Capturing patient-reported sleep disturbance in atopic dermatitis clinical trials.

BACKGROUND: Patient-focused approaches to capturing day-to-day variability in sleep disturbance are needed to properly evaluate the sleep benefits of new treatments. Such approaches rely on patient-reported outcome (PRO) measures validated in the target patient population. METHODS: Using atopic dermatitis (AD) as an example of a disease in which sleep is commonly disturbed, we developed a strategy for measuring sleep disturbance in AD trials. In developing this strategy, we conducted a targeted literature review and held concept elicitation interviews with adolescents and adults with AD. We subsequently identified potentially suitable PRO measures and cognitively debriefed them. Finally, we evaluated their psychometric properties using data from phase 2b (NCT03100344) and phase 3 (NCT03985943 and NCT03989349) clinical trials. RESULTS: The literature review confirmed that sleep disturbance is a key impact of AD but failed to identify validated PRO measures for assessing fluctuations in sleep disturbance. Subsequent concept elicitation interviews confirmed the multidimensional nature of sleep disturbance in AD and supported use of a single-item measure to assess overall sleep disturbance severity, complemented by a diary to capture individual components of sleep disturbance. The single-item sleep disturbance numerical rating scale (SD NRS) and multi-item Subject Sleep Diary (SSD)-an AD-adapted version of the Consensus Sleep Diary-were identified as potentially suitable PRO measures. Cognitive debriefing of the SD NRS and SSD demonstrated their content validity and their understandability to patients. Psychometric analyses based on AD trial data showed that the SD NRS is a well-defined, reliable, and fit-for-purpose measure of sleep disturbance in adults with AD. Furthermore, the SD NRS correlated with many SSD sleep parameters, suggesting that most concepts from the SSD can be covered using the SD NRS. CONCLUSIONS: Using these findings, we developed an approach for measuring sleep disturbance in AD trials. Subject to further research, the same approach could also be applied to future trials of other skin diseases where itch causes sleep disturbance.

Study on the preventive effect of dexmedetomidine on anesthetic associated sleep disturbance in young to middle-aged female patients undergoing hysteroscopy: a study protocol for a crossover randomized controlled trial.

BACKGROUND: Postoperative sleep disturbance has a potentially detrimental effect on postoperative recovery. Perioperative patients are affected by several factors. General anesthesia induces a non-physiological state that does not resemble natural sleep. Exposure to propofol/sevoflurane can lead to desynchronization of the circadian rhythm, which may result in postoperative sleep disturbance characterized by mid-cycle advancement of sleep and daytime sleepiness. Dexmedetomidine is a highly selective α2-adrenoceptor agonist with a unique sedative effect that facilitates the transition from sleep to wakefulness. Basic research has shown that dexmedetomidine induces deep sedation, similar to physical sleep, and helps maintain forebrain connectivity, which is likely to reduce delirium after surgery. The aim of this study is to evaluate the influence of exposure to the mono-anesthetic propofol on the development of postoperative sleep disturbance in young and middle-aged female patients undergoing hysteroscopy and whether prophylactic administration of dexmedetomidine influences reducing postoperative sleep disturbance. METHODS: This prospective randomized controlled trial (RCT) will include 150 patients undergoing hysteroscopy at the First Affiliated Hospital of Xiamen University. Participants will be randomly assigned to three groups in a 1:1:1 ratio. The dexmedetomidine group will have two subgroups and will receive a nasal spray of 0.2 µg/kg or 0.5 µg/kg 25 min before surgery, while the control group will receive a saline nasal spray. Three groups will undergo hysteroscopy with propofol-based TIVA according to the same scheme. Sleep quality will be measured using a wearable device and double-blind sleep assessments will be performed before surgery and 1, 3, and 7 days after surgery. SPSS 2.0 is used for statistical analysis. A χ2 test is used to compare groups, and t-test is used to determine statistical the significance of continuous variables. DISCUSSION: The purpose of this study is to investigate the incidence of propofol-associated sleep disorders and to test a combination of dexmedetomidine anesthesia regimen for the prevention of postoperative sleep disorders. This study will help to improve patients' postoperative satisfaction and provide a new strategy for comfortable perioperative medical treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT06281561. Registered on February 24, 2024.

