Good Sleep Group Research Articles

Association of baseline sleep duration and sleep quality with seizure recurrence in newly treated patients with epilepsy.

Although sleep duration and sleep quality are considered to be significant factors associated with epilepsy and seizure risk, findings are inconsistent, and their joint association remains uncertain. This study aimed to determine independent and joint associations of these two modifiable sleep features with seizure recurrence risk in newly treated patients with epilepsy (PWE). This is a prospective cohort study of newly treated PWE at a comprehensive epilepsy center in northeast China between June 2020 and December 2023. Self-reported sleep duration and sleep quality were collected at baseline. All patients were followed for 12 months for recurrent seizures. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) of seizure recurrence. Models fitted with restricted cubic spline were conducted to test for linear and nonlinear shapes of each association. A total of 209 patients were included, and 103 experienced seizure recurrence during follow-up. Baseline short sleep was significantly associated with greater risk of seizure recurrence (adjusted HR = 2.282, 95% confidence interval [CI] = 1.436-3.628, p < .001). Sleep duration (h/day) and recurrent seizure risk showed a significant nonlinear U-shaped association, with a nadir at 8 h/day. Baseline poor sleep quality was significantly associated with greater risk of seizure recurrence (adjusted HR = 1.985, 95% CI = 1.321-2.984, p < .001). Pittsburgh Sleep Quality Index score and seizure recurrence risk exhibited a positive linear association. Participants with a combination of poor quality-short sleep showed the highest risk of seizure recurrence (adjusted HR = 3.13, 95% CI = 1.779-5.507, p < .001) compared to the referent good quality-intermediate sleep group. Baseline sleep duration and sleep quality were independently and jointly associated with risk of seizure recurrence in newly treated PWE. Our results point to an important potential role of baseline sleep duration and sleep quality in shaping seizure risk.

Study on the Profiles of Sleep Disorders, Associated Factors, and Pathways Among Gynecological Cancer Patients - A Latent Profile Analysis.

Gynecological cancer generally refers to malignant tumors in gynecology, commonly including cervical cancer, endometrial cancer, and ovarian cancer. Patients with gynecological cancer often suffer from sleep disorders after clinical treatment. Except for serious sleep disorders, female characteristics, family roles, and feudal beliefs make their self-stigma at a medium to high level, leading to huge pressure. This study aims to identify potential categories of sleep disorders, and analyze the relationship between self-stigma, perceived stress, and sleep disorders. A cross-sectional study was conducted in 2021-2022. Two hundred and two patients' data were collected from ShengJing Hospital Affiliated to China Medical University in Liaoning, Shenyang by using paper questionnaires for face-to-face surveys. The survey tools included the Pittsburgh Sleep Quality Index (PSQI), the Perceived Stress Scale (PSS), and the Social Impact Scale (SIS). Potential profile analysis (LPA), multiple logistic regression analysis, and structural equation modeling (SEM) were performed by Mplus 8.3, SPSS 26.0, and Amos 24.0 statistical tools, respectively. Three latent patterns of sleep disorders were found: "Good Sleep group (42.5%)", "Sleep Deficiency group (32.4%)", and "Sleep Disturbance group (25.1%)". Patients with high perceived stress were more likely to report a moderate (OR=1.142, 95% CI: 1.061-1.230) or high (OR=1.455, 95% CI: 1.291-1.640) level of sleep disorders. Self-stigma did not have a direct effect on sleep disorders (0.055, P>0.05), but it could have indirect effect on sleep disorders through perceived stress (0.172, P<0.01). The perceptions of sleep disorders among gynecological cancer patients varies and exhibits individual differences. Gynecological cancer patients who feels alienated or discriminated may cause high pressure. This internal pressure can exacerbate sleep disorders.

Sleep quality, perceived stress, and attention levels: A study on medical students

Background: Sleep is the most important yet least understood function of the brain. It is seen that students usually get lesser duration of sleep, due to academic and social demands. In our study, we are trying to use relatively short-duration tasks, which are software-based and can be easily used in a clinical setting for screening purpose, for the assessment of attention in individuals with poor sleep quality. Aims and Objectives: The aim of this study was to compare the perceived stress levels in students based on the quality of sleep and to compare the attention in students based on the quality of sleep. Materials and Methods: Eighty-four participants were divided into good and bad sleep quality based on the Pittsburgh sleep quality index (PSQI) scores and their perceived stress scores were obtained. All of them were subjected to smartphonebased cognitive function testing using color word and word color Stroop test. Results: Eighty-four subjects were recruited for the study from the Bidar Institute of Medical Sciences, Bidar, of which 34 (40%) were in the good sleep group and 50 (60%) in the bad sleep group. The median PSQI score in the group with bad sleep quality was found to be significantly higher than the median PSQI scores of the group with good sleep. The median word color Stroop score in the good sleep quality was found to be significantly higher than the score of the bad sleep group. Similarly, the median color word Stroop scores were significantly higher in the good sleep group than that of the bad sleep quality group. Conclusion: Sleep quality seems to increase the levels of perceived stress in students. Sleep affects the attention of the subjects in a negative way.

