Abstract

Background. Perioperative sleep disorders exert a severe adverse impact on postoperative recovery. Recently, some observational studies reported that acupuncture-point stimulation (APS) provided benefits for promoting perioperative sleep quality. However, the effects of APS on perioperative sleep disorders following general anesthesia have not been thoroughly assessed by any systematic study and meta-analysis. Therefore, we conducted this systematic review and meta-analysis to reveal the effects of APS on perioperative sleep disorders. Methods. Eight databases (Chinese: CNKI, VIP, CBM, and Wanfang; English: PubMed, Embase, Web of Science, and Cochrane Library) were thoroughly searched to find randomized controlled trials (RCTs) that indicated a link between APS and the occurrence of perioperative sleep disorders. We applied RevMan 5.4 (Cochrane Collaboration) and Stata 16.0 (Stata Corp) to conduct our meta-analysis. In addition, the trial sequential analysis (TSA) tool was utilized to estimate the validity and reliability of the data. Results. In this study, nine RCTs with 719 patients were conducted. Compared to the control group, APS significantly improved perioperative subjective sleep quality (SMD: −1.36; 95% CI: −1.71 to −1.01; ). Besides, it increased perioperative TST (preoperative period MD = 24.29, 95% CI: 6.4 to 42.18, ; postoperative period MD = 45.86, 95% CI: 30.00 to 61.71, ) and SE (preoperative MD = 3.62, 95% CI: 2.84 to 4.39, ; postoperative MD = 6.43, 95% CI: 0.95 to 11.73, ). The consequence of trial sequential analysis further confirmed the reliability of our meta-analysis results. Conclusion. According to the currently available evidence, APS could effectively improve perioperative sleep quality and play an essential role in decreasing the incidence of perioperative sleep disorders.

Introduction

Sleep is vital for overall health as it influences the quality of life and physical functioning [1]. Good sleep quality is a sign of wellbeing, whereas poor sleep quality raises comorbidity, mortality, and medical expenses [2]. Despite advances in operative and anesthetic procedures, sleep disorders continue to be a concern in the perioperative period. Perioperative sleep problems, as compared to household sleep disorders, have gained more attention recently, such as reduced nighttime sleep, fragmentation of sleep, and circadian rhythm disruptions at night after admission [3,C4]. The proportion of sleep disorders in hospitalized patients (64%–73.1%) is much higher than that in people at home (30.6%–41.2%) due to the surgical stress response, ward environment, and patients’ underlying diseases [5–7]. Perioperative sleep problems were noted in several observational studies to be important risk factors for poor recovery [8] and were associated with anxiety, altered pain perception, and postoperative cognitive dysfunction (such as delirium), further deteriorating the patient’s physical state [1, 6, 7, 9]. Moreover, it was suggested that perioperative sleep disorders might lead to postoperative fatigue, episodic hypoxemia, cardiovascular disorders, metabolic impairment, and immune disorders [10, 11]. Enhancing perioperative sleep quality is probably related to improved health, surgery effect, and patient safety [9]. Unfortunately, there are no specific therapeutic strategies for perioperative sleep disorders. Even though it was reported that pharmaceutical therapies, such as benzodiazepines and other sedating agents, might improve perioperative sleep quality, the potentially addictive nature and risk of tolerance restricted their clinical application [9].

In complementary and alternative medicine, acupuncture-point stimulation (APS) was employed to improve perioperative sleep quality [12]. According to the theory of traditional Chinese medicine (TCM), APS refers to stimulating the body’s acupoints with various methods, including acupressure (manual stimulation), acupuncture (sterile needle stimulation), laser acupuncture, electrical stimulation (transcutaneous electrical acupoint stimulation and electrical acupuncture), magnetic acupuncture (stimulation with special equipment), moxibustion therapy, and auricular point pressing, with the goal of achieving therapeutic effects such as sleep improvement and pain management [13–18]. APS has been an integral part of traditional Chinese medicine treatment. Based on the traditional Chinese medicine meridian theory, the body’s qi circulation is restored when target acupoints along meridians are stimulated [14]. It was reported that APS might lower the risk of poor sleep quality due to its considerable analgesic and sedative effects [19, 20]. Recently, a significant number of RCTs were carried out on the effects of APS on perioperative sleep disorders [8, 15]. Besides, a previous review concluded that EA might work to alter neurotransmitter concentrations and reduce the levels of norepinephrine and dopamine so as to enhance the quality of postoperative sleep quality after general anesthesia [12]. However, this study not only did not conduct a statistical assessment of the efficiency of EA on inpatients’ sleep quality during the postoperative period but also did not examine preoperative sleep quality thoroughly [12].

