Non-pharmacological interventions for sleep disorders in patients with Alzheimer's disease: An integrative review.

Sleep disturbance is one of the clinical manifestations of post-intensive care syndrome (PICS) in ICU. Sleep disorders can cause changes in patients' emotional, cognitive, memory, immune, and motor systems, resulting in delayed wound healing, increased infection rate, readmission rate, mortality rate and complication rate. However, developing prediction models for sleep disorders in post-ICU patients is an understudied problem. To explore the risk factors of sleep disorders, establish the prediction model, and verify its prediction efficiency internally and externally, providing a scientific basis for clinical staff to prevent the occurrence of sleep disorder in patients transferred out of ICU in the early stages. A total of 405 patients transferred from the intensive care department of the Affiliated Hospital of Nantong University in China from May 2022 to December 2022 were selected as the study subjects by convenience sampling method and were divided into a modelling group of 270 patients and an internal verification group of 135 patients. A total of 67 ICU patients admitted to the same hospital from July 2023 to September 2023 were selected as the external validation group. General data and clinical data questionnaires were used to collect information on the influencing factors. The Pittsburgh Sleep Quality Index (PSQI) was used for follow-up 2 weeks after ICU transfer. According to the follow-up results, the patients were divided into a non-sleep disorder group and a sleep disorder group. Univariate analysis was used to analyse the risk factors of sleep disorders in ICU patients. To avoid multicollinearity, LASSO regression was used to filter variables. Through binary logistic regression, the forward step method and likelihood ratio test were selected to further screen the variables. R language was used to establish a riskprediction model and draw a column graph. Receiver operating characteristic (ROC) and Hosmer-Lemeshow (H-L) tests were used to verify the prediction effect of the model. The influencing factors for sleep disorders in patients transferred out of ICU were pre-hospital sleep disturbance [Odds Ratio: 4.467, 95% CI (1.191-16.749), p = .026], APACHE II score ≥15 [Odds Ratio: 6.452, 95% CI (1.777-23.434), p = .005], moderate comorbidities [Odds Ratio: 18.045, 95% CI (1.568-66.731), p = .015], severe comorbidities [Odds Ratio:12.083, 95% CI (2.785-116.911), p = .002], remifentanil use [Odds Ratio: 12.083, 95% CI (2.716-53.756), p = .001], RCSQ total score <45 [Odds Ratio: 18.037, 95% CI (4.907-66.300), p < .001], moderate depression [Odds Ratio: 70.659, 95% CI (8.195-609.219), p < .001] and severe depression [Odds Ratio: 8.563, 95% CI (1.165-62.936), p = .035]. The prediction model was as follows: Logit (P) = -10.529 + 1.497* (pre-hospital sleep disorder) +1.864* (APACHE II score ≥15) +2.325* (moderate complication) +2.893* (severe complication) +2.492* (remifentanil use) +2.892* (RCSQ) Total score <45 +0.574* (mild depression) +4.258* (moderate depression) +2.147* (major depression). The area under the ROC curve of the prediction model was 0.916, the sensitivity was 81.9%, and the specificity was 96.0%. The H-L test showed that χ2 = 4.301, p = .829 (p > .05). The area under the internal verified ROC curve (AUC) was 0.896, and the H-L test revealed that χ2 = 3.683 and p = .885 (p > .05). The area under the external verified ROC curve was 0.739, the sensitivity was 72.7%, and the specificity was 64.7%. The H-L test results showed that χ2 = 4.683, p = .699 (p > .05), indicating that the model had a good prediction effect. The risk histogram of sleep disorders in ICU patients can predict the risk of sleep disorders in ICU patients, and can be used to assess the high risk of sleep disorders in ICU patients, and can help nurses to formulate corresponding intervention measures. The dynamic nomogram can be used to systematically monitor various factors associated with sleep disorders, and the prevention of sleep disorders can improve outcomes and quality of life for patients discharged from the ICU. Furthermore, nurses need to develop and accurately apply nursing interventions, taking into account all relevant variables, thereby reducing the occurrence of sleep disorders.