Perceptions of Emerging Adults With Type 1 Diabetes Mellitus on How the Condition Influences Sleep Quality: A Qualitative Study.

Background: Emerging adulthood is a phase characterized by exploration which potentially affecting sleep quality. While many emerging adults are healthy, the effects of chronic diseases such as Type 1 Diabetes Mellitus (T1DM) on sleep may be underestimated. Considering the frequency of nocturnal glycemic alterations that cause awakenings, this study explored the perceptions of emerging adults in Andalusia on the influence of T1DM on their sleep quality. Methods: A qualitative approach was used for this study. Purposive sampling through diabetes associations was initially utilized, supplemented by snowball sampling, in order to conduct semistructured interviews with 73 emerging adults (aged 18-29) diagnosed with T1DM, to explore their perceptions of the influence of T1DM on sleep quality. Interpretative Phenomenological Analysis was used for data analysis. Results: Sleep disruptions caused by overnight hyperglycemia and hypoglycemia were identified as significant factors. However, 62% of participants did not perceive the influence of diabetes on their sleep quality, despite experiencing frequent overnight glycemic alterations (reported by 40.9%). Conclusions: Perception of the impact of T1DM on sleep quality does not always align with the frequency of disruptions. Nonetheless, promoting healthy sleep and systematically assessing sleep quality can benefit both sleep and glycemic outcomes, regardless of individual perceptions.

Core concomitant symptoms reported by the patients with breast cancer in postoperative endocrine treatment and the demand for acupuncture therapy： a network-based cross-sectional study. / ä¹³è ºç™Œæœ¯åŽå† åˆ†æ³Œæ²»ç–—æ‚£è€ æŠ¥å‘Šçš„æ ¸å¿ƒä¼´éšç—‡çŠ¶åŠå¯¹é’ˆç¸æ²»ç–—çš„éœ€æ±‚ï¼šä¸€é¡¹åŸºäºŽç½‘ç»œçš„æ¨ªæ–­é¢ç ”ç©¶.

OBJECTIVES: To investigate the most common concomitant symptoms and the urgent demand of solution in the breast cancer patients undergoing postoperative endocrine treatment, as well as the acceptance and expectation of acupuncture in the patients so as to provide the scientific data for promoting the application of acupuncture in the breast cancer patients. METHODS: Breast cancer patients treated in Tianjin Medical University Cancer Institute and Hospital from January 2022 to March 2023 were randomly selected as the subjects. Using "questionnaire star" website, the questionnaire was conducted to investigate the relevant concomitant symptoms of the patients in postoperative endocrine treatment and the questions related to acupuncture treatment. RESULTS: In this study, 229 questionnaires were distributed and 211 valid ones were collected, with the response rate of 92.1%. Among these patients, the first three common symptoms were sleep disorders (157 cases, 74.4%), hot flashes (138 cases, 65.4%) and joint / muscle pain (118 cases, 55.9%)；the top three symptoms to be solved the most urgently were sleep disorders (131 cases, 62.1%), joint / muscle pain (62 cases, 29.4%) and hot flashes (45 cases, 21.3%). 79.1% of the patients (167 cases) were willing to receive acupuncture treatment because of the high expectations on its potential effect (93%). 20.9% of them (44 cases) refused acupuncture because they were worried not to be treated by the experienced physicians of TCM (52%) or afraid of needling feelings (48%). The average expectation value of acupuncture treatment was 4.02 points (5 points for the total score) among patients willing to receive acupuncture treatment. The main purposes of receiring acupuncture for the patients undergoing endocrine treatment were to strengthen the immune function (92%), reduce the adverse reactions (83%), and improve the physical condition (75%), et al. CONCLUSIONS: Sleep disorder is one of the most concerned symptoms in endocrine treatment for the patients after breast cancer surgery. The patients highly expect for acupuncture treatment even though some patients dislike the needling sensation. How to provide the acceptable and high-quality acupuncture services for cancer patients will be one of the major directions of acupuncture research in the future.

