Specific Sleep Disorders Research Articles

Management of Sleep Disorders in the Elderly

Healthy elderly can adapt to physiological changes in their sleep. The prevalence of sleep disorders and insomnia in particular is high in the elderly. They are often associated with one or more somatic and/or psychiatric conditions that they aggravate. In clinical practice, it is important to assess whether the sleep complaint fits into the framework of: 1) Physiological changes in the sleep-wake cycle during the day or circadian rhythms related to aging. 2) Defective lifestyle habits. 3) A specific sleep disorder, 4) A somatic or psychiatric condition that requires specific treatment; The management of sleep disorders in elderly should not be minimized and requires rigorous and multidisciplinary management. Psychotherapies are preferred as first-line treatment. In the case where therapeutic prescription is necessary, low doses must be given, and adjusted according to the terrain and the evolution. Through this article, we will try, through the latest recommendations, to make an update on the management of these disorders in the elderly, who are a weakened terrain associating psychiatric and somatic comorbidities.

Current perspectives and trends in acupuncture for sleep disorders: a bibliometric analysis.

Limitations of conventional treatment methods for sleep disorders have driven the use and development of complementary and alternative therapies such as acupuncture. However, despite the surge in related studies, there is still a lack of visual analysis and detailed elaboration regarding the current status, international collaborations, and research hotspots of acupuncture for sleep disorders. We conducted a bibliometric analysis of publications on acupuncture for sleep disorders using the Web of Science Core Collection database from 2004 to 2023. We utilized the R package "bibliometrix" to count publications and citations, VOSviewer to create an inter-institutional referencing network, and CiteSpace to identify references and keywords with the highest citation bursts. Additionally, we employed a bibliometric online analysis platform designed for analyzing national partnerships. A total of 432 pertinent papers were retrieved, with China being the most prolific contributor, accounting for 61.6% of the publications, followed by the United States and South Korea. Despite China's high output, its average article citation rate and proportion of international collaborations were notably lower than those of the United States. Key research institutions such as the University of Hong Kong, Shanghai University of Traditional Chinese Medicine, Memorial Sloan Kettering Cancer Center, and Guangzhou University of Chinese Medicine have played significant roles in this field. Among authors, Ka-Fai Chung from the University of Hong Kong stood out as the most productive. In terms of journals, MEDICINE was the most active, while SLEEP was considered the most authoritative. The clinical effects of acupuncture for insomnia have garnered significant attention in recent years, with electroacupuncture emerging as the prevailing technique for addressing sleep disorders. This bibliometric study effectively outlines the basic framework of knowledge surrounding acupuncture for sleep disorders over the past two decades, covering publications, countries, institutions, authors, and sources. It highlights promising clinical effects and underlying mechanisms of acupuncture, particularly for secondary insomnia and specific sleep disorders like restless legs syndrome. Moving forward, the focus and challenge for future research lie in the development of standardized study protocols and harmonization of efficacy assessment metrics.

Sleep disturbances associated with DEAF1 pathogenic variants.

Neurodevelopmental disorders and sleep disturbances share genetic risk factors. DEAF1 genetic variants are associated with rare syndromes in which sleep disturbances are commonly reported, yet the specific sleep disorders in these patients, and the molecular mechanisms underlying this association, are unknown. We aimed to pinpoint specific biological processes that may be disrupted by pathogenic variants in this gene, comparing a list of DEAF1 regulatory target genes with a list of insomnia-associated genes, and using the intersect gene list as the input for pathway enrichment analysis. Thirty-nine DEAF1 regulatory targets were also identified as insomnia-associated genes, and the intersecting gene list was found to be strongly associated with immune processes, ubiquitin-mediated proteolysis pathways and regulation of the cell cycle. This preliminary study highlights pathways that may be disrupted by DEAF1 pathogenic mutations and might be putative factors underlying the manifestation of insomnia in patients harboring such variants.

Gut microbiome and metabolic pathways linked to sleep quality.