Background:Many psychiatric disorders present with symptoms involving disordered sleep. The overlay of sleep and psychiatric disorders, though ubiquitous, remains less well understood. The evolution of diagnostic manuals for sleep and psychiatric disorders has also complicated our understanding of this intersection.Aim:Hence, this current review was conducted to explore the progress of Indian research on sleep disorders in patients with mental illness.Methods:In order to cover the wide spectrum of our scope of review, it was decided to conduct a narrative review. The search was conducted in PubMed and Google Scholar, and the recruited studies were all research work done in India on sleep disorders in patients with mental illness.Results:The review could identify substantial volume of research published from India on sleep disorders in patients with mental illness. The prominent sleep disorders that were addressed included restless legs syndrome, insomnia, hypersomnia, parasomnia, and sleep‐related breathing disorders. The studies were mostly clinic‐based and observational in nature.Conclusion:To conclude, the relationship of psychiatric disorders and sleep disorders has been in the forefront of research in the India. There is a high prevalence of sleep disorders in Indian patients with psychiatric ailments. However, it was found that the research attempts have been largely clustered toward certain selected disorders and there is a need for conducting more studies using more rigorous designs.

This study examined the relationship between sleep disorders and the risk of dementia in patients with newly diagnosed type 2 diabetes. This study used the Korean Health Screening Cohort data and included 39 135 subjects aged ≥40 years with new-onset type 2 diabetes between 2004 and 2007, with follow-up throughout 2013. Sleep disorders were measured by F51(sleep disorders not due to a substance or known physiological condition) or G47(sleep disorders) under International Classification of Diseases, Tenth Revision (ICD-10) codes as a primary diagnosis, and the adjusted hazard ratio (AHR) and 95% CI of all-cause dementia, Alzheimer disease, vascular dementia, and other dementia were estimated using multivariable Cox proportional hazards regression models. In the patients with type 2 diabetes with an age range between 42 and 84 years (M = 57.8, SD = 9.5), this study identified 2059 events of dementia during an average follow-up time of 5.7 years. In patients with type 2 diabetes, subjects with sleep disorders were associated with an increased risk of all-cause dementia (AHR, 1.46; 95% CI, 1.19-1.80), Alzheimer disease (AHR, 1.39; 95% CI, 1.02-1.88), and other dementia (AHR, 1.69; 95% CI, 1.23-2.31) compared to those without sleep disorders. Men (AHR, 1.93; 95% CI, 1.42-2.62) and older adults (AHR, 1.70; 95% CI, 1.35-2.15) with sleep disorders were associated with an increased risk of dementia than their counterparts without sleep disorders among patients with type 2 diabetes. These findings suggest that sleep disorders are significantly associated with an increased risk of dementia in patients with new-onset type 2 diabetes.

Objective: To investigate the clinical characteristics and correlated factors of preoperative sleep disorders in patients undergoing various types of cardiac surgery. Methods: The data of patients at the Structural Heart Surgery Center of Beijing Anzhen Hospital, Capital Medical University, from April 2023 to February 2024 were retrospectively collected. Patients were categorized into five groups based on cardiac surgical diagnosis: coronary heart disease, valvular disease, large vessel disease, congenital heart disease, and others. Each group was further subdivided into normal sleep (NS) and sleep disorder (SD) groups based on the Pittsburgh Sleep Quality Index (PSQI) scores. Demographic information, cognitive function, psychiatric symptoms, and other relevant data were collected. Clinical characteristics were compared between groups, and factors associated with preoperative sleep disorders were analyzed using multivariate logistic regression. Results: A total of 1 016 patients aged (58.6±12.7) years were included in the study, including 701 males and 315 females. The incidence of SD was 45.6% (463/1 016). Multivariate logistic regression analysis showed that aging was a risk factor for sleep disorders in patients with coronary heart disease (OR=1.050, 95%CI: 1.026-1.077) and valvular disease (OR=1.033, 95%CI: 1.013-1.053). High Self-rating Depression Scale (SDS) score was a risk factor for sleep disorders in patients with valvular disease (OR=1.050, 95%CI: 1.013-1.091). High score on the Montreal Cognitive Assessment (MoCA) subitem-abstraction ability was a protective factor for sleep disorders in patients with coronary heart disease (OR=0.695, 95%CI: 0.490-0.981). Conclusions: The risk factors of preoperative sleep disorders in cardiac surgery patients vary based on the type of cardiac disease. Aging, depression and abstraction ability correlate with sleep disorders in cardiac surgical patients.

