PQSI Scores Research Articles

Anxiety and depression among patients with insomnia during the first wave and the release of the COVID-19 in Northeast China: A cross-sectional survey

BackgroundThe global coronavirus disease 2019 (COVID-19) pandemic seriously affected people's lives. We evaluated anxiety and depression among patients with insomnia in northeast China during the first wave and release of COVID-19, providing a basis for the clinical diagnosis and treatment of insomnia. MethodsWe enrolled 4211 patients with insomnia from January 2016 to February 2020, August 2020 to February 2022, August 2022 to December 2022, and January 2023 to February 2023, from our institution. Sleep quality was evaluated using the Athens Insomnia Scale, Insomnia Severity Index (ISI), and Pittsburgh sleep quality index (PSQI), while mood disorder and fatigue were evaluated using the Hhospital anxiety and depression scale (HAD), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Fatigue Scale-14 (FS-14). ResultsInsomnia with depression increased in prevalence after COVID-19 compared with before (12.8 % vs. 15.3 %, P < 0.05), while the age of patients decreased [(50.2 ± 15.2) vs. (47.5 ± 16.8), P < 0.05]. The number of patients with insomnia and severe depression increased compared with before COVID-19 (20.3 % vs. 25.3 %, P < 0.05). A higher proportion of patients with insomnia for >2 years had depression (P < 0.05). As the epidemic subsided, insomnia increased among young and male patients (young patients: 55.2 % vs. 37.0 %; male patients: 41 % vs. 27.4 %, respectively; P < 0.05). The proportion of patients with insomnia with anxiety and depression increased (53.8 % vs. 51.8 %，P < 0.05), the proportion with moderate to severe anxiety increased (7.6 % vs. 13.5 %, P < 0.05), and moderate and severe depression decreased (moderate: 25.6 % vs. 19.1 %, severe: 25.8 % vs. 20.3 %, P < 0.05, respectively). Middle-aged and elderly patients had higher PQSI scores in sleep latency, habitual sleep efficiency, subjective sleep quality, and use of sleep medications than young patients (P < 0.05). The PSQI score was positively correlated with the PHQ-9 score (r = 0.526), GAD-7 score (r = 0.563), and FS-14 score (r = 0.316) (P < 0.05). LimitationsThe study was single-center, the sample size was small, and assessment data were lacking from early in the epidemic. The scale is subjective, which may affect the accuracy. ConclusionInsomnia with depression increased during COVID-19. The patients were younger than before the epidemic, and a higher proportion with insomnia for >2 years had depression. The proportion of patients with insomnia with anxiety and depression was higher after the epidemic period, and the degree worsened. The proportion of insomnia with depression decreased after the epidemic period, and the degree alleviated. The proportion of young male patients with insomnia increased. Middle aged and elderly patients with insomnia had poor sleep quality, which was positively correlated with anxiety, depression, and fatigue.

Post-Operative Poor Sleep Quality and Its Associated Factors Among Non-Small Cell Lung Cancer Patients: A Cross-Sectional Study.

The study aimed to determine the post-operative prevalence and factors associated to poor sleep quality in non-small cell lung cancer (NSCLC) patients in China. NSCLC patients (n=307) who underwent thoracoscopic surgery at the Department of Thoracic Surgery of Shanghai Pulmonary Hospital were enrolled in this study. The Pittsburgh Sleep Quality Index (PSQI), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Prince Henry Hospital Pain Score and the Six-Minute Walk Test (6MWT), and Forced Expiratory Volume in one second (FEV-1) were used to assess the factors that could lead to poor sleep quality. All assessments were carried out between April 1 and May 30, 2023. Descriptive analyses and stepwise factor regression were employed to determine the impact of various factors on sleep quality. The factors predictive of poor sleep quality were used to develop a predictive nomogram. The Hosmer-Lemeshow test was used to assess the predictive value of the nomogram. The median PQSI score was 8 (interquartile range (IQR) 5-12), and 74.6% of patients had poor sleep quality. The median anxiety and depression scores were 6 (IQR 3-9) and 4 (IQR 2-7), respectively. The PSQI latency dimension had the highest score, while the use of sleep medications dimension had the lowest score. The multivariate analysis revealed that patients who were female (OR, 2.38; 95% CI, 1.40-4.05; P <0.01), had post-secondary education (OR, 0.42; 95% CI, 0.19-0.92; P =0.03), tertiary education (OR, 0.38; 95% CI, 0.17-0.84; P =0.02), comorbidities (OR, 2.57; 95% CI, 1.51-4.39; P <0.01), a pain score 1 (OR, 4.22; 95% CI, 2.37-7.50; P <0.01), and cough (OR, 2.97; 95% CI, 1.63-5.40; P <.001) were more like to experience poor sleep quality. The positive predictive value of the nomogram was 79.80% (p=0.390). Sociodemographic variables, comorbidities, and pain could be used to predict the post-operative sleep quality in NSCLC patients.

