Excessive Daytime Sleepiness Group Research Articles

Temporomandibular disorder patients with excessive daytime sleepiness present greater pain intensity and reduced jaw function.

Sleep disorders are associated with temporomandibular disorders (TMDs). Limited studies have focused on excessive daytime sleepiness (EDS) and its impact on jaw functions in TMD patients. The aim of the present investigation was to identify the impact of EDS on pain and jaw function in TMD patients. A total of 338 TMD patients (50 males and 288 females) was included. The Epworth Sleepiness Scale (ESS) was used to classify patients into EDS group (score ≥ 10) and non-EDS group (score < 10). The Jaw Functional Limitation Scale 8-item (JFLS-8) was used to assess the severity of jaw dysfunction. Pain intensity was evaluated using the Visual Analogue Scale (VAS). Anxiety and depression were evaluated using the Generalised Anxiety Disorder 7-item (GAD-7) and the Patient Health Questionnaire 9-item (PHQ-9). All included patients were diagnosed with pain-related TMD (PT), intra-articular TMD (IT) or combined TMD (CT). Compared with non-EDS patients, EDS patients exhibited more severe jaw dysfunction, greater pain intensity and higher PHQ-9 scores (p < .05). Multivariate analyses showed that EDS (B = 3.69), female gender (B = 3.69), and elevated GAD-7 score (B = 0.73) were significantly associated with an increased score on the JFLS-8 (p < .05). Moreover, bivariate logistic regression analysis indicated a significant relationship between EDS and PT (OR = 2.70, p = .007). The presence of EDS was more closely related to PT, but the causal relationship between them needs to be further confirmed. More concern and intervention to alleviate poor sleep quality might be highlighted during the treatment of TMD, especially PT subtype.

Challenging subjective excessive daytime sleepiness as an insomnia symptom: a retrospective study

SummaryDiagnostic manuals describe insomnia disorder (ID) characterised by fatigue and sleepiness as diurnal consequences of nocturnal symptoms. However, patients with ID do not frequently report sleepiness in the clinical setting. The present study aimed to investigate subjective sleepiness in ID measured through the Epworth Sleepiness Scale (ESS) and its independence towards daytime functioning and fatigue, and to evaluate cognitive behavioural therapy for insomnia (CBT‐I) improvement in daytime consequences and their relationship to sleepiness and fatigue. We retrospectively collected the ESS evaluation in a large sample of 105 healthy controls (HCs), 671 patients with ID, and 602 patients with sleep disorders characterised by excessive daytime sleepiness (EDS). Moreover, we conducted a pre–post evaluation of the ESS in a sub‐sample of patients with ID who underwent CBT‐I. Component 2 of the Insomnia Severity Index and Profile of Mood States–Fatigue Inertia Scale was used to evaluate daytime functioning and fatigue. Patients with ID reported ESS levels comparable to that observed in HCs and significantly lower than the EDS group. No significant correlation arose between ESS and the diurnal impact of the disorder, suggesting the independence between daytime functioning and sleepiness in ID. Contrarily, insomnia severity and diurnal impact significantly correlated with fatigue. Data showed a statistically significant increase in sleepiness after CBT‐I, despite significantly improving daytime consequences and fatigue. Although diagnostic manuals report sleepiness and fatigue as daytime consequences of sleep symptoms in patients with ID, these retrospective data indicate a dissociation between these entities. This evidence aligns with the core feature of ID: the hyperarousal status that pervades patients also during wakefulness.