Patterns of sleep quality and its influence factors: A latent class model among students of medical university in Hubei Province, China

BackgroundSleep problem among undergraduate students has become one of the most pressing public health problems. This study aimed to explore the latent class of sleep patterns and the factors affecting sleep in Chinese students of medical university. Methods3423 students participated in the cross-sectional study. The survey consisted of the reduced Morningness-Evening Questionnaire, the Pittsburgh Sleep Quality Index, and Health-Promoting Lifestyle Profile-II. Latent profile analysis and multinominal logistic regression analysis were performed. ResultsThree potential sleep categories were identified: “sleep disorder group” (1.87 %), “daytime dysfunction group” (24.42 %), and “good sleep group” (73.71 %). Compared with the “good sleep group,” the “sleep disorder group” showed monthly living expenses (RMB) ≥ 3000 yuan (OR) = 13.04), interpersonal relationships as poor (OR = 3.71), health status as poor (OR = 45.09), circadian rhythm as eveningness (OR = 6.17), and poor health-promoting lifestyles (OR = 2.090) as its risk factors (all p < 0.05). Meanwhile, sophomore (OR = 1.75), junior (OR = 1.52), interpersonal relationships as poor (OR = 1.88), health status as poor (OR = 4.62), intermediate-chronotype (OR = 2.19), eveningness chronotype (OR = 5.66), and health-promoting lifestyles as poor (OR = 1.55) were identified as risk factors for the “daytime dysfunction group” (all p < 0.05). LimitationsCausal conclusions can not be drawn and recall bias in data collection. ConclusionsSignificant population heterogeneity was found in the sleep quality. Implementing targeted interventions focusing on circadian rhythm and lifestyle is crucial to improve the sleep quality of students with different conditions.

Sleep Quality Assessment in Correlation to Autonomic Nerve Function in Type 2 Diabetic Patients

Background and Objective Diabetes mellitus negatively impacts the quality of life of its patients. Autonomic dysfunction may disturb sleep quality by negatively affecting multiple systems, including, but not limited to, the cardiovascular, respiratory, and genitourinary tracts. The current study aims to assess sleep quality and examine the degree of correlation with autonomic nervous function in relatively well-controlled type 2 diabetic patients.Methods This study uses a cross-sectional design to assess sleep quality in 88 type 2 diabetic patients via the Pittsburg Sleep Quality Index (PSQI), accordingly dividing them into two groups: good or poor sleepers. Subsequently, the study evaluates autonomic nerves’ conductivity by measuring electrical skin conductance using Sudoscan for the hands and feet.Results Of 88 recruited patients, 53% showed poor sleep quality, with higher incidence in females. Autonomic nerve conductivity showed moderate damage in poor sleepers with 59.53 ± 13.35 μS and 59.68 ± 16.91 μS of hand and foot electrodes, respectively. Autonomic damage induces sleep disturbance mainly through increased nighttime voiding in 91.49% of the poor sleepers group compared to 41.46% in the good sleepers group. PSQI score was found to strongly and inversely correlate with autonomic nerve conductivity via hand electrodes, with a correlation coefficient of -0.62 and a determination coefficient of 0.39.Conclusion Poor sleep quality seems to be a significant problem even in relatively well-controlled type 2 diabetic patients with no diagnosed micro- or macrovascular complications. Autonomic dysfunction negatively affects the quality of sleep and leads to sleep disturbance by increasing nighttime micturition as one of its complications.

