movement disorder; RBD, REM sleep behaviour disorder; EDS, excessive daytime sleepiness; ASM, anti-seizure medication.

a P < 0.05.

The univariate logistic regression analysis demonstrated that the increased risk of EDS may be correlated with the N1 sleep duration (OR, 1.019; 95 % CI, 1.007–1.031; P = 0.002), higher arousal index (OR, 1.048; 95 % CI, 1.004–1.094; P = 0.033), lower mSaO2 (OR, 0.771; 95 % CI, 0.620–0.960; P = 0.020), higher ODI (OR, 1.026; 95 % CI, 1.006–1.047; P = 0.011), and longer duration of WASO (OR, 1.007; 95 % CI, 1.001–1.013; P = 0.014).

Impact of N1 sleep duration, arousal index, mSaO2, ODI, and OSA on the incidence of EDS within patients in the epilepsy group.

A multivariate logistic regression model was constructed (Table 4), including predictors such as the duration of N1 sleep, arousal index, mSaO2, ODI, and OSA, which indicated that the duration of N1 sleep had a statistically significant effect on EDS (OR, 1.023; 95 % CI, 1.005–1.041; P = 0.014). The variance inflation factor was used to assess variable collinearity among the predictor variables. The accuracy and stability of the models were evaluated using calibration curves and the Hosmer–Lemeshow goodness-of-fit test [3]. The results showed that VIF was less than 5 and tolerance was greater than 0.1, suggesting no significant collinearity. The P-value of the Hosmer–Lemeshow test was 0.697, indicating a high goodness of fit of the model.Table 4 Multivariable logistic regression analysis of the presence of co-occurring epilepsy and EDS in patients.

Table 4Variables	Multivariable logistic regression analysis	
B	SD	OR	95 % CI	P-value	
N1 sleep duration	0.023	0.009	1.023	1.005–1.041	0.014a	
Arousal index	−0.044	0.039	0.957	0.886–1.033	0.256	
mSaO2	−0.117	0.145	0.890	0.670–1.181	0.419	
ODI	0.022	0.021	1.022	0.981–1.065	0.299	
OSA	
 0	1					
 1	−0.036	0.972	0.965	0.144–6.488	0.971	
 2	0.792	0.784	2.208	0.475–10.268	0.312	
Abbreviations: mSaO2, mean saturation; ODI, oxygen desaturation index; OSA, obstructive sleep apnoea.

a Adjusted for arousal index, mSaO2, ODI, and OSA; *P < 0.05.

4 Discussion

Patients with epilepsy are prone to multiple sleep disorders, among which EDS is the most common, with an incidence rate of 14.5%–49.6 % [11]. In our study, EDS was reported in 24.8 % of patients with epilepsy. In addition, epileptic seizures may interfere with the nocturnal sleep structure and result in EDS [12]. Therefore, we excluded patients who experienced epileptic seizures while monitored at night to better identify the elements affecting EDS. The prevalence of EDS in healthy individuals ranges from 2.5 % to 7 % [13,14], which is lower than the 11.0 % incidence of EDS in the control group in our study. This discrepancy could be attributed to the inclusion of both inpatients and outpatients who visited the department of neurology and the sleep center. Therefore, some patients develop insomnia or other sleep disorders.

Our findings demonstrated that R sleep duration was shorter in patients with epilepsy. Klobucnikova et al. found that the reduced proportion of the R-phase in patients with epilepsy resulted in sleep fragmentation, which mainly contributed to EDS [15]. A reduction in the proportion of stage 3 sleep and stage R sleep was related to poor sleep quality and the occurrence of EDS in patients with epilepsy [16]. Although the results of our study were not statistically significant, the difference in median R sleep duration between the EDS (44.5 [16.5–63.5] min) and no-EDS group (61.3 [38.5–82.6] min) had a P value of 0.056 (borderline significance), which could be attributed to the small sample size.