Conclusion

Taken together, our systematic review and meta-analysis suggested that APS could effectively improve perioperative sleep disorders, indicating that it was worthwhile to offer such therapies in perioperative healthcare institutions. Although our results had certain clinical implications of APS for the treatment of perioperative sleep disorders, more studies are needed to offer stronger evidence to further verify our conclusions in the future.

Abstract

Background

     Even though various studies have been conducted to investigate the relationship between trace metals and sleep, few epidemiological studies have evaluated the relationship between trace metals and sleep disorders in American adults.

Objective

     This study intended to evaluate the associations of serum zinc (Zn), copper (Cu), selenium (Se), Zn/Cu, Zn/Se, and Cu/Se ratios with sleep disorders in American adults.

Methods

     We conducted a cross-sectional analysis of 3660 adults aged ≥18 years old who participated in the National Health and Nutrition Examination Survey (NHANES) 2011–2016. Binary logistic regression was employed to calculate the odds ratio (OR) and 95 % confidence interval (CI) of either serum trace metals or serum trace metals ratios with risks among sleep disorder phenotypes. The restricted cubic spline (RCS) model was additionally utilized to check the dose-response relationships between serum trace metals, serum trace metals ratios, and sleep disorders.

Results

     Logistic regression demonstrated that higher serum Zn (OR: 0.70, 95 % CI: 0.51–0.97, p = 0.035), Zn/Cu (OR: 0.62, 95 % CI: 0.45–0.87, p = 0.007), and Zn/Se (OR: 0.68, 95 % CI: 0.49–0.95, p = 0.025) were related to a decreased likelihood of self-reported sleep disorders, and dose-response relationships were detected by the RCS models, after adjustment for sociodemographic, behavioral, and health characteristics. No associations between serum Cu, Se, Cu/Se, and sleep disorders were observed. The findings in the sensitivity analyses were consistent with these results.

Conclusion

     Our study revealed that serum Zn, Zn/Cu, and Zn/Se were inversely associated with the risk of self-reported sleep disorders in US adults.

Introduction

     Healthy/normal sleep patterns, often evaluated by healthy sleep scores, are characterized as early chronotype, sleep 7–8 h per day, reported never or rare insomnia symptoms, no self-reported snoring, and no frequent daytime sleepiness (Fan et al., 2020; Li et al., 2021). Sleep disorders, including insomnia, sleep apnea, narcolepsy, and restless leg syndrome, are one of the most common clinical problems which disturb sleep patterns (Karna and Gupta, 2022). Besides the direct negative influence on enthusiasm and mental state, sleep disorders have been reported to be associated with various adverse health outcomes, such as obesity, hypertension, type 2 diabetes, cardiovascular disease, and increased mortality (Huyett et al., 2021; Kase et al., 2021; Medic et al., 2017). Moreover, the prevalence of sleep disorders has been rising in the past decades and peaked at a high level, for instance, a recent study revealed that the prevalence of sleep disorders in American adults was 27.1 % (Kase et al., 2021). Since the high prevalence and correlation with various adverse health outcomes, exploring the risk factors of sleep disorders is of vital significance.

Results

Main analyses

     The baseline characteristics of participants across survey waves were presented in Table 1. The overall prevalence of self-reported sleep disorder was 28.9 % and showed a slightly climbing trend from 27.6 % in 2011–2012 to 29.9 % in 2015–2016, but without statistical significance (p = 0.610). The distributions of serum trace metals and serum trace metals ratios across three cycles did not significantly alter.

      Characteristics of participants with and without self-reported sleep disorders were presented in Table 2. From the perspective of univariate analysis, education level, family income, physical activity, caffeine intake, serum Zn, serum Cu, serum Se, and serum Zn/Se were not related to the prevalence of sleep disorders. Advanced age, female gender, nonHispanic white race, smoking, drinking, obesity, hypertension, diabetes, depression, lower Zn/Cu, and higher Cu/Se were likely to be risk factors for sleep disorders in American adults.

     The results of binary logistic regression models of serum trace metals and serum trace metals ratios on self-reported sleep disorders were described in Table 3. After fully adjusted for sociodemographic, behavioral, and health covariates, serum Cu and serum Se were not related to the risk of sleep disorders in American adults. However, compared to individuals in the lowest tertiles of serum Zn (<Q1), adults with the highest tertiles of serum Zn (>Q3) had a 30.0 % (OR: 0.70, 95 % CI: 0.51–0.97, p = 0.035) lower risk to report sleep disorders.