Mapping complex public health problems with causal loop diagrams.

This paper presents causal loop diagrams (CLDs) as tools for studying complex public health problems like health inequality. These problems often involve feedback loops-a characteristic of complex systems not fully integrated into mainstream epidemiology. CLDs are conceptual models that visualize connections between system variables. They are commonly developed through literature reviews or participatory methods with stakeholder groups. These diagrams often uncover feedback loops among variables across scales (e.g. biological, psychological and social), facilitating cross-disciplinary insights. We illustrate their use through a case example involving the feedback loop between sleep problems and depressive symptoms. We outline a typical step-by-step process for developing CLDs in epidemiology. These steps are defining a specific problem, identifying the key system variables involved, mapping these variables and analysing the CLD to find new insights and possible intervention targets. Throughout this process, we suggest triangulating between diverse sources of evidence, including domain knowledge, scientific literature and empirical data. CLDs can also be evaluated to guide policy changes and future research by revealing knowledge gaps. Finally, CLDs may be iteratively refined as new evidence emerges. We advocate for more widespread use of complex systems tools, like CLDs, in epidemiology to better understand and address complex public health problems.

[Poor sleep quality contributes to occurrence of posttraumatic stress disorder in trauma patients].

OBJECTIVE: To evaluate the impact of poor sleep quality on occurrence of post-traumatic stress disorder (PTSD) in trauma patients. METHODS: We prospectively recruited 256 trauma patients hospitalized in 4 general hospitals in Zunyi during the period from October, 2021 to November, 2022, and 226 of the participants completed the PTSD survey and assessment. The patients' sleep quality within a month before trauma was estimated using Pittsburgh Sleep Quality Index (PSQI), and their sleep quality within 7 days after admission was monitored by smart bracelet sleep monitoring; the PTSD Checklist-Civilian Version (PCL-C) was used to detect the occurrence of PTSD during the follow-up. RESULTS: The detection rate of PTSD in the patients was 19.47% at 1 month and 17.61% at 3 months after trauma. The patients who developed PTSD had poorer sleep quality before the trauma, as shown by significantly higher PSQI scale scores (P < 0.001), than those without PTSD, and they showed a sleep abnormality rate as high as 72.73% prior to PTSD onset. Within 7 days after admission, the patients developing PTSD had lower sleep quality scores with more frequent night awakenings (P < 0.05). A 1 month and 3 months after trauma, the patients with PTSD had significantly higher PSQI scores than those without PTSD (P < 0.05). CONCLUSION: PTSD is more likely to occur in trauma patients with poor sleep quality before trauma.

Moderation by better sleep of the association among childhood maltreatment, neuroticism, and depressive symptoms in the adult volunteers: A moderated mediation model.

BACKGROUND: Previously, we demonstrated that childhood maltreatment could worsen depressive symptoms through neuroticism. On the one hand, some studies report that sleep disturbances are related to childhood maltreatment and neuroticism and worsens depressive symptoms. But, to our knowledge, no reports to date have shown the interrelatedness between childhood maltreatment, neuroticism, and depressive symptoms, and sleep disturbance in the one model. We hypothesized that sleep disturbance enhances the influence of maltreatment victimization in childhood or neuroticism on adulthood depressive symptoms and the mediation influence of neuroticism between maltreatment victimization in childhood and adulthood depressive symptoms. SUBJECTS AND METHODS: Total 584 Japanese volunteer adults recruited through convenience sampling from 4/2017 to 4/2018 were assessed regarding their characteristics of demographics, history of childhood maltreatment, sleep disturbance, neuroticism, and depressive symptoms with questionnaires self-administered. Survey data were analyzed using simple moderation models and a moderating mediation model. RESULTS: The interaction of sleep disturbance with childhood maltreatment or neuroticism on depressive symptoms was significantly positive. Furthermore, the moderating effect of sleep disturbance on the indirect effect of childhood maltreatment to depressive symptoms through neuroticism was significantly positive. LIMITATIONS: Because this was a cross-sectional study, a causal relationship could not be confirmed. CONCLUSIONS: Our findings indicate that individuals with milder sleep disturbance experience fewer depressive symptoms attributable to neuroticism and childhood maltreatment. Additionally, people with less sleep disturbance have fewer depressive symptoms arising from neuroticism owing to childhood maltreatment. Therefore, improvement of sleep disturbance will buffer the aggravating effect of childhood maltreatment, neuroticism caused by various factors, and neuroticism resulting from childhood maltreatment on depressive symptoms.