The correlation between OSA and EDS remains conflicting. OSA patients often complain of sleepiness, with an incidence rate of 16%–22 % [17,18]. Regardless of whether the diagnosis of OSA is based on the results of the scale or PSG study, patients with epilepsy and OSA are more likely to experience EDS [15,19], with hypoxaemia, hypercapnia, and slight arousal playing key roles as determinants [20]. In a study that included 40 patients with epilepsy, PSG revealed that sleep-disordered breathing (P = 0.002) and REM sleep duration (P = 0.029) were significantly correlated with Epworth sleepiness scale. In addition, recurrent apnoea episodes can cause sleep fragmentation and a substantial decrease in mSaO2 [21], both of which increase the risk of EDS. Concurrent noninvasive ventilator therapy can effectively lower the risk of EDS [22]. A cross-sectional study of 874 OSA patients from tertiary care centres in China showed that AHI and mSaO2 were independent factors for severe EDS (ESS ≥17) in OSA patients [23]. A large multicentre study involving 34,684 patients by Ulander et al. also showed that AHI, ODI, and mSaO2 were associated with EDS; however, ODI was a better predictor of EDS than AHI [24]. Chen et al. showed that the ESS score gradually increased with OSA severity and that ODI was the strongest determinant of the ESS score [25]. However, some studies have suggested that OSA is only weakly associated with daytime sleepiness [26]. Nonetheless, all these studies used the ESS scale for diagnosing EDS, which has subjective limitations. Wu M et al., in their study of 101 patients with narcolepsy, found that N1%, arousal index, and periodic limb movements index were positively associated with objective EDS in the early-onset group (age at disease onset ≤15 years) [27]. Kainulainen et al. analysed the PSG and MSLT results of 362 OSA patients and found that mSaO2 had a significantly stronger negative correlation with the average sleep latency than AHI [28]. Through the investigation of the objective index in MSLT, our study further showed that ODI, mSaO2, and arousal index may be related to EDS, which is consistent with previous studies. The intermittent hypoxia that can be reflected by the ODI may result in chronic sleep fragmentation and sleep deprivation, leading to exacerbation of EDS [29]. The arousal index may lead to repeated activation of the sympathetic nervous system, causing chronic partial sleep deprivation [30], resulting in disruption of sleep continuity and sleep fragmentation [31]. In addition, our findings indicated that WASO may be related to EDS. WASO reflects the severity of repeated awakenings at night and affects sleep efficiency; however, available reports demonstrating this association are scarce. In addition, our findings showed that the severity of OSA (e.g., AHI) was not significantly associated with EDS, warranting further exploration of alternative indicators of illness severity, such as ODI and mSaO2, or incorporation of these indicators into the routine evaluation of OSA severity.

The variables included in the multivariate logistic regression were based on a combination of univariate logistic regression and findings from previous studies. Owing to the small sample size, to improve event per variable (EPV), WASO was excluded from the multivariate logistic regression model [32]. Finally, N1 sleep duration, arousal index, mSaO2, ODI, and OSA were incorporated into the multivariate logistic regression model. Our findings demonstrated a significant positive correlation between N1 sleep duration and EDS. N1 sleep is the lightest stage of sleep and begins when more than 50 % of the alpha waves are replaced with low-amplitude mixed-frequency activity, often alternating with brief episodes of awakening. N1 sleep duration is a period of transition from unsynchronised beta and gamma brain waves to more synchronised but slower alpha waves, and then to theta waves with slow-rolling eye movements [33]. Our findings indicated that the longer duration of N1 sleep at night in patients with epilepsy and IED contributes to daytime sleepiness the following day. Although prolonged N1 sleep at night is a risk factor for EDS in patients with epilepsy during the interictal phase, studies analyzing the relationship between N1 sleep duration and EDS are limited. Slonkova et al. [34] reported a significant negative correlation between hypocretin-1/orexin-A and N1 sleep duration. Consistent with this, a study specifically examining different types of central disorders of hypersomnolence in children suggested that instability in N1 sleep duration may be a biological marker of hypocretin-1/orexin-A deficiency [35]. EDS is a clinical manifestation of narcolepsy. Zhang et al. found that WASO, arousal index, and N1% of narcolepsy type 1 (NT1) increased significantly, indicating that NT1, rather than NT2, exhibited shallow and more fragmented sleep [36]. Pizza et al. found that the N1 sleep duration helped confirm clinically suspected NT1 by analysing the nocturnal sleep macrostructure and MSLT of night sleep in different types of central disorders of hypersomnolence [37]. Therefore, we speculated that the relationship between N1 sleep duration and EDS may be related to hypocretin-1/orexin-A levels. Unfortunately, owing to the invasive nature of lumbar puncture, our study lacked data on hypocretin-1/orexin-A levels. Future studies should aim to incorporate hypocretin-1 measurements to provide a more comprehensive analysis of the factors contributing to EDS.