Insomnia symptoms among older adults during the first year of the COVID-19 pandemic: A longitudinal study

ObjectiveTo identify sociodemographic, psychological, and health factors related to trajectories of insomnia symptoms in older adults during the COVID-19 pandemic. MethodsFrom May 2020 to May 2021, 644 older adults (mean age = 78.73, SD = 5.60) completed telephone-administered self-reported measures (ie, Insomnia Severity Index, consensus sleep diaries, UCLA Loneliness Scale, Kessler Psychological Distress Scale, Post-Traumatic Checklist, perceived health threat, and International Physical Activity Questionnaire) and provided sociodemographic data at 4 timepoints. Using the Insomnia Severity Index score at each timepoint, group-based trajectory modeling was conducted to identify groups with distinct insomnia trajectories. ResultsOn average, there was no significant change in insomnia symptoms over time. Three groups with distinct sleep trajectories were identified: clinical (11.8%), subthreshold (25.3%), and good sleepers (62.9%). Older adults who were younger, male, had elevated psychological distress and posttraumatic stress disorder symptoms, perceived more SARS-CoV-2 health threat, spent more time in bed, and had shorter sleep duration during the first wave of the pandemic were more likely to belong to the clinical than to the good sleepers group. Those who were younger, female, had elevated psychological distress and PTSD symptoms, greater loneliness, spent more time in bed, and had reduced sleep duration during the first wave were more likely to belong to the subthreshold than to the good sleepers group. ConclusionsOver 1 in 3 older adults experienced persistent subthreshold or clinically significant insomnia symptoms. Both sleep-related behaviors as well as general and COVID-19-related psychological factors were associated with insomnia trajectories.

Sleep structure and related clinical characteristics in drug-naïve Parkinson's disease with subjectively different sleep quality.

Sleep disturbance is a common non-motor symptom of Parkinson's disease (PD). Most polysomnography (PSG) studies are conducted when patients are in their "on medication" state. Our study aimed to investigate changes in the sleep structure in drug-naive PD patients with poor subjective sleep quality based on polysomnography (PSG) and to explore potential correlations between sleep structure and clinical features of the disease. A total of 44 drug-naive PD patients were included. All patients completed a standardized questionnaire to obtain demographic and clinical characteristics and underwent whole-night PSG recording. Patients with PSQI scores >5.5 were considered poor sleepers, and patients with PSQI scores <5.5 were considered to be good sleepers. There were 24 (54.5%) PD patients in the good sleeper group and 20 (24.5%) PD patients in the poor sleeper group. We observed that poor sleepers had severe non-motor symptoms (NMS) and worse life quality. The PSG displayed that they had a longer wake-up time after sleep onset (WASO) and lower sleep efficiency (SE). Correlation analysis revealed that the micro-arousal index was positively associated with UPDRS-III, and the N1 sleep percentage was negatively associated with the NMS score in good sleepers. For poor sleepers, rapid eye movement (REM) sleep percentage was negatively related to the Hoehn-Yahr (H-Y) stage, WASO increased with UPDRS-III, periodic limb movement index (PLMI) increased with the NMS score, and N2 sleep percentage was negatively related to the score of life quality. Night awakening is the main manifestation of decreased sleep quality in drug-naive PD patients. Poor sleepers have severe non-motor symptoms and poor life quality. Additionally, the increase in nocturnal arousal events may predict the progression of motor dysfunction.

The Influence of Sleep Quality on the Body Composition, Selective Attention, and Autonomic Nervous System Activity in Healthy Individuals

Objective: This study aimed to investigate whether the sleep quality is associated with body composition, selective attention, and autonomic nervous system (ANS) activity in healthy young individuals.Methods: This cross-sectional study was conducted using the Korean version of Pittsburgh Sleep Quality Index (PSQI-K). Sixteen healthy volunteers aged 20–26 years participated in this study. The PSQI-K was used to evaluate sleep quality, and they were divided into good and poor sleeper groups by PSQI-K. Body composition, and both reaction time and error number for discriminative reaction task indicating the selective attention, and ANS activity were measured and it compared according to sleep quality. Additionally, the correlation between sleep quality and ANS activity was analyzed.Results: There were no significant differences in the body composition, reaction time and error number between good and poor sleeper groups. In the ANS activity, the poor sleeper group only showed the lower HF value than the good sleeper group in resting state (p=0.023). Whereas, the amount of change (reaction task state – resting state) in mean HR (p=0.005), HF (p=0.039), and LF/HF ratio (p=0.023) were significantly different between the groups. Additionally, a negative correlation was observed between PSQI-K and HF (p=0.005), while a positive correlation was confirmed between PSQIK and LF/HF ratio (p=0.012).Conclusion: These findings indicate that even healthy individuals may have physiological problems such as ANS imbalance if the sleep quality is poor.

Trajectories of sleep disturbance in cancer survivors during the first 2 years post-treatment.