Emergence of different dimensions of sleepiness in a general population sample: An EPISONO study

IntroductionRecent evidence supports the idea that sleepiness has several dimensions, comprising psychophysiological phenomena, such as sleep propensity and sleepiness perception. The Epworth Sleepiness Scale (ESS) is among one of the most used sleepiness assessment tools, but recent data suggest that it might not detect problematic impairments in sleep health. More research is warranted investigating sleepiness dimensions with large sample sizes, using both objective and subjective methods of analyzing sleep. MethodsWe used data from the Epidemiological Sleep Study (EPISONO), a major study carried out in Brazil using a representative sample of 1042 participants of the general population of Sao Paulo city, who completed questionnaires and underwent type I polysomnography. Sleepiness was measured by the ESS (sleep propensity) and the UNIFESP Sleep Questionnaire, which asked about the frequency of feeling sleepy during the day (sleepiness perception). The participants were distributed into 4 groups in respect of excessive daytime sleepiness (EDS) according to the following criteria: 1) having an ESS score >10 (ESS group). 2) feeling sleepy ≥3 times per week (Frequent EDS group). 3) the combined criteria (Combined EDS group). 4) having no evidence of EDS (no EDS group). The UNIFESP Sleep Questionnaire was used to obtain self-reported sleep duration, sleep debt, and sleep duration variability. Participants also completed the Pittsburgh Sleep Quality Index, the Insomnia Severity Index, and a pre-polysomnography sleep questionnaire. ResultsAfter removing participants with missing data, there were 620 participants with no EDS, 255 individuals in the ESS group, 68 in the Frequent EDS group, and 73 in the Combined EDS group. Compared to the no EDS group, the ESS and Combined EDS groups had significantly increased sleep efficiency, diminished sleep latency, wake after sleep onset, and self-reported weekly sleep duration. The Frequent and Combined EDS groups had significantly higher scores in the Insomnia Severity Index and Pittsburgh Sleep Quality Index. All EDS groups had an increased likelihood of nonrestorative sleep. EDS frequency and the ESS scores were significantly correlated. ConclusionsParticipants with a high sleep propensity had a profile suggesting prior sleep deprivation, while high sleepiness perception was associated with impaired sleep quality. These findings indicated that, in the general population, these instruments evaluated separate sleepiness dimensions with different associations, highlighting that screening using a combination of instruments might be more effective in detecting impairments in sleep health.

Serum metabolic alterations in peritoneal dialysis patients with excessive daytime sleepiness

Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambulatory peritoneal dialysis patients were assigned to the EDS group and the non-EDS group according to the Epworth Sleepiness Scale (ESS). Ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the differential metabolites. Twenty-seven (male/female, 15/12; age, 60.1 ± 16.2 years) PD patients with ESS ≥ 10 were assigned to the EDS group, while twenty-one (male/female, 13/8; age, 57.9 ± 10.1 years) PD patients with ESS < 10 were defined as the non-EDS group. With UHPLC-Q-TOF/MS, 39 metabolites with significant differences between the two groups were found, 9 of which had good correlations with disease severity and were further classified into amino acid, lipid and organic acid metabolism. A total of 103 overlapping target proteins of the differential metabolites and EDS were found. Then, the EDS–metabolite–target network and the protein–protein interaction network were constructed. The metabolomics approach integrated with network pharmacology provides new insights into the early diagnosis and mechanisms of EDS in PD patients.

Reliability and Validity of the Turkish Version of the Observation and Interview Based Diurnal Sleepiness Inventory

Objective: The Observation and Interview Based Diurnal Sleepiness Inventory (ODSI) is a valid 3-item tool used for assessment of excessive daytime sleepiness (EDS). The aim of this study was to investigate the reliability and validity of the ODSI in the Turkish language.Methods: Linguistic validation of the ODSI was performed by forward-backward translation. The Turkish version of the ODSI and the Epworth Sleepiness Scale (ESS) were administered in EDS and control groups.Results: The ODSI was tested in 106 older patients. The median age of the patients was 73 (65–89) years and 55.7% were female. The EDS group was older and more dependent on instrumental activities of daily living than the control group. The inter-rater reliability of the ODSI was high (interclass correlation coefficient [ICC]: 0.851, 95% confidence interval [CI]: 0.540–0.958, p&lt;0.001). Test-retest reliability was also high for the total sample (ICC: 0.871, 95% CI: 0.632–0.959, p&lt;0.001). Positive strong correlations were found with the ESS (Speraman’s rho=0.876, 95% bootstrap CI [0.813–0.918], p&lt;0.001). ROC curve analysis showed an area under the curve of 0.968 (95% CI: 0.937–0.998), a cutoff score of ≥6, a sensitivity of 94.1%, a specificity of 87.6%, a positive predictive value of 76.55%, and a negative predictive value of 97.2%.Conclusion: Our data validate the ODSI for application in Turkish-speaking populations. The simplicity, reliability, and the apparent lack of relevant influences of cultural background on performance of the 3-item ODSI make it a valuable tool for clinical management and research.

