Autonomic dysfunction and sleep disorders

2017 ◽  
Author(s):  
Giovanna Calandra-Buonaura ◽  
Pietro Cortelli
Keyword(s):  
Sleep Disorders ◽  
Sleep Disorder ◽  
Autonomic Dysfunction ◽  
Sleep Apnea Syndrome ◽  
Rem Sleep Behavior Disorder ◽  
Causal Mechanism ◽  
Sleep Behavior ◽  
Obstructive Sleep ◽  
Autonomic Dysfunctions ◽  
The Impact

Autonomic dysfunctions are frequently associated with sleep disorders, as the autonomic nervous system and sleep are closely related from anatomical, physiological, and neurochemical points of view. The autonomic dysfunctions described in this chapter may result from a common pathogenetic mechanism that affects both the autonomic and the sleep functions, as in fatal familial insomnia, or from a prevalent expression of a primary disorder of autonomic regulation during sleep, as in congenital central hypoventilation syndrome. Alternatively, the autonomic dysfunction may be mainly caused by the sleep disorder, as observed in obstructive sleep apnea syndrome, or the causal mechanism resulting in the association between the autonomic dysfunction and the sleep disorder has yet to be identified with certainty, as in narcolepsy with cataplexy and in REM sleep behavior disorder. The impact of the autonomic dysfunction on health and on patients’ quality of life is also reviewed.

scholarly journals Three Decades of Progress in Sleep Disorders and Sleep Health for Women

2020 ◽  
Vol 4 ◽  
pp. 247028972094187
Author(s):  
Jennifer L. Marsella ◽  
Katherine M. Sharkey
Keyword(s):  
Sleep Disorders ◽  
Rem Sleep Behavior Disorder ◽  
Behavior Disorder ◽  
Future Research ◽  
Sex And Gender ◽  
Sleep Health ◽  
Sleep Behavior ◽  
Obstructive Sleep ◽  
And Gender ◽  
The Impact

Over the past 3 decades, significant strides have been made in the field of sleep medicine for women. The impact of sex and gender on sleep health and sleep disorders received little attention in the early 1990s, but driven by policies ensuring inclusion of women in medical research, more recent studies have identified sex differences in sleep and investigated gender differences in sleep disorders. Nevertheless, disparities remain: diagnosis of sleep disorders, such as obstructive sleep apnea, narcolepsy, and rapid eye movement (REM) sleep behavior disorder are often delayed and underdiagnosed in women. Future research should continue to examine how biological sex and identity across the gender spectrum influence sleep health and sleep disorders, allowing for more personalized health care for all patients.

Vitamin D and Sleep Regulation: Is there a Role for Vitamin D?

2020 ◽  
Vol 26 (21) ◽  
pp. 2492-2496 ◽  
Author(s):  
Fiammetta Romano ◽  
Giovanna Muscogiuri ◽  
Elea Di Benedetto ◽  
Volha V. Zhukouskaya ◽  
Luigi Barrea ◽  
...  
Keyword(s):  
Vitamin D ◽  
Sleep Disorders ◽  
Vitamin D Deficiency ◽  
Sleep Apnea Syndrome ◽  
Regulatory Mechanisms ◽  
Sleep Regulation ◽  
Vitamin D Receptors ◽  
Obstructive Sleep ◽  
The Impact

Background: Vitamin D exerts multiple pleiotropic effects beyond its role in calcium-phosphate metabolism. Growing evidence suggests an association between hypovitaminosis D and sleep disorders, thus increasing the interest in the role of this vitamin in the regulatory mechanisms of the sleep-wake cycle. Objective: The study aimed to explore and summarize the current knowledge about the role of vitamin D in sleep regulation and the impact of vitamin D deficiency on sleep disorders. Methods: The main regulatory mechanisms of vitamin D on sleep are explained in this study. The literature was scanned to identify clinical trials and correlation studies showing an association between vitamin D deficiency and sleep disorders. Results: Vitamin D receptors and the enzymes that control their activation and degradation are expressed in several areas of the brain involved in sleep regulation. Vitamin D is also involved in the pathways of production of Melatonin, the hormone involved in the regulation of human circadian rhythms and sleep. Furthermore, vitamin D can affect sleep indirectly through non-specific pain disorders, correlated with alterations in sleep quality, such as restless legs syndrome and obstructive sleep apnea syndrome. Conclusions: : Vitamin D has both a direct and an indirect role in the regulation of sleep. Although vitamin D deficiency has been associated to sleep disorders, there is still scant evidence to concretely support the role of vitamin D supplementation in the prevention or treatment of sleep disturbances; indeed, more intervention studies are needed to better clarify these aspects.

scholarly journals Sleep disorder: a possible cause of attention deficit in children and adolescents with Chiari malformation type II