To examine the trajectories of sleep disturbance in cancer survivors during the first 2 years post-treatment and to investigate whether psychological, cognitive, and physical factors differentiate trajectories. A total of 623 Chinese cancer survivors of diverse cancer types participated in a 2-year-long prospective study after the completion of cancer treatment. Sleep disturbance was measured using Pittsburgh Sleep Quality Index at 3 (T2), 6 (T3), 12 (T4), 18 (T5), and 24 (T6) months after baseline (within 6-months post-treatment; T1). Latent growth mixture modeling identified distinctive sleep disturbance trajectories and tested if these longitudinal patterns were predicted by baseline psychological distress, attentional control, attentional bias and physical symptom distress and T2 cancer-related distress. Fully adjusted multinomial logistic regression then identified whether these factors differentiated trajectories. Two distinct sleep disturbance trajectories were identified, namely stable good sleepers (69.7%) and persistent high sleep disturbance (30.3%). Compared to those in the stable good sleep group, patients in the persistent high sleep disturbance group were less likely to report avoidant (OR=0.49, 95% CI = 0.26-0.90), while more likely to report intrusive thoughts (OR = 1.76, 95% CI = 1.06-2.92) and cancer-related hyperarousal (OR = 3.37, 95% CI = 1.78-6.38). Higher depression scores also predicted persistent high sleep disturbance group membership (OR = 1.13, 95% CI = 1.03-1.25). Attentional bias, attentional control, anxiety, and physical symptom distress did not predict sleep trajectory membership. One in three cancer survivors experienced persistent high sleep disturbance. Screening and managing depressive symptoms and cancer-related distress in early cancer rehabilitation may reduce risk of persistent sleep disturbance among cancer survivors.

Differences in Gray Matter Volume in Cerebral Small Vessel Disease Patients with and without Sleep Disturbance.

Recently, there has been increased interest in the relationship between cerebral small vessel disease (CSVD) and circadian rhythm disruption, particularly sleep disturbance. However, the neural mechanism of sleep disturbance in CSVD patients remains poorly understood. The purpose of this study is to explore the gray matter alterations in CSVD patients with and without sleep disturbance. 59 patients with CSVD and 40 healthy controls (HC) were recruited for the present study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. CSVD patients were categorized into either the good sleepers group (CSVD-GS, n = 23) or the poor sleepers group (CSVD-PS, n = 36) based on PSQI score. Voxel-based morphometry (VBM) analysis was used to assess differences in gray matter volume (GMV) between groups. Multivariate regression analyses were performed to investigate the relationships between sleep quality, GMV, and white matter hyperintensities (WMH). We observed GMV differences between the three groups in the bilateral caudate, right thalamus, bilateral calcarine cortex, left precentral gyrus, right orbitofrontal cortex, left cingulate gyrus, and right sub-gyral temporal lobe. Additionally, the CSVD-PS group exhibited decreased GMV in the bilateral calcarine cortex yet increased GMV in the right caudate compared to the CSVD-GS group. In fully adjusted models, GMV of the right caudate and bilateral calcarine cortex was associated with sleep quality in CSVD patients. The present study revealed structural brain alterations in CSVD patients with sleep disturbance. These findings may provide novel insights into the neural mechanisms of sleep disturbance in CSVD.

Sleep quality evaluation, correlation with headache frequency, and propensity to conversion from episodic to chronic daily headache in migraine patients: A cross-sectional study.

The aim of the study was to determine the association between sleep quality with headache frequency in migraine patients and also to evaluate migraine trigger and non-headache symptoms in episodic and chronic migraine groups and evaluation of the same in poor and good sleepers (GSs) in migraine population. In a cross-sectional and observational study in a tertiary care hospital of East India between January 2018 and September 2020, migraine patients were evaluated. Migraine patients were divided into two groups: Episodic migraine (EM) and chronic migraine (CM) group according to ICHD 3 b classification and into poor sleepers (PSs, Global Pittsburgh Sleep Quality Index [PSQI] >5) and GSs (Global PSQI ≤5). Sleep was evaluated using PQSI - a self-rated questionnaire and disease pattern, associated non-headache symptoms, and triggers were evaluated in between groups. Demographic, headache character, and sleep parameters including seven "component" scores: Subjective sleep quality, sleep latency, sleeps duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction and global PQSI were compared between groups (EM and CM). Similar parameters were also compared between PSs and GSs group. Statistical analysis was performed using the χ2 test for categorical variables and the t-test and Wilcoxon rank-sum test for continuous variables. Correlation between two normally distributed numerical was tested by Pearson correlation coefficient assessment. One hundred migraine patients were analyzed, among which 57 were PSs and 43 were GSs and 51 patients had EM and 49 patients had CM. Moderately significant "r" value noted in between headache frequency and global PQSI score (r = 0.45, P < 0.01). In non-headache symptoms, blurring of vision (EM 8 [16%] and CM 16 [33%] P = 0.05), nasal congestion (EM - 3 [6%] and CM - 12 [24%], P = 0.01), and cervical muscle tenderness (EM- 23 [45%] and CM - 34 [69%], P = 0.01) were more prevalent in chronic headache group along with allodynia (EM - 11 [22%] and CM - 25 [51%], P < 0.01). Chronic headache group had poor subjective sleep quality, increased sleep latency, decreased sleep duration, decreased sleep efficiency, and increased sleep disturbance in comparison to episodic group which has therapeutic implication. The non-headache symptoms which are more prevalent in CM patients increase the overall disability.