SLEEP QUALITY ASSESSMENT IN ADOLESCENTS WITH TYPE 1 DIABETES MELLITUS

Background and Aims: Diabetes has been reported to be a risk factor for sleep disturbances in adolescent age groups. Although the impact of type1 diabetes mellitus (T1DM) on sleep patterns of children is well recognized, data about its prevalence is scant. This study aims to determine the quality of sleep among adolescents with T1DM and factors inuencing it. Methods: This is a cross-sectional study collected data from 30 adolescent diagnosed with T1DM at least 6 months earlier. They presented to Paediatric endocrine OPD from May 2021 to May 2022. Subjects were asked to complete the Pittsburgh Sleep Quality Index (PSQI) 19-item self-report questionnaire. Children with T1DM being under treatment for sleep disorder were excluded. The combined score of the 7 components (subjective sleep quality, sleep latency, sleep duration, habitual sleep efciency, sleep disturbances, use of sleeping medication, and daytime dysfunction) was used for analysis and the score ranged from 0 to 21. Atotal score &gt;5 was considered as “poor sleep quality”. The quality of sleep was correlated with drug, dietary compliance and metabolic control. p-value &lt;0.05 was considered signicant. Results: The mean age of study population was 14.3±1.7 years. 18 were boys and 12 were girls. Total 8 patients showed poor sleep quality (PQSI score &gt;5). No signicant relationship was found between sleep quality, duration of diabetes and HbA1c levels in the diabetes group (P= 0.59, P= 0.41, respectively). The total sleep time of boys (8.4 ± 1.2 h) was longer than girls (7.6 ± 1.7 h), but the overall total sleep time per night did not differ signicantly between boys and girls (P= 0.053). Conclusion: The present study shows that diabetes control may affect sleep quality in adolescents. Optimal diabetes management can positively affect sleep patterns in these adolescents. Further larger studies are needed to validate our results

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.

Factors associated with poor sleep quality in midlife Singaporean women: The Integrated Women’s Health program (IWHP)

ObjectiveTo examine factors associated with poor sleep quality in community-dwelling midlife women. MethodsHealthy women (aged 45–69 years) of Chinese, Malay and Indian ethnicities attending well-women clinics at the National University Hospital, Singapore, completed the Pittsburgh Sleep Quality Index (PSQI). A PQSI score >5 denoted poor sleep quality. The women filled out validated questionnaires covering menopausal and genito-urinary symptoms, and mental health. Physical performance was measured. Bone mineral density and visceral adiposity were assessed by dual energy X-ray absorptiometry. Binary logistic regression analyses assessed independent factors for poor sleep. ResultsPoor sleep quality was reported in 38.2% of women (n = 1094, mean age: 56.4 ± 6.2 years). Indian women had higher sleep disturbance scores than Chinese women (mean ± SD: 1.33 ± 0.58 vs 1.17 ± 0.49). Malays experienced more daytime dysfunction (0.54 ± 0.60 vs 0.33 ± 0.55) and had a higher overall PSQI score (6.00 ± 3.31 vs 5.02 ± 2.97) than the Chinese. A low education level (aOR: 1.76, 95% CI: 1.01–3.05), feelings of irritability (2.67, 1.56–4.60) and vaginal dryness (1.62, 1.03–2.54) were associated with poor sleep quality in the adjusted multivariable model. Women with moderate to severe disability were ∼3 times (2.99, 1.20–7.44) more likely to experience less than ideal sleep quality, while urinary incontinence (1.53, 1.08–2.17) and breast cancer history (2.77, 1.36–5.64) were also associates of poor sleep quality. ConclusionSelf-reports of education level, irritability, vaginal dryness, disability, urinary incontinence, and breast cancer history were independently related to poor sleep. Ethnic differences suggest the need for targeted interventions among the ethnic groups.