Cardiovascular Outcomes in Adults with Coronary Artery Disease and Obstructive Sleep Apnea with versus without Excessive Daytime Sleepiness in the RICCADSA Cinical Trial.

Rationale: Recent randomized controlled trials did not show cardiovascular benefits of continuous positive airway pressure (CPAP) in adults with coronary artery disease (CAD) and obstructive sleep apnea (OSA) in intention-to-treat analyses. It has been argued that exclusion of patients with OSA with excessive daytime sleepiness (EDS), who may be most likely to benefit from CPAP treatment, may be a reason for the null results. Objectives: We addressed 1) the effect of concomitant EDS on adverse outcomes in patients with CAD and OSA; and 2) whether the cardiovascular benefit of CPAP adherence differs between individuals with versus without EDS. Methods: This was a secondary analysis of the RICCADSA (Randomized Intervention with CPAP in CAD and Obstructive Sleep Apnea) trial, conducted in Sweden between 2005 and 2013. Data were analyzed from 155 patients with CAD with OSA (apnea-hypopnea index ⩾ 15/h) and EDS (Epworth Sleepiness Scale score ⩾ 10), who were allocated to CPAP and 244 patients without EDS (ESS < 10), who were randomized to CPAP or no CPAP. Patients who were allocated to no CPAP or were nonadherent (CPAP usage < 4 h/night) were compared with adherent patients (CPAP usage ⩾ 4 h/night) at 1-year follow-up. Inverse probability of treatment weighting was applied to mimic randomization of EDS. The primary endpoint was the first event of repeat revascularization, myocardial infarction, stroke, or cardiovascular mortality. Results: The median follow-up was 52.2 months. The incidence of the primary endpoint did not differ significantly between the EDS versus no-EDS groups in the entire cohort. Within the adherent group, patients without EDS had a significantly decreased risk compared with patients with EDS (adjusted hazard ratio, 0.41; 95% confidence interval, 0.20-0.85; P = 0.02). Conclusions: Adverse cardiovascular outcomes did not differ by degrees of EDS for patients with CAD with OSA who were untreated or nonadherent to treatment. CPAP use, at least 4 h/night, was associated with reduced adverse outcomes in participants without EDS. Clinical trial registered with www.clinicaltrials.gov (NCT00519597).

The Number of Monthly Night Shift Days and Depression Were Associated with an Increased Risk of Excessive Daytime Sleepiness in Emergency Physicians in South Korea.

This study aimed to report the prevalence and identify the factors associated with excessive daytime sleepiness (EDS) among emergency physicians in South Korea. We analyzed the Korean Emergency Physicians Survey data from 15 January to 26 February 2021. EDS was evaluated using the Epworth sleepiness scale, and a score of 11 or more indicated the presence of EDS. We conducted univariable and multivariable logistic regression analyses to verify the associated factors. A total of 1307 participants responded to the survey, and the response rate was 61.3%. Nine hundred fifty-four participants were included in the study. Two hundred ninety-three participants were classified as the EDS group, and six hundred sixty-one were classified as the non-EDS group. The prevalence of EDS was 30.7% (95% confidence interval (CI), 27.8–33.6%). Monthly night-shift days (odds ratio (OR) 1.106, 95% CI 1.028–1.191) and depression (OR 2.635, 95% CI 1.799–3.861) were significantly associated with an increased risk of EDS, and fair sleep quality (OR 0.560, 95% CI 0.318–0.985) was associated with a decreased risk of EDS. Almost one in three emergency physicians in South Korea suffer from daytime sleepiness. The number of monthly night-shift days and depression were associated with an increased risk of EDS.