Exercise Training Program Improves Subjective Sleep Quality and Physical Fitness in Severely Obese Bad Sleepers.

Sleep quality is an important modulator of neuroendocrine function, as sleep problems are related to metabolic and endocrine alterations. The main objective was to determine the effects of an exercise training program on the sleep quality of severely obese patients with sleep problems. The secondary objective was to determine the relationship between fitness and anthropometric parameters with sleep quality scores. Thirty severely obese patients participated in 16 weeks of PA intervention (age: 39.30 ± 11.62 y, BMI: 42.75 ± 5.27 kg/m2). Subjective sleep quality, anthropometric parameters, and fitness (i.e., handgrip strength and cardiorespiratory fitness) were measured. Two groups were defined as good sleepers (n = 15, 38.06 ± 12.26, men = 1) and bad sleepers (n = 15, 40.53 ± 11.23, men = 3). The good sleeper group reported improvement in cardiorespiratory fitness (61.33 ± 68.75 m vs. 635.33 ± 98.91 m, p = 0.003) and handgrip strength (29.63 ± 9.29 kg vs. 31.86 ± 7.17 kg, p = 0.049). The bad sleeper group improved their cardiorespiratory fitness (472.66 ± 99.7 m vs. 611.33 ± 148.75 m, p = 0.001). In terms of sleep quality dimensions, the bad sleeper group improved their subjective sleep quality (p < 0.001), sleep latency (p = 0.045), sleep duration (p = 0.031), and habitual sleep efficiency (p = 0.015). Comparing the changes in both groups (∆), there were differences in subjective sleep quality scores (∆ = 2.23 vs. ∆ = -3.90, p = 0.002), where 86.6% of the bad sleeper group improved sleep quality (p = 0.030). An increase in handgrip strength was correlated to improving sleep quality scores (r = -0.49, p = 0.050). Severely obese bad sleepers improved their subjective sleep quality, the components of sleep, and cardiorespiratory fitness through an exercise training program. Improvement in subjective sleep quality was linked to an increase in handgrip strength.

A DIFFERENCE IN INCIDENCE OF VISUAL THREATENING DIABETIC RETINOPATHY BETWEEN PATIENTS WITH AND WITHOUT IMPAIRED SLEEP QUALITY

Background: Diabetic retinopathy (DR) is a common and major complication of diabetes mellitus (DM), and is the leading cause of preventable blindness in adults of productive age after cataracts. The global prevalence of DR is 34.6% , consisting of proliferative diabetic retinopathy (7.0%), diabetic macular edema (6.8%), and visual threatening diabetic retinopathy (VTDR) (10.2%.) The risk factors for VTDR are age, duration of diabetes, glycemic control, hypertension, obesity, HbAIC levels, and dyslipidemia. In addition, impaired sleep quality is also indicated to be connected with the incidence of VTDR.&#x0D; Objective: To compare the incidence of VTDR between patients with and without impaired sleep quality.&#x0D; Methods: This was a cross-sectional comparative analytic observational study involving 178 type 2 diabetes mellitus patients with DR at the National Eye Center of Cicendo Eye Hospital who met the inclusion criteria. Subject characteristic data were taken from medical records and sleep quality data were collected through a structured interview using the Indonesian version of the Shorten Pittsburgh Sleep Quality Index (PSQI) questionnaire. Subjects were distributed into poor and good sleep quality groups. The presence of VTDR was then assessed. The differences were then analyzed statistically using chi-square test with a p value of 0.05 considered statistically significant.Results: Results showed that 66.2% and 71.1% of patients in the poor and good quality sleep group suffered from VTDR, respectively (p&gt; 0.05).&#x0D; Conclusion: There is no difference in VTDR incidence between patients in productive age with type 2 DM between those with and without impaired sleep quality.&#x0D;

Association between thyroid function and disease severity in restless legs syndrome.