Sleep quality is a vital determinant of human health as sleep disorders are associated with cognitive deficits, and chronic sleep deprivation is associated with a broad range of health complications. Previous studies on the association between the gut microbiome and sleep quality have been constrained by small sample sizes or have focused on specific sleep disorders, thus yielding inconsistent results. Herein, we investigated the relationship between microbial composition and sleep quality in a cohort of 159 Koreans. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI), determined through a self-administered questionnaire. Gut microbiome analyses were performed using 16S rRNA amplicons. We found no direct correlation between microbial alpha diversity metrics and sleep; however, we identified differences in beta diversity among sleep quality groups (with a PSQI score > 5 indicating poor sleep quality and PSQI ≤5 indicating good sleep quality). We also found differential microbial signatures (Bacteroides, Prevotella 9, and Faecalibacterium) among the groups. Furthermore, functional metabolic pathway profiles revealed significant linear correlations of the L-arginine and L-tryptophan biosynthetic pathways as well as 4-aminobutanoate degradation with sleep status. In particular, Faecalibacterium prausnitzii, which harbors these metabolic pathways, showed differences between sleep quality groups and a linear association with sleep quality scores and was thus identified as the species most strongly associated with sleep status. This study provides a significant advance in our understanding of the relationship between gut microbiota and sleep regulation. The current findings provide a basis for further research into potential therapeutic strategies for sleep disorders targeting the gut microbiome.

Utilizing Multi-Class Classification Methods for Automated Sleep Disorder Prediction

Even from infancy, a human’s day-life alternates from a period of wakefulness to a period of sleep at night, during the 24-hour cycle. Sleep is a normal process necessary for human physical and mental health. A lack of sleep makes it difficult to control emotions and behaviour, reduces productivity at work, and can even increase stress or depression. In addition, poor sleep affects health; when sleep is insufficient, the chances of developing serious diseases greatly increase. Researchers in sleep medicine have identified an extensive list of sleep disorders, and thus leveraged Artificial Intelligence (AI) to automate their analysis and gain a deeper understanding of sleep patterns and related disorders. In this research, we seek a Machine Learning (ML) solution that will allow for efficient classification of unlabeled instances as being Sleep Apnea, Insomnia or Normal (subjects without a specific sleep disorder) by assessing the performance of two well-established strategies for multi-class classification tasks: the One-Vs-All (OVA) and One-Vs-One (OVO). In the context of the specific strategies, two well-known binary classification models were assumed, Logistic Regression (LR) and Support Vector Machines (SVMs). Both strategies’ validity was verified upon a dataset of diverse information related to the profiles (anthropometric data, sleep metrics, lifestyle and cardiovascular health factors) of potential patients or individuals not exhibiting any specific sleep disorder. Performance evaluation was carried out by comparing the weighted average results in all involved classes that represent these two specific sleep disorders and no-disorder occurrence; accuracy, kappa score, precision, recall, f-measure, and Area Under the ROC curve (AUC) were recorded and compared to identify an effective and robust model and strategy, both class-wise and on average. The experimental evaluation unveiled that after feature selection, 2-degree polynomial SVM under both strategies was the least complex and most efficient, recording an accuracy of 91.44%, a kappa score of 84.97%, precision, recall and f-measure equal to 0.914, and an AUC of 0.927.

A Mendelian randomization investigation of the causal association between the gut microbiota and sleep disorders.