Comparison of factor structures of the Pittsburgh sleep quality index between mid- and late pregnancy among Korean women: a cross-sectional study

BackgroundSleep disturbance in pregnant women needs to be accurately assessed in a timely manner during pregnancy, to receive assessment-driven accurate intervention. This study aims to compare the factor structure of the Pittsburgh Sleep Quality Index (PSQI) among women in mid- and late pregnancy and evaluate the psychometric features of the Korean version of the PSQI.MethodsThe survey questionnaire with the PSQI, Center for Epidemiological Studies Depression scale, and pregnancy stress, was completed by 281 women in mid- or late pregnancy. Exploratory factor analysis determined the best factor structure of the PSQI, and the Pearson correlation coefficient examined a convergent validity with depressive symptoms and pregnancy stress. Internal consistency was examined using Cronbach’s alpha.ResultsIn both mid- and late-pregnancy women, a two-factor structure model was identified. However, each factor’s different components were named differently. For women in mid-pregnancy, it was named “quantitative sleep quality” and “subjective sleep quality,” and for those in later stages of pregnancy, they were named “perceived sleep quality” and “daily disturbance.” The PQSI score showed a significantly positive correlation between depressive symptoms and pregnancy stress in mid- (r = 0.57 and r = 0.39, respectively), and late pregnancy (r = 0.48 and 0.28, respectively). The overall Cronbach’s alpha for the PSQI was 0.63.ConclusionsThe Korean version of the PSQI demonstrated excellent construct and convergent validity, making it suitable to assess the sleep quality of women in middle to late stages of their pregnancy. The PSQI was found to have a two-factor structure in the mid-and late pregnancy, but the components were different. As sleep quality changes with each gestational stage, factors affecting it during mid- and late pregnancy need to be separately examined. It will make it easier for medical professionals to provide pregnant women sleeping irregularly, with the right kind of intervention.

0374 A sleep health educational module for social work students is associated with improvements in sleep knowledge and sleep quality

Abstract Introduction Insufficient sleep is highly prevalent, particularly among underserved groups. Social workers often work with underserved populations who are at risk for sleep deprivation and are well-positioned to promote healthy sleep behaviors. However, sleep health training is rarely integrated into social work curriculums. To address this gap, we developed and tested a 2-hour online sleep health educational intervention, designed to improve sleep-related knowledge among social work students. Methods We recruited 106 social work students via a departmental listserve to participate in a 1-hour sleep education module. Pre-post module changes in knowledge and beliefs were assessed using the Sleep Beliefs Scale (SBS) and the Sleep Practices and Attitudes Questionnaire (SPAQ). We also assessed changes in self-reported sleep quality using the Pittsburgh Sleep Quality Index (PQSI). Wilcoxon Signed-Rank tests were used to assess pre- to post-module scores. We conducted qualitative research (open-ended questions and focus groups) to assess acceptability and to inform future module refinement. Results Of the 106 students participating in the module, mean age was 28.3±8.8 yrs, 92.5% were female, 4.7% male, and 2.8% other. The sample was racially/ethnically diverse with 37.7% identifying as non-Hispanic White, 34.0% African American/Black, 22.6% Hispanic/Latino, 0.9% Asian, and 4.7% other. Ninety (84.9%) participants completed the questionnaires. Demographics did not differ between students who completed the training and those who did not. Students participating in the module reported improvements in the Sleep Beliefs Scale (Median=2.0, range: -4, 10 [positive change=increased knowledge]), the SPAQ (Median=-10, range: -37, 95 [negative change=increased importance of sleep]), and the Global PQSI Score (Median=-1, range: -7, 4 [negative change = improved sleep quality]). Qualitative data supported the module’s acceptability and utility (e.g., “Not only will I adapt these healthy sleep habits, I will always ask my clients how they are sleeping!”). Suggestions for improvement included adding additional topics (e.g., over-the-counter sleep aids) and shortening the training duration. Conclusion Participation in an online educational module was associated with not only improvements in sleep knowledge but also self-reported sleep among social work students, suggesting feasible ways to expand providers promoting sleep health. Support (If Any) American Academy of Sleep Medicine Foundation

Efficacy of gabapentin for low back pain at a tertiary hospital

Objective: To assess the efficacy of gabapentin in the treatment of low back pain patients. Methods: This prospective observational study was conducted over 6 months to assess the efficacy of gabapentin in patients suffering from low back pain. Past medical history, pain severity by Visual Analogue scale (VAS) and sleep quality by Pittsburgh Sleep Quality Index (PQSI) were collected. VAS scores and PQSI scores before and after gabapentin treatment were compared, and gabapentin satisfaction post treatment were recorded. Results: This study included 100 low back pain patients with 65 males and 35 females, and the mean age was (39.0±10.5) years. The commonest presentation was non-radiating low back pain (40%). The mean VAS score and the mean PQSI score in the study before treatment were 7.70±1.91 and 10.95±5.02, respectively. After treatment with gabapentin, the mean VAS score and the mean PQSI score decreased to 2.75±1.79 and 4.90±2.20, respectively, and the differences before and after the treatment were significantly different (both P=0.001). Overall, 62% of the patients were extremely satisfied with gabapentin because they reported no adverse drug reaction. Besides, 31% of the patients were satisfied and 7%were strongly dissatisfied with the therapy. Conclusion: Gabapentin can improve sleep quality and reduce lower back pain as measured by the VAS and PQSI. The efficacy of this drug is relatively good, but further improvement is required.