Brain Network Analysis via Graph-Theory on E.E.G. Recordings in Physiological and Pathological Brain Aging

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value < 0.0001). WDS group presented more complexity than EDS in the occipital zone, while a stronger nonlinear coupling between occipital and frontal zones was detected in EDS patients than in WDS. The AMIF and CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients.

Changes in EEG Alpha Activity during Attention Control in Patients: Association with Sleep Disorders.

We aimed to assess which quantitative EEG changes during daytime testing in patients with sleep disorder (primary insomnia and excessive daytime sleepiness groups). All experimental study participants were subjected to a long-term test for maintaining attention to sound stimuli, and their EEGs were recorded and then processed, using wavelet analysis, in order to estimate the power and frequency structure of alpha activity. In healthy subjects, the maximum increase in the alpha rhythm occurred near 9 Hz. Patients with primary insomnia were characterized by an increase in the amplitude of the alpha rhythm near 11 Hz. For subjects with sleep disorders, an increase in the amplitude of the alpha rhythm was observed in the entire frequency range (7.5–12.5 Hz), with a maximum increase at 9–10 Hz. Significant differences () for changes in the alpha rhythm dynamics in the course of performing the attention test were observed in the frequency range of 7.5–10.5 Hz between the control group and patients with sleep disorders. The ratios of the alpha rhythm power values for passive stages with closed eyes before and after active stage were significantly different among the groups of healthy sleep volunteers, patients with primary insomnia, and patients with impaired sleep hygiene within the range of 9.5 to 12.5 Hz. The results of the current study supported the notion of a 24-h hyperarousal in primary insomnia.

A novel parameter is better than the AHI to assess nocturnal hypoxaemia and excessive daytime sleepiness in obstructive sleep apnoea

To evaluate whether the percentage of total sleep time spent with apnoea and hypopnoea duration time (AHT%) is better than the apnoea-hypopnoea index (AHI) for the assessment of nocturnal hypoxaemia and excessive daytime sleepiness (EDS) in patients with obstructive sleep apnoea (OSA). Patients with suspected OSA were enrolled. Polysomnography, Epworth Sleepiness Scale, self-administered surveys and anthropometric measures were performed. The efficiency of AHT% and the AHI was evaluated for nocturnal hypoxaemia and EDS. A total of 160 eligible participants were analysed. The median AHT% in normal, mild, moderate and severe OSA patients was significantly different in the four-group patients with OSA. Spearman rank correlations analysis found that the associations were stronger between AHT% with percentage of total sleep time and O2 saturation of < 90% and minimum nocturnal oxygen saturation than these parameters with the AHI. AHT% had a greater area under the curve than the AHI for predicting EDS in patients with OSA. AHT% was significantly higher in the EDS group. We present a novel parameter, AHT%, to evaluate nocturnal hypoxaemia and EDS in OSA patients. AHT% partially compensates for the shortcomings of the AHI. AHT% is better than the AHI for assessing nocturnal hypoxaemia and EDS. AHT% reflects different clinical characteristics associated with OSA from a new perspective.

The rate of decrease in oxygen desaturation during severe obstructive sleep apnea syndrome is correlated with subjective excessive daytime sleepiness.

To explore factors that influence subjective excessive daytime sleepiness (EDS) in patients with severe obstructive sleep apnea syndrome (OSAS). Patients with snoring seen at the Sleep Medicine Center of The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University between October 2018 and November 2019 were included in this study. All patients underwent polysomnography (PSG). Noninvasive frequency-domain analysis was used to assess the autonomic nervous system regulation of the heart, with the low frequency (LF)/high frequency (HF) power ratio used to represent the sympathetic-parasympathetic balance. Daytime sleepiness was evaluated by the Epworth sleepiness scale (ESS). Overnight apnea episodes were included for analyses. The rate of pulse oxyhemoglobin saturation (SpO2) decrease was measured as the change in the percentage of SpO2 per second after obstructive apnea and was expressed as the oxygen desaturation rate (ODR). A total of 101 patients with severe OSAS were enrolled in this study and were further divided into two groups: the EDS group (ESS > 10, n = 52) and the non-EDS group (ESS ≤ 10, n = 49). The apnea-hypopnea index (AHI), respiratory effort-related arousals (RERAs), and LF/HF power ratio were significantly higher in the EDS group than in the non-EDS group (AHI: 69.9 ± 14.5 vs. 57.9 ± 16.1 events/h; RERAs: 42.2 ± 16.7 vs. 30.4 ± 13.7 events/h; LF/HF power ratio: 2.9 ± 0.8% vs. 2.4 ± 0.9%, all p < 0.001). Multiple linear regression analyses revealed that after adjusting for covariates expected to affect this relationship, ESS scores were correlated with ODR (β = 0.520, p < 0.001) and LF/HF power ratio (β = 0.155, p = 0.028), rather than with the traditional sleep-disordered breathing parameters. Compared with the traditional PSG parameters, both ODR and an increased LF/HF power ratio were more closely related to daytime sleepiness, especially ODR.