Our study had several limitations. First, this was a single-centre study with a small sample size, and only adult patients with epilepsy receiving outpatient treatments at the sleep medication centre were included, which might have contributed to selection bias. Second, the effect of the type and dosage of ASMs on sleep patterns and sleepiness during the day was not completely eliminated. Valproic acid, oxcarbazepine, carbamazepine, and levetiracetam had no effect on EDS [38,39], whereas topiramate [40] and lamotrigine had a minimal effect on EDS [41]. In addition, clonazepam, phenytoin, and gabapentin may stimulate EDS [40,41]. However, only one patient in our study received phenytoin (no-EDS group) and gabapentin (EDS group), three patients in the no-EDS group received clonazepam, and two patients in the EDS group received clonazepam; therefore, we believe that their influence on the results of the study was negligible. In the future, we will further expand the sample size and conduct multi-center studies to further investigate the effects of different ASM on sleep. Third, the sleep monitoring in our study was limited to a single night. Repeated experiments over two or more nights could enhance the reliability of the data. However, extending the monitoring period increases the resources required, including time and financial costs, and patient cooperation can be challenging. Finally, other potential variables, such as psychiatric conditions, drug interactions, living conditions and more detailed properties of epilepsy could have influenced our findings, warranting further exploration.

5 Conclusion

In conclusion, nocturnal simultaneous 16-channel video electroencephalography, including PSG and next-day MSLT, is an objective method that can be employed in clinical practice for patients with epilepsy and comorbid sleep disorders during the interictal phase. These techniques can be used to determine the characteristics of nocturnal and daytime sleep disturbances. Moreover, the likelihood of experiencing excessive daytime drowsiness increases with an increase in the duration of light sleep (N1) at night. In the future, we can expand the sample size for further validation and try interventions to mitigate EDS.

Ethical standards

The study was approved by the Ethics Committee of Fujian Provincial Governmental Hospital (approval number: 2019J01012090) and was conducted in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its later amendments. All the participants provided written informed consent.

Data availability statement

The datasets generated and/or analysed in the current study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Sangru Wu: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation. Sihang Wang: Writing – review & editing. Meina Wu: Supervision, Investigation, Data curation. Fang Lin: Investigation, Data curation. Xiaolin Ji: Writing – review & editing, Supervision. Jinzhu Yan: Writing – review & editing, Supervision, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was supported by Fujian Provincial Special Foundation for Natural Science Innovation Project (2019J01095).
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References