Investigation of the role of sleep quality and sleep duration on fasting blood glucose level in acute ischemic stroke patients: A preliminary study.

The aim of this study was to evaluate the association between the sleep quality and sleep duration with the level of fasting blood glucose in patients with acute ischemic stroke. A cross-sectional study was conducted among acute ischemic stroke patients admitted to Dr. Soetomo Hospital and Universitas Airlangga Hospital from May to October 2021. Patients who met the inclusion were enrolled. To assess the sleep quality, Pittsburgh Sleeps Quality Index (PSQI) was applied. To determine sleep duration during the nocturnal period, Fitbit Charge 2 HR device was used. Evaluation of plausible confounders was assessed through physical examination, interviews, and a set of validated questionnaires. A total of 30 acute ischemic stroke patients were included in this study. The mean age of the participants was 56.40±9.77 years and 60% were males. There were 63.3% patients classified as mild stroke and 36.7% moderate-severe stroke. The average PQSI score was 5.57±2.59, while the average sleep duration was 319.8±108.7 minutes. The average fasting blood glucose level was 89.03±14.71 mg/dL. Significant positive correlation was obtained between sleep duration and fasting blood glucose level (r=0.533; p=0.002). Similarly, there was no statistically significant correlation between sleep quality with the level of fasting blood glucose (r=-0.167; p=0.377). To the best of our knowledge, this is the first study assessing the correlation between sleep quality and sleep duration with the level of fasting blood glucose levels in patients with acute ischemic stroke. This study therefore might be of great interest to provide insights on the importance of sleep management in acute ischemic stroke patients.

Assessment of Sleep Habits and Quality of Sleep among Elderly Residing in Rural Areas of Patiala: A Community-Based Cross-Sectional Survey

INTRODUCTION: Among the elderly, sleep problems are quite prevalent and can lead to many adverse health consequences. AIM: To assess the quality of sleep among the elderly residing in rural population and factors related to it, and provide necessary recommendations for its prevention. MATERIALS AND METHOD: In this cross-sectional study, elderly aged above 60 years residing in Patiala were taken and were interviewed separately using the modified version of the Pittsburgh Sleep Quality Index (PSQI), which was pre-tested and pre-validated prior to commencement of the study. Data recorded was divided into seven components and each component had an individual range of 0 (no difficulty) to 3 (severe difficulty) points and added to obtain a combined score of the individual with a range of 0(no difficulty)-21(severe difficulty) points. Based on the combined score, elderly obtaining a total score of 5 or greater was classified as having “poor sleep quality”. Statistics were applied using SPSS version 22.0, using the student’s t- test, and multivariate analysis. A p value &lt; 0.05 was considered as significant. RESULTS: Out of 108 elderly people, most of the participants (62.9%) belonged to the age group of 60-75 years, out of which the majority (65.7%) were males. Most elderly reported having “fairly good” subjective sleep quality (53.7%, p=0.01) and was found to be significant with a global PQSI score of 7.22±4.31. Multivariate analysis revealed that significant “poor sleep quality” was observed in elderly aged above 75 years (OR:1.25, p=0.01) followed by elderly who were Immobilized (wheelchair/Bed ridden) (OR: 1.87, p=0.01). CONCLUSION: Efforts should be directed towards proper education of not only the elderly, but their children as well as colleagues and guardians to improve the sleep score of the elderly population.