Introduction

Methods

Results

Discussion

Conclusions

References

Abstract

Background
Ments were examined in the acute period of stroke. 33 (50%) patients had at least one or more new or exacerbated sleep complaiore than half of stroke patients present with a sleep-related breathing disorder including both central and obstructive forms of sleep apnoea. A cerebral infarction in different brain areas can disrupt sleep regulating pathways and cause insomnia, hypersomnia, circadian rhythm disturbances and other sleep disorders. Therefore, there is a need of objective data about various sleep disorders arising after ischemic or haemorrhagic stroke in order to implement practical recommendations how to suspect, diagnose and treat these conditions. Our medical hypothesis is that non-breathing sleep disorders are common among patients with acute ischemic or haemorrhagic stroke.
Objective
To investigate the subjective and objective sleep parameters in the patients with an acute ischemic or haemorrhagic stroke.
Methods
In the acute period (from 3 to 10 days after the first symptoms) of stroke all the patients completed questionnaires about sleep complaints and symptoms experienced before and after stroke, Epworth Sleepiness Scale (ESS), National Institute of Health Stroke Scale, Hospital Anxiety and Depression Scale and Modified Rankin Scale. Patients were included for further polysomnography (PSG) and sleep electroencephalography according to these criteria: (1) patients expressing severe sleep related complaints and/or symptoms that are new or have exacerbated after the stroke; and/or (2) patients having the ESS score equal or >10.
Results
66 patints and/or symptoms, mostly related to obstructive sleep apnoea (OSA) and insomnia. Finally, 13 (19.7% of the whole sample) patients were selected for performing PSG. 12 of 13 patients were diagnosed with sleep disorder: 1 patient got the diagnosis of mild OSA, 1 – central sleep apnoea (CSA), 2 – combination of OSA and CSA, 1 – combination of mild OSA, periodic limb movement disorder (PLMD) and REM sleep behaviour disorder (RBD), 1 – combination of mild OSA and PLMD, 3 – combination of PLMD and insomnia, 3 – insomnia. There were no significant relations between type, location or treatment of stroke and various PSG measures, as well as type of a diagnosed sleep disorder.
Conclusions
Half of our acute stroke patients had at least one or more new or exacerbated sleep complaints and/or symptoms, mainly related to OSA or insomnia. In the selected PSG group almost all patients were diagnosed with a sleep disorder, half of them having non-breathing sleep disorder, such as PLMD, RBD and insomnia.

Introduction

Sleep is recognized to be considerable for health and well-being in all persons, but increasingly so in those recovering from brain damage [1]. It is known that sleep disorders are a frequent complication in patients with acute ischemic or haemorrhagic stroke, approximately 20–40% of stroke patients experience various sleep-wake disorders, such as insomnia, hypersomnia, REM sleep behavior disorder (RBD), periodic limb movement disorder (PLMD). Even more, about 50–70% stroke patients present with a sleep-related breathing disorder including both central and obstructive forms of sleep apnoea [2,3]. Despite that, the majority of physicians do not screen stroke patients for sleep-disordered breathing [4]. Patients with stroke and OSA have a higher risk for repeated stroke and significantly increased mortality in one year after the stroke in comparison with the patients without apnoea [5,6]. Studies showed a significant reduction in stroke recurrence and mortality as well as improved neurological recovery among the patients treated with continuous positive airway pressure therapy (CPAP), consequently, CPAP treatment may reduce the risk of stroke in patients with OSA [7]. A cerebral infarction in subcortex, thalamus or mesencephalon can fully disrupt sleep and wakefulness cycle, leading to insomnia and agitation during the night, and severe sleepiness during the day [8]. Insufficient sleep after stroke can be followed by chronic fatigue, cognitive and emotional dysfunction, worse neurological outcome and life quality. Therefore, there is a need of objective data about various sleep disorders arising after ischemic or haemorrhagic stroke in order to implement practical recommendations how to suspect, diagnose and treat these conditions. Our medical hypothesis is that non-breathing sleep disorders are common among patients with acute ischemic or haemorrhagic stroke. The aim of the study presented in this article was to investigate the subjective and objective sleep parameters in the patients with an acute ischemic or haemorrhagic stroke.