1 Jain S.V. Kothare S.V. Sleep and epilepsy Semin. Pediatr. Neurol. 22 2 2015 86 92 10.1016/j.spen.2015.03.005 26072338
2 Grigg-Damberger M.M. Foldvary-Schaefer N. Primary sleep disorders in people with epilepsy Child Adolesc Psychiatr Clin N Am 24 1 2015 145 176 10.1016/j.chc.2014.09.001 25455580
3 Gammino M. Excessive daytime sleepiness and sleep disorders in a population of patients with epilepsy: a case-control study J Epilepsy Res 6 2 2016 79 86 10.14581/jer.16015 28101479
4 Giorelli A.S. Excessive daytime sleepiness and epilepsy: a systematic review Epilepsy Res Treat 2013 2013 1 9 10.1155/2013/629469
5 Fong S.Y.Y. Ho C.K.W. Wing Y.K. Comparing MSLT and ESS in the measurement of excessive daytime sleepiness in obstructive sleep apnoea syndrome J. Psychosom. Res. 58 1 2005 55 60 10.1016/j.jpsychores.2004.05.004 15771871
6 Falco-Walter J.J. Scheffer I.E. Fisher R.S. The new definition and classification of seizures and epilepsy Epilepsy Res. 139 2018 73 79 10.1016/j.eplepsyres.2017.11.015 29197668
7 Tatum W.O. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults Clin. Neurophysiol. 129 5 2018 1056 1082 10.1016/j.clinph.2018.01.019 29483017
8 Devulder A. Subclinical epileptiform activity and sleep disturbances in Alzheimer's disease Brain Behav 13 12 2023 10.1002/brb3.3306
9 Kapur V.K. Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of sleep medicine clinical practice guideline J. Clin. Sleep Med. 13 3 2017 479 504 10.5664/jcsm.6506 28162150
10 Guilleminault C. Excessive daytime sleepiness: a challenge for the practising neurologist Brain 124 8 2001 1482 1491 10.1093/brain/124.8.1482 11459741
11 Choi S.J. Joo E.Y. Hong S.B. Sleep–wake pattern, chronotype and seizures in patients with epilepsy Epilepsy Res. 120 2016 19 24 10.1016/j.eplepsyres.2015.11.010 26709878
12 Jo S. Sex differences in factors associated with daytime sleepiness and insomnia symptoms in persons with epilepsy Epilepsy Behav. 104 2020 10.1016/j.yebeh.2020.106919
13 Gutter T. Prevalence of sleep disturbances in people with epilepsy and the impact on quality of life: a survey in secondary care Seizure 69 2019 298 303 10.1016/j.seizure.2019.04.019 31152984
14 Chen N.C. Sleep quality and daytime sleepiness in patients with epilepsy Acta Neurol. Taiwan 20 4 2011 249 256 22315175
15 Klobucnikova K. Sleep-disordered breathing and excessive daytime sleepiness in patients with epilepsy - a polysomnographic study Neuroendocrinol. Lett. 37 4 2016 313 317 27857049
16 Klobucníková K. Is nocturnal epilepsy cause of disturbed quality of sleep and elevated daytime sleepiness? Neuroendocrinol. Lett. 35 5 2014 405 410 25275263
17 Kapur V.K. Sleepiness in patients with moderate to severe sleep-disordered breathing Sleep 28 4 2005 472 478 10.1093/sleep/28.4.472 16171292
18 Young T. The occurrence of sleep-disordered breathing among middle-aged adults N. Engl. J. Med. 328 17 1993 1230 1235 10.1056/nejm199304293281704 8464434
19 Manni R. Obstructive sleep apnea in a clinical series of adult epilepsy patients: frequency and features of the comorbidity Epilepsia 44 6 2003 836 840 10.1046/j.1528-1157.2003.55702.x 12790898
20 Lusic Kalcina L. Psychomotor performance in patients with obstructive sleep apnea syndrome Nat. Sci. Sleep 12 2020 183 195 10.2147/nss.S234310 32210650
21 Memon J. Manganaro S.N. Obstructive sleep-disordered breathing StatPearls 2024 StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC. Treasure Island (FL) ineligible companies