BackgroundRestless Legs Syndrome (RLS) is a common neurological disorder. Growing evidence shows that dopaminergic dysfunction and iron deficiency are associated with the pathogenesis of RLS. Additionally, the dopaminergic system is linked with the hypothalamic-pituitary-thyroid (HPT) axis. Thus, the current study aimed to compare thyroid function between RLS patients and healthy subjects and investigate the associations with clinical characteristics of RLS.MethodsSerum levels of thyroid hormones were investigated in 102 first-episode drug-naïve RLS patients and 80 matched healthy controls (HCs). Baseline data and clinical characteristics were performed by professional personnel. In addition, multivariate regression was used to analyze the relationship between thyroid function and RLS.ResultsCompared with control group, RLS patients had significantly higher serum thyroid-stimulating hormone (TSH) levels (p < 0.001), and higher prevalence of subclinical hypothyroidism [Odds ratio (OR) 8.00; 95% confidence interval (CI) = 3.50–18.30; p < 0.001]. The Subclinical hypothyroidism rate (47.1 vs. 10%, p < 0.001) in RLS patients was higher than the HCs group. Regression analysis revealed that serum TSH (OR = 1.77; 95% CI = 1.41–2.23; p < 0.001) was independently associated with RLS. There was a statistically significant positive correlation between TSH and the Pittsburgh sleep quality index (PSQI) scores (r = 0.728, p < 0.001), and the International Restless Legs Scales (IRLS) points (r = 0.627, p < 0.001). Spearman correlation analysis showed that FT3 was positive correlated with HAMA14 score (r = 0.239, p = 0.015). In addition, compared with the good-sleeper group, poor-sleeper patients had significantly higher serum TSH levels (p < 0.001).ConclusionSerum levels of TSH and the prevalence of subclinical hypothyroidism were higher in RLS patients, indicating the imbalance between thyroid hormones (TH) and the dopaminergic system may contribute to the development of primary RLS. Additionally, the TH axis may influence the quality of sleep in RLS patients.

Visual Attention and Poor Sleep Quality.

BackgroundSleep deprivation disrupts visual attention; however, the effects of chronic poor sleep quality on it are not understood. The dorsal attention network (DAN) and the ventral attention network (VAN) are involved in visual attention and search (VSA), with the DAN being important for the serial attention network and the VAN for parallel “pop-out” visual search.ObjectiveThe aim of the study was to evaluate correlation of sleep quality with visual attention and search, functional, and tracts’ properties of the DAN and VAN.Materials and MethodsWe recruited 79 young male subjects and assessed their sleep quality using the Pittsburgh Sleep Quality Index (PSQI), dividing subjects into poor sleepers (PSs) and good sleepers (GSs) based on a cutoff of 5. Daytime sleepiness, sleep hygiene, depression, and anxiety levels were also evaluated. We assessed VSA using a computerized match-to-sample (MTS) task. We extracted functional networks and tracts of the VAN and DAN and statistically assessed group differences in task performance and imaging covarying age, depression, and anxiety. An interaction model with MTS × group was also done on imaging.ResultsIn total, 43.67% of subjects were PSs. Sleep quality significantly correlated with daytime sleepiness, sleep hygiene, depression, and anxiety (all p < 0.001). No between-group differences were seen in task performance and functional or tract properties of the attention networks. Interaction analysis showed that the task performance was highly reliant on the DAN in PSs and on the VAN in GSs.ConclusionOur findings show no association between sleep quality and VSA in task performance and imaging correlates of the attention network. However, unlike the GS group, poor sleep quality is associated with VSA being more reliant on the DAN than on the VAN.