Smartphone Addiction and Quality of Sleep among Indian Medical Students

Background: Smartphone is an indispensable miracle of artificial intelligence in the hands of global netizens. Medical students overburdened and sleep-deprived due to the curricular demands can have serious health effects due to further sleep deprivation caused by problematic smartphone use, affecting their work proficiency as practicing physicians. This study aimed to evaluate the association of smartphone addiction and quality of sleep among medical students across all semesters, along with other background variables. Methodology: This cross-sectional study was conducted on 224 medical students of a tertiary care teaching hospital in North India using a self-administered questionnaire with four parts –Socio-demographic characteristics, General health questionnaire (GHQ-12), Smartphone addiction scale-short version (SAS-SV), and Pittsburgh sleep quality index (PSQI). Results: The prevalence of smartphone addiction is was found out to be 33.33% in females and 46.15% in males. In the study, 63.39% were poor sleepers as assessed by their PQSI scores, and 62.05% reported poor health status as per their GHQ scores. There was a positive correlation between overall PQSI scores and smartphone use duration per day, SAS-SV scores, and GHQ scores. Conclusion: The high prevalence of excessive smartphone usage among medical students is a cause for concern and is detrimental to their health and sleep quality. The research addresses current lacunae in correlating smartphone addiction with smartphone usage before sleeping and right after waking up. Risky behavior adoption and pervasive mood changes associated with excessive smartphone use are addressed with equal representation across semesters. The study recommends increasing self-awareness for help-seeking to regulate smartphone usage and providing counseling services for students in their formative years.

Study on the relationship between benign paroxysmal positional vertigo and sleep disturbance

Objective:To explore the relationship between benign paroxysmal positional vertigo （BPPV） and sleep disorders through the analysis of subjective and objective sleep conditions. Methods:Forty-five patients with BPPV and fifty controls who met the inclusion and exclusion criteria were selected for Pittsburgh sleep quality index （PSQI） questionnaire survey and polysomnography （PSG） check, and SPSS 23.0 was used to compare and analyze the results. Results:Compared with the control group, patients with BPPV had changes in sleep structure, high apnea hypopnea index （AHI） and significantly decreased subjective sleep quality （P<0.05）, and there were significant differences in the PQSI scores of patients with BPPV before and after treatment （P<0.05）.Binary logistic regression analysis of BPPV and AHI showed that for every 1 increase in AHI index, the probability of BPPV increased by 1.8 times （OR=2.80, 95%CI=2.25-3.66）.After grouping AHI and performing regression analysis, it was found that the risk of BPPV in patients with AHI≥5 was 3.94 times that of patients with AHI <5（OR=3.94，95%CI=1.63-9.48）. Conclusion:Patients with BPPV have decreased sleep quality and altered sleep structure, and in this study, AHI is found to be a risk indicator for BPPV.

Management of intractable pain in patients treated with hemorrhoidectomy for mixed hemorrhoids.

Post-hemorrhoidectomy pain is common, usually temporary, and responsive to analgesics. However, some patients experience prolonged, intractable anal pain, which is refractory to conventional analgesics and adversely effects quality of life. We aimed to evaluate the efficacy of a combination injection containing local anesthesia and steroids for the treatment of intractable post-hemorrhoidectomy anal pain. This study included five patients with intractable post-hemorrhoidectomy anal pain who presented between July 2015 and November 2018. Milligan-Morgan hemorrhoidectomy (M-M) with a sclerosant injection had been performed in three patients and stapled hemorrhoidectomy (SH) along with external hemorrhoidectomy in two. For the purpose of this study, all patients received local combination injections containing ropivacaine and triamcinolone acetonide. The primary outcome was the visual analogue scale (VAS) score, and secondary outcomes included the Pittsburgh Sleep Quality Index (PSQI) score, adverse reactions, and recurrence. Prior to treatment, the VAS score was 8 in one patient and 5-7 in four, and the PSQI score was ≥16 in all patients. The injection was administered once (n=4) or twice (n=1). Rapid pain resolution was achieved on the day of treatment (VAS scores 0-3), and patients reported undisturbed sleep the same night. VAS scores were 0-2 (n=4) and 1-3 (n=1), and the PQSI scores were 0-6 (n=4) and 11-15 (n=1) at the 6-month follow-up. No patient reported significant pain or adverse reaction. Intractable post-hemorrhoidectomy anal pain is rare but significantly effects quality of life. While conventional analgesia may be ineffective, the local injection of anti-inflammatory and analgesic drugs may be a useful treatment strategy.

Clinical Features and Correlates of Poor Nighttime Sleepiness in Patients with Parkinson's Disease.