Increasing numbers of people are suffering from sleep disorders. The gut microbiota of these individuals differs significantly. However, no reports are available on the causal associations between specific gut microbiota and sleep disorders. Data on gut genera were obtained from the MiBioGen consortium. Twenty-four cohorts with 18,340 individuals of European origin were included. Sleep disorder data, which included 216,454 European individuals, were retrieved from the FinnGen Biobank. Subsequently, two-sample Mendelian randomization was performed to analyze associations between sleep disorders and specific components of the gut microbiota. Inverse variance weighting (IVW) revealed a negative correlation between Coprobacter and sleep disorders (OR = 0.797, 95% CI = 0.66-0.96, and p = 0.016), a positive correlation between Lachnospiraceae and sleep disorders (OR = 1.429, 95% CI = 1.03-1.98, and p = 0.032), a negative association between Oscillospira and sleep disorders (OR = 0.745, 95% CI = 0.56-0.98, and p = 0.038), and a negative association between Peptococcus and sleep disorders (OR = 0.858, 95% CI = 0.74-0.99, p = 0.039). A significant causal relationship was found between four specific gut microbiota and sleep disorders. One family, Lachnospiraceae, was observed to increase the risk of sleep disorders, while three genera, namely, Coprobacter, Oscillospira, and Peptococcus, could reduce the risk of sleep disorders. However, further investigations are needed to confirm the specific mechanisms by which the gut microbiota affects sleep.

From trenches to technology: a narrative review of sleep medicine in the military.

Thomas CL, Carr K, Yang F, etal. From trenches to technology: a narrative review of sleep medicine in the military. J Clin Sleep Med. 2024;20(6):973-981.

Current Pharmacological Treatment for Sleep Disorders in Children and Adolescents with Autism Spectrum Disorder

Sleep disorders are very common in children and adolescents with Autism Spectrum Disorder (ASD) and can negatively impact their lives, mental health, developmental processes, families' lives, and emotional well-being. It is essential to determine the specific sleep disorder and its underlying cause in treatment planning. Currently, nonpharmacological and pharmacological interventions are the main treatments for improving sleep disorders in children and adolescents with ASD. If nonpharmacological strategies are unsuccessful or difficult to implement, medications should be considered and used in conjunction with them. Melatonin, behavioral interventions, and parent education are the most effective treatments to improve sleep, relative to other pharmacological treatments. Medications used to treat sleep disorders in these children are used off-label. Melatonin appearing to be safe and effective may be an evidence-based and efficacious first-line treatment for treating insomnia symptoms in children and adolescents with ASD. Antipsychotics (e.g.low dose quetiapine), antidepressants with strong sedative effects such as trazodone and mirtazapine, antihistamines (e.g.diphenhydramine, niaprazine), alpha-adrenergic drugs (e.g. clonidine), benzodiazepines (e.g.clonazepam) and other hypnotic drugs, anticonvulsants (e.g. gabapentin), Alzheimer's drugs (e..g donepezil), superoxide and iron treatment are other drugs used in pharmacological treatment. Depending on the type of sleep disorders and the presence of comorbidities, the most effective pharmacological treatment should be selected on a case-by-case basis.

Daytime sleepiness in depression—underestimated in psychiatric inpatients

Abstract Background Sleep disorders are among the most common symptoms of depression. Both the ICD-10/11 and DSM‑5 list sleep disorders of all types as diagnostic criteria for depression, but these are not defined in detail. Objective This study focused on the prevalence of daytime sleepiness and associated sleep disorders in patients diagnosed with a severe depressive episode. Materials and methods In total, 192 inpatients with a moderate/severe depressive episode from an open acute psychiatric ward were included. Sleep history immediately after admission and sleep-related questionnaires, such as the Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), and Regensburg Insomnia Scale (RIS), were collected. Polysomnographic assessment was performed in 82 patients with suspected sleep disorders. Patient groups (e.g., with and without sleepiness or apnea) were compared. Results The prevalence of daytime sleepiness (ESS > 10) was 25.3%. Fatigue and insomnia were reported in 66.7 and 75.7% of patients, respectively. Polysomnography revealed a prevalence of sleep apnea of 18.2%, and sleep apnea was newly diagnosed in 80% of these patients. Daytime sleepiness was more common in patients with undiagnosed sleep apnea. Patients with daytime sleepiness had more fatigue but did not have more severe depression. Conclusion The present results highlight the importance of assessing sleep history in psychiatric patients, especially those with depression. The ESS may be a useful tool to specifically assess daytime sleepiness as opposed to depression-related fatigue. A systematic assessment of sleepiness and specific sleep disorders, in particular sleep apnea, might contribute to improved treatment of inpatients with depression.