0601 Predicting Incident Outcomes from the Microstructure of Sleep

Abstract Introduction Sleep contains rich information about health status, relevant to future health outcomes including dementia, cerebrocardiovascular diseases, psychiatric diseases, and mortality. We hypothesized that the risk of these outcomes is predictable from quantitative analysis of sleep microstructure. Methods We included participants who underwent a diagnostic study and age older than 18 years. We excluded participants with missing demographics or PSGs &amp;lt; 2.5 hours in duration. We considered 11 outcomes including dementia, mild cognitive impairment or dementia, ischemic stroke, intracranial hemorrhage, atrial fibrillation, myocardial infarction, type 2 diabetes, hypertension, bipolar disorder, depression, and mortality. The outcomes were determined using ICD codes, brain imaging reports, medications, and/or cognition scores. We extracted 86 spectral and time-domains features from overnight sleep EEG recordings, including 57 features from NREM sleep epochs, 21 from REM, and 8 covariates including age, sex, body mass index, and medication prescriptions including benzodiazepines, antidepressants, sedatives, antiseizure medications, and stimulants. We modeled risk using Cox survival analysis with death as a competing risk. Model calibration was assessed using the difference in 10-year cumulative incidence (10y-CI) between Cox estimate vs. Aalon-Johansen estimate (ground truth). Results There were 8673 participants with an average age of 51 years; 51% were female. Participants were partitioned into three groups: poor sleep (hazard &amp;gt; 3rd quartile (Q3)), average sleep (Q1 ≤ hazard ≤ Q3), and good sleep (hazard &amp;lt; Q1). The model was able to predict the 10y-CI not significantly different from the ground truth, except for the risk of intracranial hemorrhage in the poor sleep group. The outcome-wise mean prediction difference in 10y-CI was 2.3% for the poor sleep group, 0.5% for the average sleep group, and 1.3% for the good sleep group. The outcomes with the top three poor-to-average risk ratios (RR) were dementia (RR = 6.2 95% confidence interval [4.5 – 9.3]), mortality (RR = 5.7 [5.0 – 7.5]), and MCI or dementia (RR = 4.0 [3.2 – 4.9]). Conclusion Sleep EEGs contain decodable information about the risk for future incidence of mortality, dementia, cerebrocardiovascular and psychiatric diseases. The findings strengthen the concept of sleep as a window into brain and general health. Support (If Any) This work is supported by the AASM Foundation 2019 Strategic Research Award.

Men's Sleep Quality and Assisted Reproductive Technology Outcomes in Couples Referred to a Fertility Clinic: A Chinese Cohort Study.

BackgroundPoor sleep quality has been linked to lower semen quality, but it is unclear whether this result in decreased fertility. To address this question, we retrospectively evaluated the relationship between men’s sleep quality and treatment outcomes in subfertile couples receiving assisted reproductive technology (ART).Patient Enrollment and MethodsFrom September 2017 to November 2019, 282 subfertile couples referred to a Chinese fertility clinic and eligible for ART procedures were enrolled in our study. Sociodemographic characteristics, life habits, and sleep habits in the year prior to ART were recorded. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). We first divided the patients into two groups based on sleep quality (good sleep: PSQI < 5 and poor sleep: PSQI ≥ 5). Then, the ART outcomes (fertilization rate, good quality embryo rate, implantation rate, positive pregnancy rate, clinical pregnancy rate, live birth rate, miscarriage rate, and birth weight) of each group were analyzed. Finally, multivariate linear and logistic regression analysis were used to examine the relationship between sleep quality (discrete variable or dichotomous variable) and ART outcomes.ResultsThe participants in the poor sleep group showed a lower fertilization rate of 60.13% (543/903) when compared with 67.36% for the good sleep group (902/1339), P < 0.001. The global PSQI score had a significant influence on birth weight (β, −63.81; 95% CI, −119.91- −8.52; P = 0.047), and live birth rate (OR, 0.88; 95% CI, 0.78- 0.99; P = 0.047) after adjusting for the interfering factors. Men’s sleep quality was unrelated to good quality embryos rate, implantation rate, positive pregnancy rate, clinical pregnancy rate, or miscarriage rate.ConclusionMen’s sleep quality was positively associated with fertilization rate, birth weight, and live birth rate among couples undergoing ART.