Power spectral densities of nocturnal pulse oximetry signals differ in OSA patients with and without daytime sleepiness

BackgroundAs nocturnal hypoxemia and heart rate variability are associated with excessive daytime sleepiness (EDS) related to OSA, we hypothesize that the power spectral densities (PSD) of nocturnal pulse oximetry signals could be utilized in the assessment of EDS. Thus, we aimed to investigate if PSDs contain features that are related to EDS and whether a convolutional neural network (CNN) could detect patients with EDS using self-learned PSD features. MethodsA total of 915 OSA patients who had undergone polysomnography with multiple sleep latency test on the following day were investigated. PSDs for nocturnal blood oxygen saturation (SpO2), heart rate (HR), and photoplethysmogram (PPG), as well as power in the 15–35 mHz band in SpO2 (PSPO2) and HR (PHR), were computed. Differences in PSD features were investigated between EDS groups. Additionally, a CNN classifier was developed for identifying severe EDS patients based on spectral data. ResultsSpO2 power content increased significantly (p < 0.002) with increasing severity of EDS. Furthermore, a significant (p < 0.001) increase in HR-PSD was found in severe EDS (mean sleep latency < 5 min). Elevated odds of having severe EDS was found in PSPO2 (OR = 1.19–1.29) and PHR (OR = 1.81–1.83). Despite these significant spectral differences, the CNN classifier reached only moderate sensitivity (49.5%) alongside high specificity (80.4%) in identifying patients with severe EDS. ConclusionsWe conclude that PSDs of nocturnal pulse oximetry signals contain features significantly associated with OSA-related EDS. However, CNN-based identification of patients with EDS is challenging via pulse oximetry.

Analysis of influencing factors of excessive daytime sleepiness in adults with different degrees of sleep-disordered breathing

Objective:To explore the main influencing factors of excessive daytime sleepiness（EDS） in adults with different degrees of sleep-disordered breathing（SDB）, which will provide the scientific evidences for the individualized diagnosis and treatment. Method:Retrospective analysis was performed on the clinical data of 361 young and middle-aged snoring patients monitored by polysomnography. According to the presence or absence of obstructive sleep apnea（OSA） and apnea hypopnea index（AHI） levels, they were divided into primary snoring（AHI<5）, mild OSA（AHI 5-<15）, moderate OSA（AHI 15-<30） and severe OSA（AHI≥30）. From sleep efficiency（ES）, different sleep stages（REM, NREM1, NREM2, NREM3） ratio of total sleep, oxygen reduction index（ODI）, blood oxygen saturation<90% of total sleep time（TS90%）, the average saturation of blood oxygen（MSaO₂） and the lowest blood oxygen saturation（LSaO₂） of all-night sleep, and AHI in different sleep stages（REM-AHI, NREM-AHI）, MSaO₂ in different sleep stages（REM-MSaO₂, NREM-MSaO₂） and LSaO₂ in different sleep stages（REM-LSaO₂, NREM-LSaO₂）, the main influencing factors of EDS were discussed. Result:Among the 361 patients, 23 patients suffered from the primary snoring, 47 patients with mild OSA, 56 patients with moderate OSA, and 235 patients with severe OSA. REM-AHI, ODI and TS90% in EDS group were 10.9, 9.6 and 0.2 respectively in patients with primary snoring, which were significantly higher than those without EDS（P<0.01）. The main influencing factors of EDS were REM-AHI, ODI, and TS90%. However, among patients with mild OSA, REM-AHI was the main influencing factor of EDS, REM-AHI of the EDS group was 29.6, which was significantly higher than that of the non-EDS（P<0.05）. In patients with moderate OSA, LSaO₂ of the EDS group was 76.2, significantly lower than the group without EDS（P<0.05）, the main influencing factor of EDS is LSaO₂. In patients with severe OSA, BMI, ODI and TS90% in EDS group were significantly higher than those without EDS（P<0.05 or P<0.01）, while NREM-MSaO₂, MSaO₂ and LSaO₂ were significantly lower than those without EDS（P<0.05 or P<0.01）. The main influencing factors of EDS were BMI, NREM-MSaO₂, MSaO₂, LSaO₂, ODI and TS90%. Conclusion:Frequent apnea during REM stage may be one of the important factors causing EDS in patients with primary snoring and mild OSA. For patients with moderate and severe OSA, intermittent hypoxia at night may be the main factor leading to EDS, and obesity may promote the development of the disease and the occurrence of sleepiness.