Common Childhood Sleep Problems and Disorders.

Sleep insufficiency and disturbances affect the physical, cognitive, and emotional well-being of children. To perform a narrative review on common sleep problems and disorders encountered in primary care for children and adolescents. A search of English literature in the Pubmed and Google Scholar databases published from 1 January 2000 till 31 October 2021 was conducted with the keywords "sleep problem" or "sleep disorder" and "child" or "adolescent". Findings in the relevant articles and cross-references were compiled. Sleep duration and habits of children vary widely across countries with different cultural backgrounds. There is robust evidence to support the promotion of positive bedtime routines and sleep hygiene as prevention and management of sleep problems. 15-70% of parents reported their children having sleep problems or disturbances. Common sleep complaints include difficulty in initiation or maintenance of sleep, abnormal behaviors or movements, snoring or abnormal breathing, and excessive daytime sleepiness. Comprehensive sleep history and a sleep diary are the first steps for evaluation. Home video and actigraphy may be used as preliminary tools to confirm the history. Referrals to a sleep specialist for polysomnography and other tests are needed, if suspecting specific sleep disorders, such as obstructive sleep apnea and narcolepsy, needs timely intervention. Common sleep disorders in different age groups encountered in primary care are reviewed with clinical features, indications for evaluation, and treatment options summarized. Screening for sleep problems shall be an integral part of each child's health care visit. It is important to evaluate the impact of common sleep problems and identify specific sleep disorders for early intervention to prevent long-term adverse outcomes.

Systematic item content and overlap analysis of self-reported generic and specific sleep disorders screening questionnaires in adults

Systematic item content and overlap analysis of self-reported generic and specific sleep disorders screening questionnaires in adults

Association between sleep disorders and health care utilization in children with chronic medical conditions: a Medicaid claims data analysis.

To examine the risk of increased health care utilization (HU) linked to individual sleep disorders in children with chronic medical conditions. Medicaid claims data from a cohort of 16,325 children enrolled in the Coordinated Healthcare for Complex Kids (CHECK) project were used. Sleep disorders and chronic medical conditions were identified using International Classification of Diseases, Ninth, and 10th Revision, codes. Three HU groups were identified based on participants' prior hospitalizations and emergency department (ED) visits in the 12 months prior to enrollment: low (no hospitalization or ED visit), medium (1-2 hospitalizations or 1-3 ED visits), and high (≥ 3 hospitalizations or ≥ 4 ED visits). The odds of being in an increased HU group associated with specific sleep disorders after controlling for confounding factors were examined. Children with chronic medical conditions and any sleep disorder had nearly twice the odds (odds ratio = 1.83; 95% confidence interval: 1.67-2.01) of being in an increased HU group compared with those without a sleep disorder. The odds of being in the increased HU group varied among sleep disorders. Only sleep-disordered breathing (odds ratio = 1.51; 95% confidence interval : 1.17-1.95), insomnia (odds ratio = 1.46; 95% confidence interval : 1.06-2.02), and circadian rhythm sleep disorder (odds ratio = 2.45; 95% confidence interval : 1.07-5.64) increased those odds. Younger age and being White were also linked to increased HU. Sleep disorders are associated with increased risk of heightened HU (ED visits and/or hospitalizations) in children with chronic medical conditions. This risk varies by specific sleep disorders. These findings indicate the need for careful evaluation and management of sleep disorders in this high-risk cohort. Adavadkar PA, Brooks L, Pappalardo AA, Schwartz A, Rasinski K, Martin MA. Association between sleep disorders and health care utilization in children with chronic medical conditions: a Medicaid claims data analysis. J Clin Sleep Med. 2024;20(4):595-601.