Exploring Determinants of Health-Related Quality of Life in Emerging Adults with Type 1 Diabetes Mellitus: A Cross-Sectional Analysis.

(1) Background: Emerging adulthood, from the age of 18 to 29 years, is a crucial phase for individuals with Type 1 Diabetes Mellitus, as it affects their Health-Related Quality of Life. (2) Methods: This cross-sectional study analyzes the influence of the Mediterranean diet, Diabetes duration, Hemoglobin A1c, and sleep disorders on Health-Relate Quality of Life in Type 1 Diabetes Mellitus. In this study, conducted in Andalusia, Spain, 362 emerging adults with Type 1 Diabetes Mellitus completed the Oviedo Sleep Questionnaire, the Adaptation of Mediterranean Diet Adherence Screener, and the Vida con Diabetes Tipo 1 (ViDa1) Health-Related Quality of Life questionnaire between October 2021 and July 2022. Pearson correlation coefficients and a multiple regression analysis were conducted for each Health-Related Quality of Life in Type 1 Diabetes Mellitus dimension (Interference with Life, Well-being, Self-care, and Concern about the Condition) for overall sample and separately for males and females. (3) Results: Different and significant correlations are found among factors such as Age, Body Mass Index, Currently being a student, Hemoglobin A1c, Sleep satisfaction, Insomnia, Hypersomnolence, and Adherence to Mediterranean diet. Notably, Insomnia is a main predictor for Interference with Life, Well-being, and Concern about the Condition, especially for females. (4) Conclusions: Insomnia is the main predictor of Health-Related Quality of Life in Type 1 Diabetes Mellitus among Andalusian emerging adults with this condition. Consequently, a regular assessment of sleep and Health-Related Quality of Life from a gender perspective in this age group is crucial.

Association of Sleep Quality and General, Mental, and Oral Health with Lifestyle Traits (Dietary Intake, Smoking Status) in Arthritis: A Cross-Sectional Study from the Canadian Community Health Survey (CCHS).

Arthritis is associated with health challenges. Lifestyle traits are believed to influence arthritis development and progression; however, data to support personalized treatment regimens based on holistic lifestyle factors are missing. This study aims to provide a comprehensive list of associations between lifestyle traits and the health status of individuals with arthritis in the Canadian population, using binary logistic regression analysis on data from the Canadian Community Health Survey, which includes 104,359 respondents. Firstly, we explored the association between arthritis and various aspects of health status including self-reported lifestyle factors. Secondly, we examined the associations between self-reported dietary intake and smoking status with general, mental, and oral health, and sleep disturbance among individuals both with and without arthritis. Our analysis revealed that individuals with arthritis reported considerably poorer general, mental, and oral health, and poorer sleep quality compared to those without arthritis. Associations were also found between self-reported dietary intake and various measures of health status in individuals with arthritis. Smoking and exposure to passive smoking were associated not only with arthritis but also with compromised sleep quality and poorer general, mental, and oral health in people with and without arthritis. This study highlights the need for personalized and holistic approaches that may include a combination of dietary interventions, oral health improvements, sleep therapies, and smoking cessation for improved arthritis prevention and care.

Poor Adherence to the Mediterranean Diet and Sleep Disturbances Are Associated with Migraine Chronification and Disability among an Adult Population in the Lazio Region, Italy.