Objective The present study investigated the clinical features and correlates of poor nighttime sleepiness (PNS) in patients with Parkinson's disease (PD). Methods One hundred ten patients with PD (divided into PD-PNS group and PD-nPNS group) and forty-seven controls (nPD-PNS group) were enrolled in this study. Demographic information was collected. Patients were assessed according to the unified Parkinson's disease rating scale (UPDRS) and Hoehn–Yahr (H&Y) stage scale. Patients were also evaluated according to the Pittsburgh sleep quality index (PSQI), Epworth sleepiness scale (ESS), rapid eye movement sleep behavior disorder screening questionnaire (RBD-SQ), restless leg syndrome (RLS) diagnosis, Hamilton's depression scale (HAMD), and Hamilton's anxiety scale (HAMA). Results The prevalence of PNS was 55.45% (61/110) in patients with PD. The PD-PNS group tended to have a longer duration of disease, higher UPDRS-I and UPDRS-III scores, a higher percentage of RLS patients, and higher HAMA and HAMD scores than those of the PD-nPNS group. The PD-PNS group tended to have a higher percentage of RBD and RLS patients and higher HAMA and HAMD scores than those of the nPD-PNS group. Analysis of the PSQI components and PSQI impact factors showed that the PD-PNS group had worse subjective sleep quality (χ2 = −2.267, P = 0.023), shorter sleep latency (χ2 = −2.262, P = 0.024), fewer sleep medications (χ2 = −4.170, P ≤ 0.001), worse daytime functioning (χ2 = −2.347, P = 0.019), and an even higher prevalence of increased nocturia (χ2 = 4.447, P = 0.035), nightmares (χ2 = 7.887, P = 0.005), and pain (χ2 = 9.604, P = 0.002) than those of the nPD-PNS group. Analysis also indicated that the PSQI global score positively correlated with BMI (r = 0.216, P < 0.05), H&Y stage (r = 0.223, P < 0.05), UPDRS-I (r = 0.501, P < 0.01), UPDRS-III (r = 0.425, P < 0.01), ESS (r = −0.296, P < 0.01), RBD (r = 0.227, P < 0.05), RLS (r = 0.254, P < 0.01), HAMA (r = 0.329, P < 0.01), and HAMD (r = 0.466, P < 0.01). In the final model, H&Y stage, RLS, UPDRS-III, and HAMD remained associated with the PQSI score (P ≤ 0.001, P ≤ 0.001, P = 0.049, P ≤ 0.001, respectively). Conclusions Our data showed that PNS was common in patients with PD. H&Y stage, UPDRS-III, HAMD, and RLS were positively associated with PNS. Attention to the management of motor symptoms, RLS, and depression may be beneficial to nighttime sleep quality in patients with PD.

Association of poor sleep quality with risk factors after coronary artery bypass graft surgery—A prospective cohort study

Fragmented sleep is a daunting experience and a common health problem with high prevalence among patients 3months after coronary artery bypass grafting (CABG). However, the potential predictors on poor seep quality remains unexplored. The main purpose of this study was to determine the predictors of poor sleep quality among patients 3months after CABG. A prospective cohort study is a part of the randomized controlled trial between 2012 and 2013 in which 400 adult patients undergoing elective CABG were being randomly sampled as per the inclusion criteria followed up at 3months after CABG surgery in the cardiovascular outpatient clinic of a tertiary-care hospital. The study was conducted according to the Declaration of Helsinki and was approved by the institutional ethical committee. All participants gave written informed consent on having received detailed information on the study. Demographic and clinical data were obtained from medical records at the time of CABG. The data on sleep quality were collected by using the Pittsburgh Sleep Quality Index and state anxiety was evaluated utilizing state-trait anxiety inventory (STAI-YI fo3rm). Multivariable logistic regression examined the association between the postoperative poor sleep quality and clinical, preoperative state anxiety, and angina. The significant variables are chosen based on the P-value associated with the significant level of model that lies on α=0.05. Logit determination and the correlation between the variables are also discussed for further analysis. A total of 187 patients (mean age 55.6±12.05years) completed the questionnaire. Most patients (78%) reported poor sleep quality (4.23±1.24) (PQSI score of less than 5). There was a strong relationship between PQSI and state anxiety. The higher state anxiety among 68% of patients with the mean score (53.51±9.55) had 6.42 (95% CI 3.04-9.61) times the odds of being classified as high risk for sleep disturbance. There are 3 factors that most significant of the 8 factors tested were identified as having influence significantly on the poor sleep quality. These factors are diabetes (OR 1.186, 95% CI 1.016-1.097, P>.01), body mass index>30kg/m2 (OR 2.36, 95% CI 1.041-1.172, P>.05), sedentary lifestyle (OR 1.091, 95% CI 1.016-1.159, P>.01), and preoperative state anxiety (OR 1.186, 95% CI 1.074-1.115, P>.01). Even though the body mass index>30kg/m2, sedentary lifestyle, and diabetes were significantly associated with sleep quality, the only factor with more significantly related to poor sleep quality was preoperative state anxiety which is the strong predictor of poor sleep quality. Hence, early recognition of predictors and careful management of poor sleep quality is warranted.