P155: Circadian Rhythms and Alzheimer's Disease

Introduction:Major neurocognitive disorder (or simply Dementia) is one of the main causes of disability and burden disease to caregivers and the health system, and a frequent cause of mortality worldwide. Alzheimer`s disease (AD) is the most common type (60-70%).AD is a progressive neurodegenerative disorder characterized by amyloid-β (Aβ) deposition, causing neuronal and synaptic loss with subsequent cognitive disfunction.There is cumulating evidence that sleep disturbances are associated with several pathological conditions, and AD is one of these. The prevalence and severity of sleep disorders is significant in AD patients, with sleep disturbances often precede its clinical diagnosis in many years. Some studies focus on possible mechanisms by which (abnormal) sleep participate in AD pathogenesis, and concluded individuals with sleep disturbances are at higher risk of developing dementia.Objectives:To highlight the current evidence on whether sleep disorders could precipitate or accelerate the clinical course of AD.Methods:Non-systematic review about sleep abnormalities and AD pathogenesis.Results:Several authors described a two-way relationship between sleep and amyloid pathology - sleep deprivation would lead to increased production and decreased clearance of Aβ; once Aβ is accumulated it results in more disrupted sleep, with an increase of Aβ production during wakefulness and a decrease of its clearance during sleep.Recent data showed that sleep continuity and architecture (decreased total sleep time, slow-wave sleep, and REM sleep) are disturbed in AD patients.Otherwise, sleep deprivation may be associated with decreased glymphatic system clearance, leading to accumulation of neurotoxic proteins, particularly Aβ (and tau). It`s also associated with proinflammatory states due to accumulation of reactive oxygen species, nucleotides and proteins during wakefulness, which leads to immune response that causes neuronal dysfunction and cellular death. Insomnia and sleep deprivation were also associated with activation of complement pathway and immunoglobulins secretion. Many studies suggest chronic sleep disruption changes blood–brain barrier structure and function leading to Aβ accumulation.Conclusions:There is emerging evidence that points sleep disturbances as both a potential marker for AD pathology and risk predictor of developing the disease. Future investigations should evaluate the relationship between specific sleep disorders and AD physiopathology.

Per- and polyfluoroalkyl substances and sleep health in U.S. adults, NHANES 2005–2014

BackgroundPer- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that induce oxidative inflammatory responses and disrupt the endocrine and central nervous systems, all of which can influence sleep. ObjectiveTo investigate the association between PFAS exposure and sleep health measures in U.S. adults. MethodsWe analyzed serum concentration data of four PFAS [perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] reported for 8913 adults in NHANES 2005–2014. Sleep outcomes, including trouble sleeping, having a diagnosis of sleep disorder, and recent daily sleep duration classified as insufficient or excessive sleep (<6 or >9 h/day) were examined. Weighted logistic regression was used to estimate the association between the sleep outcomes and each PFAS modeled continuously (log2) or in exposure tertiles. We applied quantile g-computation to estimate the effect of the four PFAS as a mixture on the sleep outcomes. We conducted a quantitative bias analysis to assess the potential influence of self-selection and uncontrolled confounding. ResultsWe observed some inverse associations between serum PFAS and trouble sleeping or sleep disorder, which were more consistent for PFOS (e.g., per log2-PFOS (ng/ml) and trouble sleeping OR = 0.93, 95%CI: 0.89, 0.98; sleep disorder OR = 0.89, 95%CI: 0.83, 0.95). Per quartile increase of the PFAS mixture was inversely associated with trouble sleeping and sleep disorder. No consistent associations were found for sleep duration across analyses. Our bias analysis suggests that the finding on sleep disorder could be explained by a moderate level of self-selection and negative confounding effects. ConclusionsWe found no evidence to suggest exposure to four legacy PFAS worsened self-reported sleep health among U.S. adults. While some inverse associations between specific PFAS and sleep disorder were observed, self-selection and uncontrolled confounding biases may play a role in these findings.