Lifestyle factors, such as diet and sleep quality, are receiving increasing interest as accessible therapeutic approaches to migraine. The Mediterranean diet (MD) has shown clear benefits in cardiovascular and metabolic diseases, as well as in sleep patterns. Here, our objective was to identify the impact of adherence to the MD and other lifestyle factors on the clinical burden of migraine. For this purpose, we enrolled 170 migraine patients and 100 controls, assessing the clinical disability of headache using standardized clinical scales (HIT-6 and MIDAS) in the migraineur cohort and lifestyle patterns in both groups through the PREDIMED score for MD adherence, the IPAQ scale for physical activity, and BMI. Subjects were also screened for sleep-wake disturbances based on the Pittsburgh Sleep Quality Index (PSQI). We found that migraine patients had lower adherence to the MD compared to the controls and that the HIT-6 scale had a significant negative relationship with MD adherence in patients with high-frequency episodic and chronic migraine. Additionally, in the same migraine patients, the presence of sleep-wake disturbances was correlated with greater migraine disability as assessed by the MIDAS score. In conclusion, this study found that among different lifestyle factors, poor adherence to the MD and the presence of sleep-wake disturbances were closely associated with migraine disability and chronification.

Sleep profiles of different psychiatric traits.

Disturbed sleep comes in many forms. While the key role of sleep in mental health is undisputed, our understanding of the type of sleeping problems that manifest in the early stages of psychiatric disorders is limited. A sample without psychiatric diagnoses (N = 440, 341 women, 97 men, 2 non-binaries; Mage = 32.1, SD = 9.4, range 18-77) underwent a comprehensive assessment, evaluating eight sleep features and 13 questionnaires on common psychiatric complaints. Results revealed that traits of affect disorders, generalized anxiety, and ADHD had the worst sleep profiles, while autism disorder, eating disorder, and impulsivity traits showed milder sleep issues. Mania was the only trait associated with an overall better sleep profile. Across traits, insomnia and fatigue dominated and sleep variability was least prominent. These findings provide support for both transdiagnostic and disorder-specific targets for prevention and treatment.

State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset.

Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an optimized, state-of-the-art approach using data from daily work in our university hospital sleep laboratory. Therefore, a machine learning algorithm was trained and evaluated on 3423 polysomnograms of people with various sleep disorders. The model architecture is a U-net that accepts 50 Hz signals as input. We compared this algorithm with models trained on publicly available datasets, and evaluated these models using our clinical dataset, particularly with regard to the effects of different sleep disorders. In an effort to evaluate clinical relevance, we designed a metric based on the error of the predicted arousal index. Our models achieve an area under the precision recall curve (AUPRC) of up to 0.83 and F1 scores of up to 0.81. The model trained on our data showed no age or gender bias and no significant negative effect regarding sleep disorders on model performance compared to healthy sleep. In contrast, models trained on public datasets showed a small to moderate negative effect (calculated using Cohen's d) of sleep disorders on model performance. Therefore, we conclude that state-of-the-art arousal detection on our clinical data is possible with our model architecture. Thus, our results support the general recommendation to use a clinical dataset for training if the model is to be applied to clinical data.

Interaction effects between sleep-related disorders and depression on hypertension among adults: a cross-sectional study.

BACKGROUND: Hypertension, sleep disorders, and depression represent notable public health issues, and their interconnected nature has long been acknowledged. The objective of this study is to explore the interplay between sleep disorders and depression in the context of hypertension. METHODS: This cross-sectional study involved 42,143 participants aged 18 and above from the NHANES database across seven survey cycles between 2005 and 2018. After excluding those with missing data on depression, sleep disorders, and hypertension, as well as incomplete main variables, 33,383 participants remained. We used weighted logistic regression to examine the relationship between sleep disorders, depression, and hypertension. Additionally, we assessed the interaction between sleep disorders and depression on hypertension using both multiplicative and additive approaches to quantify their combined effect. RESULTS: Compared to individuals without sleep disorders, those with sleep disorders have an increased risk of hypertension (OR = 1.51, 95% CI: 1.37-1.67). Furthermore, individuals with depression experience a significantly higher risk of hypertension compared to those with sleep disorders alone (OR = 2.34, 95% CI: 1.95-2.80). Our study reveals a positive interaction between sleep disorders and depression in relation to hypertension risk (OR = 1.07, 95% CI: 1.02-1.13). In addition, we observed the quantitative additive interaction indicators (RERI = 0.73, 95% CI: 0.56 ~ 0.92; API = 0.31, 95% CI: 0.11 ~ 0.46; SI = 2.19, 95% CI: 1.08-3.46) influencing hypertension risk. Furthermore, our research also identified that individuals with less than 7 h of sleep, a sleep latency period between 5 and 30 min, or a latency period exceeding 30 min experience a significantly increased risk of hypertension. CONCLUSIONS: Our research uncovered separate links between sleep disorders, depression, and hypertension prevalence. Moreover, we identified an interaction between depression and sleep disorders in hypertension prevalence. Enhancing mental well-being and tackling sleep disorders could help prevent and manage hypertension. Yet, more investigation is required to establish causation and clarify mechanisms.