Aberrant DNA methylation of the toll-like receptors 2 and 6 genes in patients with obstructive sleep apnea.

Obstructive sleep apnea (OSA) is a syndrome leading to chronic intermittent hypoxia, and the up-regulation of toll-like receptors (TLR) 2 and 6 on peripheral blood cells has been reported. We hypothesized that DNA methylation in TLR2 and TLR6 genes may play a role in the development of OSA and its excessive daytime sleepiness (EDS) phenotype. DNA methylation over 28 cytosine-phosphate-guanine (CpG) sites of the TLR2 promoter region and 3 CpG sites of the TLR6 gene body, and their protein expressions were measured by using pyrosequencing and ELISA methods in 18 heathy subjects (HS) and 58 patients with severe OSA (divided into 18 non-EDS and 40 EDS group). Patients with severe OSA had higher DNA methylation levels over five CpG sites (#1, #2, #3, #25 and #28) and lower DNA methylation levels over CpG site #18 of the TLR2 promoter region, higher DNA methylation levels over two CpG sites (#1 and #3) of the TLR6 gene body, and higher protein expressions of TLR6 than HS. The CpG site #2 of the TLR6 gene body was hypermethylated in severe OSA patients with EDS. Both DNA methylation levels over CpG site #1 of the TLR6 gene body and protein expressions of TLR6 were reduced after more than 6 months of nasal CPAP treatment in seven selected patients. Aberrant DNA methylation of the TLR2 promoter region and TLR6 gene body are associated with the consequence of severe OSA and its EDS phenotype.

Clinical Features and Contributing Factors of Excessive Daytime Sleepiness in Chinese Obstructive Sleep Apnea Patients: The Role of Comorbid Symptoms and Polysomnographic Variables.

Background The occurrence and severity of excessive daytime sleepiness (EDS) vary considerably among obstructive sleep apnea (OSA) patients. This study was designed to investigate the characteristics of EDS and identify its contributing factors in OSA patients. Methods This was a cross-sectional study from a tertiary medical center in China. A total of 874 consecutive patients with newly diagnosed OSA were included. Subjective daytime sleepiness was assessed with the Epworth Sleepiness Scale (ESS). The subjects were assigned to the non-EDS group (582 patients), mild to moderate EDS group (227 patients), and severe EDS group (65 patients) according to the ESS scores. The clinical features and polysomnographic parameters were acquired and analyzed to identify the differences between groups and the determinants of EDS. Results The age of patients with severe EDS (49.5 ± 11.3) was slightly greater than that of patients with mild to moderate EDS (44.5 ± 10.2) (p < 0.05) and non-EDS patients (45.2 ± 12.0) (p < 0.05). Body mass index (BMI) was highest in the severe EDS group (29.1 ± 3.6 kg/m2) (p < 0.0001), intermediate in the mild to moderate EDS group (27.9 ± 3.3 kg/m2), and lower in the non-EDS group (26.8 ± 3.3 kg/m2). Logistic regression analysis showed waist circumference, memory loss, work/commute disturbances, and sleep efficiency were independently associated with mild to moderate EDS, and the microarousal index, apnea-hypopnea index (AHI), and saturation impair time below 90% were independent contributing factors of mild to moderate EDS. Meanwhile, age, neck circumference, gasping/choking, memory loss, work/commute disturbances, and sleep latency were independently associated with severe EDS, and the AHI and mean SpO2 were independent contributing factors of severe EDS. Conclusions OSA patients with various severities of EDS are more obese and have more comorbid symptoms compared to patients without EDS. Sleep fragmentation, respiratory events, and nocturnal hypoxia may be predictors of EDS. Comprehensive consideration of demographic, clinical, and polysomnographic factors is required when evaluating OSA patients.