Sleep Disorders in Neuromuscular Diseases: A Narrative Review

Neuromuscular disorders (NMDs) encompass a highly diverse group of conditions that affect the skeletal muscles, peripheral nervous system, or motor endplate. Depending on the underlying disease, common characteristics include progressive muscle weakness and sensory disturbances, both of which can contribute to sleep disruption. Disorders of sleep are extremely frequent in NMDs and substantially co-determine overall morbidity, quality of life, and survival. As many NMDs currently lack a cure, supportive therapy is mandatory and includes appropriate management of sleep-related symptoms. Specific sleep disorders that may arise in NMDs include insomnia due to pain or leg muscle cramps, restless legs syndrome, and sleep-disordered breathing, notably obstructive sleep apnea and hypoventilation. This review article aims to comprehensively outline the clinical spectrum of sleep disorders and sleep properties associated with NMDs.

Sleep disorders in a naturalistic cohort of Dutch psychiatric outpatients: prevalence rates and associations with psychopathology symptom severity and well-being.

Sleep problems are very common in individuals with a mental disorder. Given the abundant evidence indicating the negative impact of disturbed sleep on mental health outcome, insight into the prevalence of all types of sleep disorders in specific mental disorders and neurodevelopmental conditions is of practical importance. Therefore, we estimated the prevalence of six types of sleep disorders with the Holland Sleep Disorders Questionnaire in an overall mental health sample (n = 1082) and separately for different mental and neurodevelopmental conditions. Furthermore, associations between specific sleep disorders, psychopathology and well-being were studied. The impact of the total number of sleep disorders on these associations was examined. Overall, 46.2% of all participants scored above the cut-off for having a sleep disorder. Specifically, 26.8% scored on insomnia, 12.1% on sleep breathing disorders, 9.7% on hypersomnia, 13.7% on circadian rhythm sleep-wake disorders, 11.2% on parasomnia, and 17.9% on sleep-related movement disorders. Most sleep disorders were associated with greater severity of psychopathology and lower well-being. These associations got stronger with an increasing number of sleep disorders. Our study revealed higher suspected prevalence of most sleep disorders in a mental disorder sample compared to the general population. Moreover, the presence of sleep disorder(s) was strongly associated with symptom severity and reduced well-being. These findings extend the notion that early detection and treatment of sleep disorders in mental health populations is essential for psychiatric outcome.

Assessment of Sleep Quality Among Adolescents and Adults With Self-Diagnosed Irritable Bowel Syndrome, in Jeddah, Saudi Arabia.

Background The frequency of irritable bowel syndrome (IBS) has increased significantly in the last ten years. Few studies were done in Saudi Arabia to assess the relationship between sleep quality and IBS. This study aims to assess the prevalence of IBS and its association with sleep quality among adolescents and adults in Saudi Arabia. Methods A cross-sectional study was done on 651 participants aged 15-65 years. An online questionnaire was used to collect data, including demographics; the Rome IV criteria (R4DQ) was used in the diagnosis of IBS, the IBS symptoms severity scale (IBS-SSS) assessed IBS symptoms and severity, and the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. Results Based on the Rome IV criteria, 25.7% of the participants had IBS. Among them, 23.3%, 17.9%, 47.3%, and 11.5% had IBS types constipation (C), diarrhea (D), mixed bowel habits (M), and undefined subtype (U), respectively. Mild, moderate, and severe IBS were found among 43.1%, 39.5%, and 17.4% of IBS cases, respectively. About 46% had poor sleep quality, which was significantly higher among those with younger mean age, females, and students. Patients with IBS exhibited a considerably greater prevalence of poor sleep quality, and IBS-C had the highest prevalence. Conclusion A correlation was found between poor sleep quality and the positive status of IBS diagnosis among adolescents and adults. An evaluation of specific sleep disorders among IBS patients is needed.

Sleep disorders in Lewy body dementia: Mechanisms, clinical relevance, and unanswered questions.