Cross-sectional study assessing sleep behavior and musculoskeletal symptoms in elite junior badminton athletes.

Sleep inadequacy has previously been associated with increased risk of injury and reduced performance. It is unclear if sleep disorders are associated with musculoskeletal symptoms, which may be a predictor of serious injury and affect performance. The aim was therefore to assess sleep behavior in elite junior badminton players and its association to musculoskeletal symptoms. In 2018, players at the World Junior Badminton Championship completed the Athlete Sleep Behavior Questionnaire and a modified version of the World Olympic Association Musculoskeletal Health Questionnaire. Participants were categorized with poor or moderate/good sleep behavior as the independent variable. Musculoskeletal symptoms were the primary outcome and was categorized using yes/no questions. Relevant musculoskeletal symptoms were defined as pain higher than 30 mm Numeric Rating Scale pain score or more than 30 minutes of joint stiffness a day. Group comparison was performed using chi-square analysis and logistic regression for primary outcome adjusted for age, sex, ethnicity, previous injury, training load, and resting days. Of the 153 participants, 28% reported poor sleep scores. There was no difference between poor and moderate/good sleep score concerning demographic variables such as sex, age, ethnicity, previous injury, training load, and resting days. There were 27% with current musculoskeletal symptoms but with no difference in groups between poor and moderate/good sleep score (P = .376). This yielded an adjusted odds ratio of 1.23 (95% confidence intervals 0.52; 2.90). Twenty-eight percent of the participants reported poor sleep behavior. Twenty-seven percent experienced current musculoskeletal symptoms. We found no statistical differences in reported musculoskeletal symptoms when comparing athletes with poor sleep behavior to athletes with moderate/good sleep behavior.

Risks of anxiety disorders, depressive disorders, and sleep disorders in patients with dengue fever: A nationwide, population-based cohort study.

BACKGROUND: Dengue virus (DENV) infection, a common mosquito-borne disease, has been linked to several mental disorders like depression and anxiety. However, the temporal risk of these disorders after DENV infection is not well studied. METHODS: This population-based cohort study encompassed 45,334 recently lab-confirmed dengue patients in Taiwan spanning 2002 to 2015, matched at a 1:5 ratio with non-dengue individuals based on age, gender, and residence (n = 226,670). Employing subdistribution hazard regression analysis, we assessed the immediate (<3 months), intermediate (3-12 months), and prolonged (>12 months) risks of anxiety disorders, depressive disorders, and sleep disorders post DENV infection. Corrections for multiple comparisons were carried out using the Benjamini-Hochberg procedure. RESULTS: A significant increase in depressive disorder risk across all timeframes post-infection was observed (<3 months [aSHR 1.90, 95% CI 1.20-2.99], 3-12 months [aSHR 1.68, 95% CI 1.32-2.14], and >12 months [aSHR 1.14, 95% CI 1.03-1.25]). Sleep disorder risk was higher only during 3-12 months (aSHR 1.55, 95% CI 1.18-2.04). No elevated anxiety disorder risk was found. Subgroup analysis of hospitalized dengue patients showed increased risk of anxiety disorders within 3 months (aSHR 2.14, 95% CI 1.19-3.85) and persistent risk of depressive disorders across all periods. Hospitalized dengue patients also had elevated sleep disorder risk within the first year. CONCLUSION: Dengue patients exhibited significantly elevated risks of depressive disorders in both the short and long term. However, dengue's impact on sleep disorders and anxiety seems to be short-lived. Further research is essential to elucidate the underlying mechanisms.