Preliminary study of the association of serum irisin levels with poor sleep quality in rheumatoid arthritis patients

Study objectivesSleep disorders are significant problems in patients with rheumatoid arthritis (RA) and are associated with poor quality of life. Irisin is myokine which may have anti-inflammatory and energy regulatory roles. This study assessed the association of serum irisin levels with the quality of sleep and disease activity in RA patients. MethodsIn sum, 58 RA patients and 30 matched healthy controls were included. Disease activity score in 28 joints (DAS28-ESR) and the patients’ global score were calculated. RA patients were grouped according to the Pittsburgh Sleep Quality Index score (PSQI) into good-sleepers (group 1) defined as a PQSI score≤5 and poor sleepers (group 2) with a PSQI > 5. Serum irisin levels were measured for both patients and controls by commercially available enzyme-linked immunosorbent assay kits. ResultsPoor sleep quality was found in 26 (45%) of the RA patients. Irisin levels were significantly lower in RA patients with poor sleep compared to those with good sleep and healthy controls (p < 0.001). Serum irisin levels correlated inversely with disease duration, morning stiffness duration, DAS28-ESR, global score, and total PSQI score (r = −0.722 to −0.263 & p values≤0.001–0.04) indicating a possible anti-inflammatory role of irisin in RA patients. The analysis employed Student's t-test, ANOVA, and Pearson correlation. ConclusionsIrisin levels were decreased in RA patients with poor sleep quality compared to RA patients with good sleep quality and healthy controls, indicating a possible association of decreased serum irisin with sleep impairment in RA patients.

Hopelessness is associated with poor sleep quality after breast cancer surgery among Tunisian women

Background: Sleep disorders are a common complaint in breast cancer patients. These women suffer from fear of death, fear of suffering, treatment complications as well as social devaluation; all leading to feelings of hopelessness. The objectives of this work were to evaluate the quality of sleep in a group of breast cancer women, and to analyze the association between sleep quality, depression, and hopelessness.Methods: A cross-sectional study was carried out over a period of 3 months, including 50 women suffering from breast cancer and having received a surgical treatment of their disease. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The evaluation of depression was performed using the Beck Depression Inventory (BDI-II). Hopelessness was measured with the Beck hopelessness scale (BHS). All participants were screened using the Arab-language version of these scales.Results: Of 66% of breast cancer patients were considered as poor sleepers (PSQI scores >5), 30% of our sample had a moderate to severe depression, and 24% had a high level of hopelessness. PQSI scores were negatively correlated with depression (P < 0.001) and hopelessness scores (P < 0.001). Multivariate analysis retained as main predictors of the sleep quality habitation and hopelessness scores. After controlling for demographic (age) and social (habitation) variables, hopelessness significantly contributed to sleep quality.Conclusion: Hopelessness was positively associated to sleep disorders in women suffering from breast cancer. Hopelessness requires an appropriate management in order to prevent depression and suicide and to improve the quality of life of these patients.

Effect of rehabilitation exercise training on sleep quality and fatigue of hemodialysis patients with uremia

Objective To study the effects of rehabilitation exercise training on sleep quality and fatigue in hemodialysis patients with uremia. Methods A convenient sampling method was used to select 94 patients with uremia who underwent hemodialysis from September 2016 to September 2017. The patients were divided into routine group and training group according to the random number table method. example. The routine group was given routine hemodialysis care, and the training group was instructed to perform rehabilitation exercise training on the basis of routine group nursing. Both groups were intervened for 16 weeks. Pittsburgh Sleep Index (PQSI) was used to assess the quality of sleep. The sleep quality of the two groups before intervention, intervention for 8 weeks, and intervention for 16 weeks was compared. The fatigue scale (Fatigue Scale-14, FS-14) was used to assess the degree of fatigue. The degree of fatigue in the two groups before intervention, 8 weeks of intervention, and 16 weeks of intervention. Results Before the intervention, there was no significant difference in PQSI scores between the two groups (P>0.05). After 8 weeks of intervention, the PQSI values of the training group were significantly lower than those before the intervention (t=4.20, P 0.05), and the PQSI value of the training group (8.21±2.26) was significantly lower than that of the conventional group (10.15±3.19) (t=3.40, P 0.05). The PQSI values of the training group (6.97±2.32). PQSI values (8.93 ± 3.28) were significantly lower than those in the conventional group (t = 5.50, P 0.05). After 8 weeks of intervention, the FS-14 total score, physical fatigue score and mental fatigue of the training group. The scores were significantly lower than those before the intervention (t=3.83, 3.29, 2.64, P 0.05), and the FS-14 total score (7.02±1.12), physical fatigue score (5.30±1.55), and mental fatigue score (1.83±1.02) in the training group were significantly lower than those in the conventional group. -14 total score (9.01±2.14), physical fatigue score (6.23±1.72), mental fatigue score (2.66±1.37) (t=5.65, 2.75, 3.33, P 0.05), and The FS-14 total score (6.05±1.58), physical fatigue score (4.58±1.36), and mental fatigue score (1.35±1.10) in the training group were significantly lower than those in the conventional group (8.94±2.17), body. Fatigue score (6.33±1.82) and mental fatigue score (2.59±1.36) (t=7.34, 5.28, 4.86, P<0.05). Conclusion Rehabilitation exercise training can significantly improve the sleep quality of hemodialysis patients with uremia and reduce the fatigue degree of hemodialysis patients with uremia. It is worthy of clinical promotion. Key words: Rehabilitation exercise training; Uremia; Hemodialysis; Sleep quality; Fatigue