In Lewy body dementia (LBD), disturbances of sleep and/or arousal including insomnia, excessive daytime sleepiness, rapid eye movement (REM) sleep behavior disorder, obstructive sleep apnea, and restless leg syndrome are common. These disorders can each exert a significant negative impact on both patient and caregiver quality of life; however, their etiology is poorly understood. Little guidance is available for assessing and managing sleep disorders in LBD, and they remain under-diagnosed and under-treated. This review aims to (1) describe the specific sleep disorders which occur in LBD, considering their putative or potential mechanisms; (2) describe the history and diagnostic process for these disorders in LBD; and (3) summarize current evidence for their management in LBD and consider some of the ongoing and unanswered questions in this field and future research directions.

The Correlation of Sleep Disturbance and Location of Glioma Tumors: A Narrative Review.

Sleep disturbance can occur when sleep centers of the brain, regions that are responsible for coordinating and generating healthy amounts of sleep, are disrupted by glioma growth or surgical resection. Several disorders cause disruptions to the average duration, quality, or patterns of sleep, resulting in sleep disturbance. It is unknown whether specific sleep disorders can be reliably correlated with glioma growth, but there are sufficient numbers of case reports to suggest that a connection is possible. In this manuscript, these case reports and retrospective chart reviews are considered in the context of the current primary literature on sleep disturbance and glioma diagnosis to identify a new and useful connection which warrants further systematic and scientific examination in preclinical animal models. Confirmation of the relationship between disruption of the sleep centers in the brain and glioma location could have significant implications for diagnostics, treatment, monitoring of metastasis/recurrence, and end-of-life considerations.

0969 Severe persistent specific sleep disorders in post-acute sequelae of SARS-CoV-2

Abstract Introduction Viral infections have long been associated with sleep disorders, especially hypersomnia following the acute phase The Covid-19 epidemic has resulted in a post-viral syndrome called post-acute sequelae of SARS-CoV-2 (PASC), or Long-Covid. Sleep has been reported to be severely disturbed during acute Covid-19 infection, and is a major feature of PASC. Much of the subjective data is based on questionnaires, with a paucity of objective sleep evaluations including polysomnography. We share our early experience with diagnosis and management of sleep disorders in PASC. Methods PASC patients are seen in a dedicated Long-Covid clinic at the Beth Israel Deaconess Medical Center for a comprehensive evaluation. The patients presented with new onset persistent sleep impairments shortly following acute COVID-19 infection, without pre-existing sleep impairments, in association with a clinical diagnosis of long covid. Sleep symptoms (excessive sleepiness, hypersomnia/long sleep, and insomnia) are identified and those who consider these a key symptom are referred to the Covid Sleep Clinic, for formal sleep evaluation by RJT. Diagnostic evaluations include polysomnography (extended for hypersomnia diagnosis), Multiple Sleep Latency Test for excessive daytime sleepiness, and home sleep apnea test for suspected sleep apnea. Sleep logs and sleep quality using a Ring oximeter-based SleepImage system complements evaluation of sleep-wake instability. Standard management is offered based on the ensuing diagnosis. Results Twenty-six patients (age range 22 to 58 years, 16 females) have been evaluated in this sleep pathology enriched pathway. Specific new sleep disorders diagnosis so far have included narcolepsy without cataplexy (3), hypersomnia with long sleep (3), hypersomnia without long sleep (3), rapid eye movement sleep disorder (2), persistent insomnia (3), a sleep-wake instability syndrome we call cyclical insomnia (2), and sleep apnea (7). Treatment has included CPAP, stimulants, modafinil, and sodium oxybate. Clinical responses to treatment have so far been as expected. One patient with cyclical insomnia has had a marked subjective and objective improvement with low dose (250 mg) sodium valproate. Conclusion PASC/Long-Covid can induce specific sleep syndromes. These include narcolepsy, hypersomnia, persistent insomnia, sleep-wake instability, and REM-behavior disorder. Support (if any)