Clinical Features and Correlates of Excessive Daytime Sleepiness in Parkinson's Disease.

Objective: To explore the clinical features and correlates of excessive daytime sleepiness (EDS) in a Chinese population of Parkinson's disease (PD) patients.Methods: Patients with clinically established or clinically probable PD were recruited. Clinical and demographic data were collected, and participants were evaluated using standardized assessment protocols. Patients were divided into PD with EDS and PD without EDS groups based on the Epworth sleepiness scale (ESS) scores, with a cutoff score of 10. Clinical manifestations were compared between patients with and without EDS, and correlates of EDS were also studied. In addition, the relationship between EDS and poor nighttime sleep quality was analyzed.Results: A total of 1,221 PD patients were recruited in our study. The mean ESS (min, max) score was 7.6 ± 6.1 (0, 24), and 34.1% of the patients had ESS scores ≥10. No difference was seen in lifestyle (except for alcohol consumption), environmental factors, BMI, levodopa equivalent dose (LED), initial presentation of motor symptoms, motor subtype, and wearing off between patients with and without EDS. The PD with EDS group had a higher proportion of male patients and a higher average patient age. Moreover, the PD with EDS group showed older age at PD onset, lower educational level, and longer disease duration. Patients with EDS had higher scores on the Hoehn-Yahr scale and the Unified Parkinson's Disease Rating Scale (UPDRS) parts I, II, and III score, more severe non-motor symptoms, and poorer quality of sleep and life. Logistic regression analyses demonstrated that EDS was associated with male sex, age, cognitive impairment, PD-related sleep problems, rapid eye movement sleep behavior disorder (RBD), and worse quality of life (QoL).Conclusion: EDS is a general clinical manifestation in PD, and there were significant differences in clinical features between patients with and without EDS. Moreover, our study proved that many factors were associated with EDS, including male sex, age, cognitive impairment, PD-related sleep problems, RBD, and worse QoL. Understanding the clinical characteristics of EDS in PD patients may help identify EDS early, improve QoL, and reduce the occurrence of accidents.

The influence of excessive daytime sleepiness and sleep quality on anxiety and depression in patients with obstructive sleep apnea hypopnea syndrome