22 Chihorek A.M. Abou-Khalil B. Malow B.A. Obstructive sleep apnea is associated with seizure occurrence in older adults with epilepsy Neurology 69 19 2007 1823 1827 10.1212/01.wnl.0000279334.78298.d5 17984449
23 Shao C. Clinical features and contributing factors of excessive daytime sleepiness in Chinese obstructive sleep apnea patients: the role of comorbid symptoms and polysomnographic variables Cancer Res. J. 2019 2019 1 10 10.1155/2019/5476372
24 Ulander M. Correlates of excessive daytime sleepiness in obstructive sleep apnea: results from the nationwide SESAR cohort including 34,684 patients J. Sleep Res. 31 6 2022 10.1111/jsr.13690
25 Chen R. Daytime sleepiness and its determining factors in Chinese obstructive sleep apnea patients Sleep Breath. 15 1 2010 129 135 10.1007/s11325-010-0337-4 20174875
26 Lee S.-A. Factors contributing to excessive daytime sleepiness in Korean adults with epilepsy: a sleep questionnaire-based study Epilepsy Behav. 90 2019 61 65 10.1016/j.yebeh.2018.11.007 30513436
27 Wu M. Early- and late-onset narcolepsy: possibly two distinct clinical phenotypes Sleep Breath. 27 6 2023 2443 2452 10.1007/s11325-023-02820-5 37046113
28 Kainulainen S. Severity of desaturations reflects OSA-related daytime sleepiness better than AHI J. Clin. Sleep Med. 15 8 2019 1135 1142 10.5664/jcsm.7806 31482835
29 Bucks R.S. Olaithe M. Eastwood P. Neurocognitive function in obstructive sleep apnoea: a meta‐review Respirology 18 1 2012 61 70 10.1111/j.1440-1843.2012.02255.x
30 Suzuki M. Arousal index as a marker of carotid artery atherosclerosis in patients with obstructive sleep apnea syndrome Sleep Breath. 23 1 2018 87 94 10.1007/s11325-018-1664-0 29779142
31 Perrault A.A. Whole-night continuous rocking entrains spontaneous neural oscillations with benefits for sleep and memory Curr. Biol. 29 3 2019 402 411.e3 10.1016/j.cub.2018.12.028 30686735
32 Moons K.G.M. Prognosis and prognostic research: what, why, and how? Bmj 338 feb23 1 2009 10.1136/bmj.b375 b375-b375
33 Martynowicz H. Sleep architecture and daytime sleepiness in patients with erectile dysfunction Life 13 7 2023 10.3390/life13071541
34 Slonkova J. Hypocretin-1/orexin-A, sleep and excessive daytime sleepiness in patients with nonconvulsive status epilepticus: a cross-sectional cohort study Sleep Med. 119 2024 192 200 10.1016/j.sleep.2024.04.019 38701718
35 Maski K.P. Stability of nocturnal wake and sleep stages defines central nervous system disorders of hypersomnolence Sleep 44 7 2021 10.1093/sleep/zsab021
36 Zhang Y. Comparative polysomnography parameters between narcolepsy type 1/type 2 and idiopathic hypersomnia: a systematic review and meta-analysis Sleep Med. Rev. 63 2022 10.1016/j.smrv.2022.101610
37 Pizza F. Nocturnal sleep dynamics identify narcolepsy type 1 Sleep 38 8 2015 1277 1284 10.5665/sleep.4908 25845690
38 Liguori C. Toledo M. Kothare S. Effects of anti-seizure medications on sleep architecture and daytime sleepiness in patients with epilepsy: a literature review Sleep Med. Rev. 60 2021 10.1016/j.smrv.2021.101559
39 Thelengana A. Cognitive, behavioural and sleep-related adverse effects on introduction of levetiracetam versus oxcarbazepine for epilepsy Epilepsy Res. 150 2019 58 65 10.1016/j.eplepsyres.2019.01.004 30641352
40 Kataria L. Vaughn B.V. Sleep and epilepsy Sleep Med Clin 11 1 2016 25 38 10.1016/j.jsmc.2015.10.008 26972031
41 Shen Y. Subjective sleep disturbance in Chinese adults with epilepsy: associations with affective symptoms Epilepsy Res. 135 2017 150 157 10.1016/j.eplepsyres.2017.06.014 28697489