Introduction The problem of sleep disorders plays a significant role in the functioning of people in the contemporary world, particularly affecting cardiac patients. It entails a series of consequences that impact health. The study analyzed the occurrence of sleep disorders among cardiac patients. Purpose The project aimed to assess the available literature regarding described sleep disorders in patients with cardiovascular diseases and to analyze the impact of sleep disorders on the functioning of cardiac patients. Methods Materials available in PubMed and Google Scholar were analyzed using keywords such as "sleep disorders," "insomnia," "cardiovascular disease," "heart attack," "heart failure," "hypertension," "coronary artery disease" in various configurations. A comprehensive analysis of publications was conducted to identify studies on sleep disorders in cardiac patients, focusing on risk factors and management strategies for sleep problems in this patient group. Results Sleep disorders occur in cardiac patients and significantly affect their health. Sleep disorders also increase cardiovascular risk in healthy individuals. Sleep disorder management methods include problem recognition, lifestyle modifications, pharmacotherapy, and behavioral interventions. A crucial aspect of care appears to be the need for diagnosing sleep problems in cardiac patients and implementing integrated multidisciplinary care. Conclusions Sleep disorders pose a significant risk for cardiac patients, requiring an interdisciplinary therapeutic approach. Future research should assess the scale of sleep disorders in cardiac patients in Poland, as well as identify factors influencing sleep disorders in this patient group. Subsequently, treatment strategies and integrated care should be developed.

This study aimed to investigate the risk factors related to sleep disorders in patients undergoing hemodialysis using a nomogram model. A cross-sectional survey was conducted in a hospital in Zhejiang province, China from January 1, 2020, to November 31, 2022 among patients undergoing hemodialysis. Dietary intake was assessed applying a Food Frequency Questionnaire. Sleep quality was evaluated by the Pittsburgh Sleep Quality Index. Evaluation of risk factors related to sleep disorders in patients undergoing hemodialysis was using a nomogram model. This study included 201 patients and 87 individuals (43.3%, 87/201) exhibited sleep disorders. The average age of included patients was 51.1 ± 9.0 years, with males accounting for 55.7% (112/201). Results from nomogram model exhibited that potential risk factors for sleep disorders in patients undergoing hemodialysis included female, advanced age, increased creatinine and alanine aminotransferase levels, as well as higher red meat consumption. Inversely, protective factors against sleep disorders in these patients included higher consumption of poultry, fish, vegetables, and dietary fiber. The C-index demonstrated a high level of discriminative ability (0.922). This study found that age, sex, and dietary factors were associated with sleep disorders in hemodialysis patients. Hemodialysis patients with sleep disorders require urgent dietary guidance.

Sleep disorder is a common comorbidity in chronic obstructive pulmonary disease (COPD). We aim to explore the potential association between daily sitting time (DST), leisure-time physical activity (LTPA) and sleep disorders in COPD patients. The sleep, LTPA, and DST data of participants with COPD were extracted from the National Health and Nutrition Examination Survey (NHANES) portal (2007-2012), basing on Global Physical Activity Questionnaire. The t-test, Mann-Whitney test, or chi-square test were employed to analyze the differences between two groups. The weighted binomial logistic regression model was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of DST and LTPA on sleep disorders. The analyses were conducted from April 1 to July 1, 2023. A total of 2063 COPD samples were included in this work, of which 58% had LTPA < 150 min/wk and 48% had DST > 6h. Patients with sleep disorders had longer sedentary time (DST > 6h: 151, DST > 8h: 105) and less physical activity (LTPA < 150min/wk: 185). Longer sedentary time was correlated with a higher risk of sleep disorders, while LTPA showed no significant correlation with sleep disorders. The conjoint analysis revealed that the risk of sleep disorders in patients with LTPA <150 min/wk and DST > 8h was 5.88 times (95% CI: 1.80-19.2) great than that of patients with LTPA≥150 min/wk and DST < 4h. COPD patients often lacked physical activity and exhibited sedentary behaviors. Long-term sedentary behavior was associated with elevated risk of sleep disorders in COPD patients. More light intensity physical activity and supervised exercise programs are probably good choices to prevent sleep disorders in COPD population.