Objective: To explore the factors that contribute to the anxiety and depression in obstructive sleep apnea hypopnea syndrome (OSAHS) patients in terms of excessive daytime sleepiness (EDS) and sleep quality. Methods: A total of 196 OSAHS patients, including 103 severe patients and 93 mild-moderate patients, were enrolled. Polysomnography was carried on at the sleep center of the First Hospital of China Medical University between May 2013 and November 2015. According to the Epworth sleepiness scale (ESS) and the subject daytime sleepiness symptom, all patients were divided into EDS group and non-EDS group. The patients' general information and subjective symptoms were recorded. Emotional states were assessed with self-rating anxiety scale (SAS) and self-rating depression scale (SDS). Sleep quality was evaluated with Pittsburgh sleep quality index (PSQI). The anxiety and depression related factors were studied by regression analysis. Results: (1) In severe OSAHS group, the patients with EDS showed higher PSQI(6.22±2.57 vs. 4.05±3.72, P<0.01) and oxygen desaturation index(ODI)[(57.70±17.53) events/h vs. (48.23±22.01) events/h, P<0.05] when compared with those without EDS. (2) In both severe and mild-moderate OSAHS groups, the patients with EDS presented higher SAS scores (severe: 33.86±7.60 vs.28.95±4.71, mild-moderate: 37.46±10.68 vs. 33.40±11.07, P<0.05) and SDS scores (severe: 32.81±8.36 vs. 28.90±4.53, mild-moderate:36.98±12.77 vs. 31.70±10.94, P<0.05) when compared with those without EDS. (3) The multiple regression analysis showed that the SAS scores were related to ESS, PSQI, insomnia and nasal obstruction (R(2)=0.356, P<0.05), and the SDS scores were related to ESS, PSQI and insomnia(R(2)=0.344, P<0.05). Conclusions: The anxiety and depression of OSAHS patients are closely related to the severity of EDS and sleep quality. Both severe and mild-moderate OSAHS patients with EDS have worse anxiety and depression scores.

Predictors of excessive daytime sleepiness in patients with obstructive sleep apnea syndrome

Objective: Excessive daytime sleepiness (EDS) in patients with obstructive sleep apnea syndrome (OSAS) is a known risk factor for various accidents and can cause poor quality of life. In this study, we intended to study the demographic and clinical characteristics of EDS in patients with OSAS. Methods: This retrospective study gathered data from 283 patients. We classified patients with Epworth Sleepiness Scale (ESS) scores ≥ 10 points as the EDS group and those with an ESS score

Delayed sleep/wake rhythm and excessive daytime sleepiness correlate with decreased daytime brain activity during cognitive task in university students

Insufficient sleep and irregular sleep/wake rhythm are common problems among university students. We investigated the effect of sleep/wake rhythm and excessive daytime sleepiness (EDS) on the cortical oxygenation as measured by near-infrared spectroscopy (NIRS) and cognitive performance in university students. Peak- and integral values by a word fluency task were measured with NIRS. EDS was evaluated by the Epworth sleepiness scale (ESS), and performance function was evaluated using N-back task. Peak cerebral oxygenation was significantly correlated with ESS, bedtime, wake-up time, and median time of sleep. Accuracy on 2-back task was significantly correlated with integral value. Peak- and integral values were significantly lower, and bedtime and median time of sleep were significantly delayed in the EDS group than in the non-EDS group. EDS accompanied by delayed sleep/wake rhythm and short sleep duration may play an important role in decreasing daytime brain activity and cognitive performance.

Sleep Duration and Excessive Daytime Sleepiness Are Associated With Incidence of Disability in Community-Dwelling Older Adults

ObjectiveAlthough sleep disturbances are associated with disability among older adults, no longitudinal study has examined the impact of sleep assessed based on both sleep quality and quantity on incident disability. This study examined whether sleep duration and excessive daytime sleepiness were associated with incidence of disability in community-dwelling older adults. MethodsA total of 4756 older adults (53.3% women, mean age 71.9 years) met the entry criteria for this study. We measured monthly incident disability, defined as the onset of being certified for personal support or care as required by Japanese public long-term care insurance during the preceding 24 months. Sleep duration, excessive daytime sleepiness (EDS), and demographic factors were assessed at baseline. Cox's proportional hazard regression analysis estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of incidence of disability according to the 3 categories of sleep duration (short: ≤6.0 hours, mid: 6.1 to 8.9 hours, long: ≥9.0 hours), and we used mid duration sleepers as the reference group. ResultsLong sleep duration (HR 1.43, 95% CI 1.04–1.97) and presence of EDS (HR 1.41, 95% CI 1.01–1.98) were associated with higher rates of incident disability. Furthermore, a combination of sleep duration and EDS was associated with a higher rate of incident disability than the mid and no EDS group (HR 2.25, 95% CI 1.36–3.70). ConclusionLong sleep duration and EDS affected the incident of disability; thus, older adults with both sleep patterns may require an intervention to alter their sleep habit.