COVID-19 pandemic: depression and sleep quality in hemodialysis patients

Introduction: Depression and sleep disturbance are prevalent comorbidities in hemodialysis patients. This study aimed to investigate the relationship between depressive mood, sleep disturbance, and the fear of COVID-19 Scale in hemodialysis patients during the pandemic process.&#x0D; Material and Method: 116 hemodialysis patients followed up in our clinic and volunteered were included in the study. The socio-demographic characteristics of the patients and the laboratory test results studied in their routine follow-ups were obtained from the file records. Beck Depression Inventory (BDI), Pittsburgh Sleep Quality Index (PSQI), and the Fear of COVID-19 Scale (FCV-19S) were applied through face-to-face interviews.&#x0D; Results: 116 patients (70 males, 46 females) with a hemodialysis duration of 40 months (13-295) and age of 60.2±13.3 years were included in the study. The patients were divided into two groups according to their PSQI score as good sleeper (PSQI ≤ 5, n=66) and poor sleeper (PSQI &gt;5, n=50). When evaluated by gender 28 (56%) female patients were in the poor sleeper group (p=0.002). Dialysis time was longer, BDI score and FCV-19 scale were higher in the poor sleeper group than the good sleeper group. PSQI score was positively correlated with dialysis time (r=0.259 p=0.005), BDI score (r=0.279 p=0.002), and FCV-19 scale (r=0.304 p=0.001). In the Multiple Logistic Regression analysis established to evaluate the risk factors affecting sleep quality, BDI was determined as an independent risk factor for poor sleep (OR: 1.084, 95%CI [1.021-1.152], p=0.008). Subjects were divided into two groups according to their BDI scores as those with depressive mood (BDI score ≥ 17, n=47) (40.5%) and those without (BDI score &lt; 17, n=69) (59.5%). Thirty-two of the cases with depressive mood were women (68.1%) (p

Psychometric properties of the Turkish version of the Anxiety and Preoccupation about Sleep Questionnaire in clinical and non-clinical samples.

ObjectivesThe aim of the study was to investigate the psychometric properties of the Turkish version of Anxiety and preoccupation about sleep questionnaire (APSQ) in clinical and non-clinical samples.Material and MethodsTwo samples (141 university students and 42 patients with major depressive disorders) completed Turkish APSQ, the Pittsburgh sleep quality index (PSQI), the insomnia severity index (ISI) and the sociodemographic data form. Content validity analysis was performed with the Davis technique after the translation process of the original scale. Explanatory factor analysis and principal component analysis were performed to determine the scales construct validity, and internal consistency and temporal stability analyses were conducted to evaluate its reliability. The PSQI and the insomnia severity index (ISI) were used to assess criterion- related validity. In addition, we divided all the participants into two groups as good-sleepers and clinical insomnia according to ISI scores. Predictive validity analyses were also computed via comparing groups.ResultsConfirmatory factor analysis showed that the scale model aligns well with the original scales 10 items and two-factor structure. The scales and subdimensions Cronbach’s alpha coefficients were excellent (Factor 1; 0.935, factor 2; 0.906, total scale; 0.952). The test-retest correlations were 0.661 and 0.828 for depression group and university student group, respectively. Turkish APSQ scores were found to be significantly higher in both of the clinical groups (depression group vs. university student group, clinic insomnia group vs. good-sleepers group).ConclusionThe Turkish APSQ is adequate reliability and validity for assessing anxiety and preoccupation about sleep in Turkish clinical and non-clinical samples.

Sleep EEG characteristics associated with total sleep time misperception in young adults: an exploratory study

BackgroundPower spectral analysis (PSA) is one of the most commonly-used EEG markers of cortical hyperarousal, and can help to understand subjective–objective sleep discrepancy (SOD). Age is associated with decreased sleep EEG activity; however, the PSA of young adults is currently limited. Thus, this study aimed to examine the correlation of spectral EEG power with total sleep time (TST) misperception in young patients.MethodsForty-seven young adults were recruited and underwent a polysomnography recording in a sleep laboratory. Clinical records and self-report questionnaires of all patients were collected, and were used to categorize patients into a good sleeper (GS) group (n = 10), insomnia with a low mismatch group (IWLM, n = 19) or participant with a high mismatch group (IWHM, n = 18). PSA was applied to the first 6 h of sleep.ResultsIWHM patients exhibited a higher absolute power and relative beta/delta ratio in the frontal region compared to the GS group. No significant difference was observed between the IWLM and GS groups. No significant difference in the above parameters was observed between the IWHM and IWLM groups. Moreover, The SOD of TST was positively correlated with frontal absolute power and the relative beta/delta ratio (r = 0.363, P = 0.012; r = 0.363, P = 0.012), and absolute beta EEG spectral power (r = 0.313, P = 0.032) as well as the number of arousals.ConclusionsIncreased frontal beta/delta ratio EEG power was found in young patients with a high mismatch but not in those with a low mismatch, compared with good sleepers. This suggests that there exists increased cortical activity in IWHM patients. In addition, the frontal beta/delta ratio and the number of arousals was positively correlated with the SOD of TST.