2009 ◽  
Vol 67 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Paulo Sérgio Azeredo Henriques Filho ◽  
Riccardo Pratesi
Keyword(s):  
Sleep Apnea ◽  
Sleep Disorders ◽  
Attention Deficit ◽  
Chiari Malformation ◽  
Sleep Apnea Syndrome ◽  
Rem Sleep Behavior Disorder ◽  
Behavior Disorder ◽  
Type Ii ◽  
Sleep Behavior ◽  
Apnea Syndrome

BACKGROUND: Attention deficit may be related to sleep disorders in Chiari malformation type II (CMII). Our aim is identify sleep disorders and their specific contribution in attention deficit. METHOD: We selected 24 patients with CM II and 24 without CM II. DSM-IV criteria and a neuropsychological analysis were applied in all. All patients underwent full night polysomnography. RESULTS: 14 CM II patients presented sleep apnea syndrome, REM sleep behavior disorder and periodic limb movement in sleep; six patients without CM II presented sleep apnea syndrome. Among these patients, 12 (six with CM II and six without CM II) presented attention deficit related to the sleep disorders. CONCLUSION: Sleep disorders may impair cognitive functions, as attention, and contribute to poor quality of learning also in patients with CM II.

scholarly journals 1183 Board-certified Sleep Medicine Physicians See A Greater Proportion Of Complex Sleep Patients Than Non-specialist Providers

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A452-A452
Author(s):  
S L Jobe ◽  
J S Albrecht ◽  
S M Scharf ◽  
A M Johnson ◽  
S Parthasarathy ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Sleep Disorders ◽  
Sleep Disorder ◽  
Sleep Medicine ◽  
Board Certification ◽  
Administrative Claims ◽  
Medicare Beneficiaries ◽  
Sleep Complaints ◽  
Obstructive Sleep ◽  
The Impact

Abstract Introduction Despite a growing literature regarding the impact of board-certification in sleep medicine, little is known about the complexity of patients seen by board-certified sleep medicine physicians (BCSMPs) relative to non-specialists. To address this gap, the purpose of the current study was to evaluate the differences in sleep complaints among Medicare beneficiaries seen by BCSMPs relative to individuals seen by non-specialists. Methods Our data source was a random 5% sample of Medicare administrative claims data from 2006-2013. Sleep disorders were operationalized using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Descriptive analyses were performed to estimate the number of sleep disorder diagnoses patients received by provider status. BCSMPs were identified using a cross-matching procedure based on National Provider Identifier (NPI). Results A total of 57,209 Medicare beneficiaries received a sleep disorder diagnosis between 2006-2013. Of these, only 2.2% were seen by BCSMPs. Relative to beneficiaries seen by non-specialists, those seen by BCSMPs were more likely to be diagnosed with more than one sleep disorder (p<0.001). Specifically, 91.0% of individuals seen by non-specialists received only one sleep disorder diagnosis, whereas 75.9% of individuals seen by BCSMPs received only one sleep disorder diagnosis. Among beneficiaries seen by non-specialists, the most common sleep disorders were insomnia (48.2%; n=26,967), obstructive sleep apnea (OSA; 31.4%; n=17,554), and restless legs syndrome (8.7%; n=4,871). Among those seen by BCSMPs, the most common sleep disorders were OSA, (70.4%; n=901), sleep apnea with hypersomnia (16.5%; n=211), and insomnia (11.7%; n=150). Conclusion BCSMPs see more complex sleep patients than do non-specialists. These results suggest the possibility that more complex patients are referred for sleep specialty care. Further, these results demonstrate the value of board certification in sleep medicine in caring for complex sleep patients. Support This research was supported by an AASM Strategic Research Award from the AASM Foundation to the University of Maryland, Baltimore (PI: EMW).

REM sleep behavior disorder and other sleep abnormalities in p. A53T SNCA mutation carriers

SLEEP ◽  
2020 ◽  
Author(s):  
Athina Maria Simitsi ◽  
Christos Koros ◽  
Maria Stamelou ◽  
Dimitra Papadimitriou ◽  
Athanasios Leonardos ◽  
...  
Keyword(s):  
Sleep Disorder ◽  
Rem Sleep ◽  
Rem Sleep Behavior Disorder ◽  
Behavior Disorder ◽  
Alpha Synuclein ◽  
Sleep Behavior ◽  
Asymptomatic Carriers ◽  
Olfactory Testing ◽  
Obstructive Sleep ◽  
Sleep Abnormalities