The association of depression and sleep disorders in patients with type 1 diabetes in Taiwan.

The association between depression and sleep disorders in patients with type 1 diabetes mellitus (T1DM) in Taiwan is underexplored. We used a nationwide population-based dataset to evaluate the association of T1DM with these conditions in Taiwan from 2001 to 2019. Patients with T1DM were identified as cases, and 2 control groups were used for comparison: patients with type 2 diabetes mellitus (T2DM) and nondiabetic patients. Age, sex, date of diagnosis, and multiple comorbidities were included and matched using propensity score matching between cases and controls. The primary outcome of this study was to identify new occurrences of the first diagnosis of depression or sleep disorders. After matching, this study included 27,029 T1DM cases, 54,058 T2DM controls, and 108,116 nondiabetic controls. Patients with T1DM exhibited a 1.55-fold higher risk of developing depression (hazard ratio [HR] 1.55, 95% confidence intervals [CI] 1.48-1.61) and a 1.41-fold higher risk of experiencing sleep disorders (HR 1.41, 95% CI 1.37-1.46) compared to nondiabetic controls. Similarly, patients with T2DM displayed elevated risks of both depression (HR 1.39, 95% CI 1.34-1.43) and sleep disorders (HR 1.40, 95% CI 1.37-1.44) relative to non-diabetic controls. When comparing the T1DM and T2DM groups, T1DM patients demonstrated a slightly higher risk of depression (HR 1.11, 95% CI 1.07-1.16) but no significant difference in the risk of sleep disorders compared to T2DM patients. These results were consistent regardless of different ages or sexes. This study demonstrates a significant association between diabetes mellitus and the risk of depression and sleep disorders in a large cohort of Taiwanese patients.

Gray matter volume alterations in de novo Parkinson's disease: A mediational role in the interplay between sleep quality and anxiety.

OBJECTIVE: Parkinson's disease (PD) is increasingly recognized for its non-motor symptoms, among which emotional disturbances and sleep disorders frequently co-occur. The commonality of neuroanatomical underpinnings for these symptoms is not fully understood. This study is intended to investigate the differences in gray matter volume (GMV) between PD patients with anxiety (A-PD) and those without anxiety (NA-PD). Additionally, it seeks to uncover the interplay between GMV variations and the manifestations of anxiety and sleep quality. METHODS: A total of 37 A-PD patients, 43 NA-PD patients, and 36 healthy controls (HCs) were recruited, all of whom underwent voxel-based morphometry (VBM) analysis. Group differences in GMV were assessed using analysis of covariance (ANCOVA). Partial correlation between GMV, anxiety symptom, and sleep quality were analyzed. Mediation analysis explored the mediating role of the volume of GMV-distinct brain regions on the relationship between sleep quality and anxiety within the PD patient cohort. RESULTS: A-PD patients showed significantly lower GMV in the fusiform gyrus (FG) and right inferior temporal gyrus (ITG) compared to HCs and NA-PD patients. GMV in these regions correlated negatively with Hamilton Anxiety Rating Scale (HAMA) scores (right ITG: r = -0.690, p < 0.001; left FG: r = -0.509, p < 0.001; right FG: r = -0.576, p < 0.001) and positively with sleep quality in PD patients (right ITG: r = 0.592, p < 0.001; left FG: r = 0.356, p = 0.001; right FG: r = 0.470, p < 0.001). Mediation analysis revealed that GMV in the FG and right ITG mediated the relationship between sleep quality and anxiety symptoms, with substantial effect sizes accounted for by the right ITG (25.74%) and FG (left: 11.90%, right: 15.59%). CONCLUSION: This study has shed further light on the relationship between sleep disturbances and anxiety symptoms in PD patients. Given the pivotal roles of the FG and the ITG in facial recognition and the recognition of emotion-related facial expressions, our findings indicate that compromised sleep quality, under the pathological conditions of PD, may exacerbate the reduction in GMV within these regions, impairing the recognition of emotional facial expressions and thereby intensifying anxiety symptoms.