The article presents analysis of current research on sleep disorders in patients with type 2 diabetes mellitus (T2DM). The mechanisms underlying the relationship between insomnia and glycemic control are complex, as both DM can cause sleep disorders and insomnia can worsen the course of diabetes. It is well known that both short (&lt; 6 hours) and long (&gt; 8 hours) sleep durations are associated with an elevated risk of diabetes development. The reported prevalence of sleep disorders in diabetes patients ranges between 28.0% and 59.1%. Our investigation performed in Lviv with the use of Pittsburgh Sleep Quality Index (PSQI) questionnaire, identified that 46.2% of T2DM patients experienced sleep disorders. A comprehensive literature review also unveils association between DM and diverse sleep disorders such as insomnia, circadian rhythm disturbances, obstructive sleep apnea (OSA), and restless legs syndrome (RLS). The article furnishes insights into the classification, diagnostic principles, and treatment modalities for these disorders. Referral of patients to sleep specialists for the management of sleep disorders and the integration of sleep hygiene into diabetes care can effectively mitigate symptoms, forestall DM complications, and enhance patients’ quality of life. Circadian molecules like nobiletin, REV‑ERB agonists, and CRY stabilizers have demonstrated efficacy in preclinical studies and hold potential for the development of novel treatments for conditions associated with circadian dysregulation. Considering the frequency of detection of sleep disorders in T2DM patients according to the modern literary sources and own research, the study of this problem is important for the development of an algorithm for the examination of such patients, namely the need for endocrinologists to pay attention to the sleep status of patients and, if necessary, to refer them to somnologists. Further investigation into the etiology of sleep disorders in T2DM patients and their correlation with carbohydrate metabolism indicators exhibits promise. It is imperative to explore avenues to address these causes by complementing the primary therapy for T2DM.

Sleep Disorders in Neurorehabilitation

ObjectiveBoth sleep disorders and BPD are prevalent in the population, and one is often a comorbidity of the other. This narrative review aims to assess contemporary literature and scientific databases to provide the current state of knowledge about sleep disorders in patients with borderline personality disorder (BPD) and clinical suggestions for managing sleep disorders in BPD patients and future research direction.MethodsArticles were acquired via PubMed and Web of Science, and papers published between January 1980 and October 2020 were extracted. Authors made a series of literature searches using the keywords: Sleep problems, Insomnia, Nightmares, Obstructive sleep apnea, Borderline personality disorder. The inclusion criteria were: published in peer-reviewed journals; studies in humans; or reviews on the related topic; English language. The exclusion criteria were: abstracts from conferences; commentaries; subjects younger than 18 years. After an inspection of the full texts, 42 papers from 101 were selected. Secondary documents from the reference lists of the primary designated papers were searched, assessed for suitability, and included. In total, 71 papers were included in the review process.ResultsSleep disturbance is common among patients with BPD. Nevertheless, the number of investigations is limited, and the prevalence differs between 5–45%. Studies assessing objective changes in sleep architecture in BPD show inconsistent results. Some of them identify REM sleep changes and a decrease in slow-wave sleep, while other studies found no objective sleep architecture changes. There is also a higher prevalence of nightmares in patients with BPD. Untreated insomnia can worsen BPD symptoms via interference with emotional regulation. BPD itself seems to influence the subjective quality of sleep significantly. Proper diagnosis and treatment of sleep disorders in patients with BPD could lead to better results in therapy. Psychotherapeutic approaches can improve both sleep disorders and BPD symptoms.ConclusionRecognising and managing sleep disorders in patients with BPD may help alleviate the disorder’s symptoms. Treatment of people with BPD may be more effective if the treatment plan explicitly addresses sleep problems. Further research is needed to reach reliable conclusions.

Introduction: Sleep disorders, especially insomnia, are very common in different kinds of cancers, but their prevalence and incidence are not well-known. Disturbed sleep in cancer is caused by different reasons and usually appears as a comorbid disorder to different somatic and psychiatric diagnoses, psychological disturbances and treatment methods. There can be many different predictors for sleep disturbances in these vulnerable groups, such as pre-existing sleep disorders, caused by the mental status in cancer or as side effect of the cancer treatment. Methods: A systematic literature review of 8073 studies was conducted on the topic of sleep and sleep disorders in cancer patients. The articles were identified though PubMed, PsycInfo and Web of Knowledge, and a total number of 89 publications were qualified for analysis. Results: The identified eighty-nine studies were analyzed on the topic of sleep and sleep disorders in cancer, twenty-six studies on sleep and fatigue in cancer and sixty-one studies on the topic of sleep disorders in cancer. The prevalence of sleep disturbences and/or sleep disorders in cancer was up to 95%. Discussion: Sleep disturbances and sleep disorders (such as insomnia, OSAS, narcolepsy and RLS; REM-SBD) in cancer patients can be associated with different conditions. Side effects of cancer treatment and cancer-related psychological dysfunctions can be instigated by sleep disturbances and sleep disorders in these patients, especially insomnia and OSAS are common. An evidence-based treatment is necessary for concomitant mental and/or physical states.