Abstract Study Objectives Τo assess whether REM Sleep Behavior Disorder (RBD) and other sleep abnormalities occur in carriers of the p.A53T alpha-synuclein gene (SNCA) mutation, using both subjective and objective measures. Methods We have assessed 15 p.A53T carriers (10 manifesting Parkinson’s Disease [PD-A53T] and 5 asymptomatic carriers) with simultaneous Video-PSG (polysomnography) recording, the Epworth Sleepiness Scale (ESS) for daytime sleepiness, the Athens Insomnia Scale (AIS), the RBD Screening Questionnaire (RBDSQ) for clinical features of RBD, the Montreal Cognitive Assessment (MOCA) for cognition and the University of Pennsylvania Smell Identification Test (UPSIT) for olfaction. Results In our cohort, 90% of PD carriers had at least one sleep disorder and 40% had two: 4 RBD, 1 Periodic Limb Movements (PLM), 1 RBD plus PLM, 2 RBD plus moderate Obstructive Sleep Apnea (OSA), and 1 moderate OSA plus Restless Leg Syndrome. No asymptomatic carrier manifested a confirmed sleep disorder. 6/7 PD carriers with RBD had abnormal olfactory testing and 4/7 MOCA below cut off. There was a correlation of both impaired olfaction and cognition with RBD. Conclusions RBD occurs in the majority of PD-A53T, in contrast to most other genetic forms of PD, in which RBD is uncommon. The paucity of a sleep disorder in the asymptomatic carriers suggests that such carriers have not yet reached the prodromal phase when such sleep disorders manifest. Hyposmia in almost all subjects with RBD and cognitive decline in most of them are indicative of the general pattern of disease progression, which however is not uniform.

Commonly Encountered Sleep Disorders

2018 ◽  
Author(s):  
Karl Doghramji
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Disorders ◽  
Eye Movement ◽  
Treatment Options ◽  
Sleep Apnea Syndrome ◽  
Central Sleep Apnea ◽  
Periodic Limb Movement Disorder ◽  
Sleep Behavior ◽  
Obstructive Sleep

Complaints related to sleep and wakefulness are some of the most commonly encountered in clinical settings. This chapter reviews specific sleep disorders including insomnia disorder, hypersomnolence disorder, narcolepsy, obstructive sleep apnea hypopnea syndrome, central sleep apnea syndrome and selected parasomnias (nonrapid eye movement sleep arousal disorders and rapid eye movement sleep behavior disorder). These disorders are some of the best characterized and commonly comorbid with other medical and psychiatric disorders. Their defining characteristics, diagnostic modalities, and treatment options are summarized. Topics covered in this chapter include narcolepsy, cataplexy, insomnia, restless legs syndrome, periodic limb movement disorder, obstructive sleep apnea, central sleep apnea, hypersomnolence.

AI-enabled Algorithm for Automatic Classification of Sleep Disorders Based on Single-lead Electrocardiogram (Preprint)

2021 ◽  
Author(s):  
Erdenebayar Urtnasan ◽  
Eun Yeon Joo ◽  
Kyuhee Lee
Keyword(s):  
Sleep Disorders ◽  
Sleep Disorder ◽  
Screening Method ◽  
Rem Sleep Behavior Disorder ◽  
Automatic Classification ◽  
Control Group ◽  
Ecg Signal ◽  
Deep Convolutional Neural Networks ◽  
Sleep Behavior

BACKGROUND Healthy sleep is an essential and important physiological process for every individual to live a healthy life. Many sleep disorders are both destroying the quality and decreasing the duration of sleep. Thus, a convenient and accurate detection or classification method is important for screening and identifying sleep disorders. OBJECTIVE In this study, we proposed an AI-enabled algorithm for automatic classification of sleep disorders based on a single-lead electrocardiogram (ECG). AI-enabled algorithm—named a sleep-disorder network (SDN) was designed for automatic classification of four major sleep-disorders namely insomnia (INS), periodic leg movement (PLM), REM sleep Behavior Disorder (RBD), and nocturnal frontal-lobe epilepsy (NFE). METHODS The SDN was constructed using deep convolutional neural networks that can extract and analyze the complex and cyclic rhythm of sleep disorders that affect ECG patterns. The SDN consists of 5-layers 1-D convolutional layer and is optimized via dropout and batch normalization. The single-lead ECG signal was extracted from the 35 subjects with the control (CNT) and the four sleep-disorder groups (7 subjects of each group) in the CAP Sleep Database. The ECG signal was pre-processed, segmented at 30-s intervals, and divided into the training, validation, and test sets consisting of 74,135, 18,534, and 23,168 segments, respectively. The constructed SDN was trained and evaluated using the CAP Sleep Database, which contains not only data on sleep disorders, but also data of the control group. RESULTS The proposed SDN algorithm for the automatic classification of sleep disorders based on a single-lead ECG showed very high performances. We achieved F1-scores of 99.0%, 97.0%, 97.0%, 95.0%, and 98.0% for the CNT, INS, PLM, RBD, and NFE groups, respectively. CONCLUSIONS We proposed an AI-enabled method for the automatic classification of sleep disorders based on a single-lead ECG signal. In addition, it represents the possibility of the sleep disorder classification using ECG only. The SDN can be a useful tool or an alternative screening method based on single-lead ECGs for sleep monitoring and screening.

Sign in / Sign up

Export Citation Format

Share Document