Mendelian randomization highlights sleep disturbances mediated the effect of depression on chronic pain.

INTRODUCTION: Depression and chronic pain are significant contributors to the global burden of disease. Previous research has revealed complex relationships between these two conditions, which may be influenced by sleep quality. However, observational studies have limitations, including confounding factors and reverse causation. This study aims to explore the mediating effects of sleep on the relationship between depression and chronic pain using Mendelian randomization (MR). METHODS: We conducted a two-step, two-sample MR study using mediation analysis. We obtained major depressive disorder (MDD) Genome-Wide Association Studdies (GWAS) data from Wray et al.'s GWAS meta-analysis. Phenotypic data related to sleep were collected from the UK Biobank. Chronic pain data were obtained from the Finnish database. RESULTS: MR analysis revealed significant genetic associations between MDD and chronic localized pain [IVW: odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.16-1.38, p = 2.52 × 10-7] as well as fibromyalgia (IVW: OR = 2.17, 95% CI = 1.34-3.52, p = .002). Genetic susceptibility for MDD was also associated with insomnia (IVW: OR = 1.10, 95% CI = 1.06-1.13, p = 3.57 × 10-8) and self-reported short sleep duration (IVW: OR = 1.03, 95% CI = 1.00-1.06, p = .047). The mediating effects of insomnia and fibromyalgia on the pathway from depression to chronic regional pain were 1.04 and 1.03, respectively, with mediation proportions of 12.8% and 15.2%. Insomnia mediated the pathway between depression and fibromyalgia with an effect of 1.12, accounting for 15.2% of the total effect. CONCLUSION: This two-step MR analysis strengthens the evidence of genetic predictive associations between depression and chronic pain, highlighting the mediating roles of insomnia and short sleep duration. It further elucidates the specific roles of distinct sleep disorders, differentiating insomnia and short sleep duration from other sleep-related phenotypes.

Development and validation of a nomogram model of depression and sleep disorders and the risk of disease progression in patients with breast cancer.

BACKGROUND: In this study, we investigated the relationship between the risk of postoperative progressive disease (PD) in breast cancer and depression and sleep disorders in order to develop and validate a suitable risk prevention model. METHODS: A total of 750 postoperative patients with breast cancer were selected from the First People's Hospital of LianYunGang, and the indices of two groups (an event group and a non-event group) were compared to develop and validate a risk prediction model. The relationship between depression, sleep disorders, and PD events was investigated using the follow-up data of the 750 patients. RESULTS: SAS, SDS, and AIS scores differed in the group of patients who experienced postoperative disease progression versus those who did not; the differences were statistically significant and the ability to differentiate prognosis was high. The area under the receiver operating characteristic (ROC) curves (AUC) were: 0.8049 (0.7685-0.8613), 0.768 (0.727-0.809), and 0.7661 (0.724--0.808), with cut-off values of 43.5, 48.5, and 4.5, respectively. Significant variables were screened by single-factor analysis and multi-factor analysis to create model 1, by lasso regression and cross-lasso regression analysis to create model 2, by random forest calculation method to create model 3, by stepwise regression method (backward method) to create model 4, and by including all variables for Cox regression to include significant variables to create model 5. The AUC of model 2 was 0.883 (0.848-0.918) and 0.937 (0.893-0.981) in the training set and validation set, respectively. The clinical efficacy of the model was evaluated using decision curve analysis and clinical impact curve, and then the model 2 variables were transformed into scores, which were validated in two datasets, the training and validation sets, with AUCs of 0.884 (0.848-0.919) and 0.885 (0.818-0.951), respectively. CONCLUSION: We established and verified a model including SAS, SDS and AIS to predict the prognosis of breast cancer patients, and simplified it by scoring, making it convenient for clinical use, providing a theoretical basis for precise intervention in these patients. However, further research is needed to verify the generalization ability of our model.