This study aimed at identifying factors that are associated with sleep disorders in Chinese patients on continuous ambulatory peritoneal dialysis (CAPD). Questionnaire survey. Renal dialysis unit of a tertiary-care hospital. 179 Chinese patients on CAPD. The quantity and quality of sleep were compared between CAPD patients with and without self-reported sleep disorders. Demographic variables, personality traits, behavioral factors, somatic symptoms, and clinical parameters were correlated with the presence of sleep disorders. The mean age of the patients was 61 +/- 12 years and the male-to-female ratio was 1:1.3. The mean duration of CAPD was 47 +/- 42 months. 110 patients (61%) had self-reported sleep disorders. Among patients with self-reported sleep disorders, difficulty falling asleep was the most frequent complaint (74.5%), followed by frequent awakening (68%) and early morning waking (68%). The mean duration of sleep among these patients was 4.6 +/- 2.2 hours, versus 7.3 +/- 1.4 hours in patients without self- reported sleep disorders. Three personality traits (anxiety, worry, and sadness) and two somatic symptoms (bone pain and arthralgia) were the factors significantly associated with sleep disorders. Patients with sleep disorders also more frequently reported certain symptoms suggestive of sleep apnea. Demographic variables, behavioral factors (e.g., caffeine or alcohol intake), and clinical parameters (e.g., adequacy of dialysis, body mass index, hemoglobin, albumin, parathyroid hormone levels) did not differ between patients with and without sleep disorders. Sleep disorders are prevalent among Chinese CAPD patients. Personality traits (anxiety, worry, and sadness) and somatic symptoms (bone pain and arthralgia) were the factors significantly associated with sleep disorders in this patient population. Behavioral factors, demographic variables, and clinical parameters did not appear to predict sleep disorders. Further studies evaluating the impact of various psychological factors on sleep disorders among CAPD patients are warranted.

Introduction: chronic hemodialysis is a current treatment in patients with advanced renal failure, the presence of sleep disorders is characteristic due to the comorbidities they present and the water overload altering their quality of life. Sleep disorders in patients with hemodialysis are a risk factor for morbidity and mortality and they should receive timely treatment that will determine the evolution of the disease. Objective: descriptive, cross-sectional study to determine the prevalence and describe the clinical characteristics of sleep disorders in adult patients who are in a chronic hemodialysis treatment center. Results: a total of 27 patients were included. 55% men and 45% women, the average age was 60 years. 81% of the patients had more than 3 sessions and between 6 months and 1 year of stay in treatment. 77.7% of the patients were highly likely to present a sleep disorder associated with obstructive sleep apnea syndrome by standardized scales predicting sleep disorders. Conclusion: there is a large percentage of patients with a probability of presenting sleep apnea in the population that is on chronic hemodialysis. It is necessary to perform standardized scales of probability of sleep disorders in patients and confirm the diagnosis in a timely manner and start treatment as soon as possible. Improving their quality of life and reducing their morbidity and mortality.

Sleeping Disorders in Patients With End-Stage Renal Disease and Chronic Kidney Disease

The aim of this study was to investigate the relationship between sleep disorders and C-reactive protein (CRP), hallmark of inflammation, and other biomarkers which may alter in hemodialysis patients. Our study included 108 patients who were dialyzed at least for 3 months. Before hemodialysis, blood samples were collected and serum levels of CRP, ferritin, albumin, phosphorus, parathyroid hormone, and hemoglobin were measured. Sleep disorders were confirmed by the presence of at least one of following criteria: insomnia, restless leg syndrome (RLS), obstructive sleep apnea syndrome (OSAS), narcolepsy, nightmare, sleepwalking, and poor sleep. 82.4% of patients demonstrated sleep disorders; insomnia (50%), RLS (32.4%), OSAS (7.4%), narcolepsy (15.7%), nightmare (15.7%), sleepwalking (0.9%), and poor sleep (71.3%). Our results revealed that CRP ≥3.8 μg/ml and advanced age were significantly associated with sleep disorders in these patients (p = 0.004 and p = 0.006, respectively). We concluded that inflammation has a close relation with sleep disorders in hemodialysis patients.