PIH11 - Anxiety and Insomnia Among Elderly People in Chonburi, Thailand 2017

1. To identify socio-economic and demographic data of elderly people in Chonburi, Thailand. 2. To collect data of sleep quality, anxiety and drug use for insomnia 3. To compare means of age, BMI, sleep quality and anxiety among elderly people in 11 districts. 4. To identify association between sleep quality and anxiety. A cross-sectional survey research by face to face interview and questionnaire was performed during 7 months in 2017. The 60 years of age and above people in 11 Chonburi districts were randomly selected using non-probability, purposive-sampling method. Population were all elderly people who could read and write Thai and willing to participate. Sample size was calculated via Jacob Cohen’s table 8.4.3, when α was set to 0.05, power 0.80, effect size 0.20, k (group)= 11, it yielded n = 30 in each group. therefore 30*11= 330 samples were collected. 100% samples were completely collected. Cronbach’s Alpha coefficient confirmed internal consistency of The Pittsburgh Sleep Quality Index (PSQI), 0.7447 and The Hospital Anxiety and Depression Scale (HADS), 0.7874. The average age of participants was 68.50±3.47, BMI 21.91±8.44, PQSI score 9.60±4.58, HAD score 11.42±3.71. Most were female 176 (53.33%), live with spouse 215 (65.15%), passed secondary school 117 (35.45%), employee 130 (39.39%). Anxiety elderly was classified as normal 233 (76.61%), mild 83 (25.61%), moderate 13 (3.94%) and severe 1 (0.30%). These senior citizens were sleet well 124 (35.58%) and not sleep well 206 (62.42%). Most insomnia drugs prescribed for elderly were, Lorazepam, Amitriptyline and Clonazepam (7,41%, 6.51% and 4.74%) respectively. Inference statistics proved: Anxiety and sleep quality of elderly in 11 districts were not significantly different (ANOVA, p=0.0741). Moreover, anxiety (HADS), BMI, marital status and occupation significantly associated with sleep quality (PSQI) (Chi Square, p=0.000, 0.045, 0.041 and 0.005 respectively). Anxiety was significantly associated with sleep quality.

Analysis on the non-motor symptoms of essential tremor

Objective To explore the the characteristics of non-motor symptoms of essential tremor(ET). Methods Totally 50 ET patients and 45 age-gender-matched healthy volunteers, admitted in Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine from May 2015 to April 2016, were included.Clinical data and tremor analyses under different postures were obtained.The non-motor symptoms were evaluated using the Pittsburgh Sleep Quality Index(PSQI), Hamilton anxiety scale(HAMA), Hamilton's Depression Scale(HAMD), and the MOS item short from health survey(SF-36). Cognitive functions were evaluated by the Mini-mental state examination(MMSE). Results ET group had lower MMSE total score of(25.81±2.75 vs.28.16±1.71), increased rate of dyssomnia(62.0% vs.15.6%)and higher PQSI score(6.42±2.71 vs.3.84±2.13)compared with the control group(all P<0.05). Moreover, more patients in the ET group had moderate and severe anxiety(60.0% vs.37.8%), moderate and severe depression(34.0% vs.15.6%)than the control group(both P<0.05). Anxiety and depression had effects on physical and mental health and were also related to the quality of life. Conclusions Non-motor symptoms, such as mild cognitive deficits, depression, anxiety and dyssomnia are common in ET patients.Furthermore, depression and anxiety have negative effects on physical and mental health. Key words: Essential tremor; Depression; Anxiety; Cognition disorders; Nonmotor symptoms