Introduction

Major Sleep Disorders

Conclusion

References

Abstract

Sleep disorders are frequent and can have serious consequences on patients’ health and quality of life. While some sleep disorders are more challenging to treat, most can be easily managed with adequate interventions. We review the main diagnostic features of 6 major sleep disorders (insomnia, circadian rhythm disorders, sleep-disordered breathing, hypersomnia/narcolepsy, parasomnias, and restless legs syndrome/periodic limb movement disorder) to aid medical practitioners in screening and treating sleep disorders as part of clinical practice.

INTRODUCTION

Sleep is a universal function of living species, comprising one-third of human life. Poor or insufficient sleep has been associated with a wide variety of dysfunction in most body systems, including endocrine,1 metabolic,2 higher cortical function,3 and neurological disorders. Disorders of sleep can manifest as complaints of either insufficient sleep, excessive amount of perceived sleep, or abnormal movements during sleep. This review article focuses on the most commonly seen sleep disorders in neurological practice.

Abstract

Sleep disorders are common in a general population. It effect one in 5 adults and has several short term and long term bad side effects on health. Sleep apnea (SA) is the most important and common component of sleep disorders. This paper presents an automatic approach for detecting apnea events by using few bio-singles that are related to breathe defect. This work uses only air flow, thoracic and abdominal respiratory movement as input. The proposed algorithm consists of three main parts which are signal segmentation, feature generation and classification. A new proposed segmentation method intelligently segments the input signals for further classification, then features are generated for each segment by wavelet packet coefficients and also original signals. In classification phase a unique parallel PSO-SVM algorithm is investigated. PSO used to tune SVM parameters, and also data reduction. Proposed parallel structure used to help PSO to search space more efficiently, also avoiding fast convergence and local optimal results that are common problem in similar parallel algorithms. Obtained results demonstrate that the proposed method is effective and robust in sleep apnea detection and statistical tests on the results shown superiority of it versus previous methods even with more input signals, and also versus single PSO-SVM. Using fewer signals means more comfortable to subject and also, reduction of cost during recording the data.

INTRODUCTION

Sleep disorders are important because they are common in a general population; a survey in 1987 [1] reported that at least one symptom of disturbed sleep was present in 41% of all subjects; and still sleep disorder is common now [2], for instance, Young reported that one daytime sleepiness in 5 adults in 2004 [3].

The sleep disorders have several short term and long term bad side effects[4]. Short-term effects lead to impaired attention and concentration, lowered life quality, increased rates of absenteeism with less productivity, and greater possibility of accidents at work, home or on the road. Longterm consequences of sleep deprivation include increased morbidity and mortality from more automobile accidents, coronary artery disease, heart failure, high blood pressure, obesity, type 2 diabetes mellitus, stroke and memory impairment as well as depression. Long-term consequences, however, are still open [5] for further academic research..

Following traumatic experiences, sleep disturbances are frequently reported. The most common symptoms are insomnia and trauma related nightmares (TRN) [1]. The nightmares that trauma survivors develop are noted to be distinctly different than the nightmares which characterize idiopathic nightmare disorder [2,3]. Trauma related nightmares tend to be more severe and distressing to the individual, and in many (but not all) cases, associated with posttraumatic stress disorder (PTSD). Disruptive nocturnal behaviors (DNB) to include dream enactment behavior (DEB) and sympathetic activation are often reported in the context of TRN. Nocturnal movements with TRN can range from gross body movements to frank combative behaviors. These symptoms, which further distinguish TRN from idiopathic nightmares, have remained relatively poorly characterized. This is in part due to the frequent association of TRN with PTSD as a variant of idiopathic nightmares, as well as the rare capture of nightmares and DNB in monitored settings [4]. Prior to the proposal of trauma associated sleep disorder (TSD) as a distinct parasomnia [5], these nocturnal phenomena was best described by Raskind: “The physiology of PTSD trauma nightmares differs from that of ‘normal’ dreams. Trauma nightmares are largely expressed during light sleep and disrupted rapid eye movement (REM) sleep, and often are accompanied by motor activity. Normal dreams, whether pleasant or unpleasant, most often arise from REM sleep that is characterized by a relative paralysis of large muscle movement” [6]. This description highlights the characteristics which distinguish TSD from nightmare disorder, most notably the presence of motor activity, but also that the nightmares potentially emanate from both non-rapid eye movement (NREM) and REM sleep. Additionally, this constellation of findings occurs exclusively while asleep, thus differentiating TSD from the diagnosis of PTSD. In this article, we report on the historical findings consistent with TSD and develop the clinical and potential neurobiological mechanisms of TSD. As there is a paucity of articles on nightmares and DNB emanating solely from traumatic experiences in the absence of PTSD, we review the scientific literature which has evaluated patients with PTSD and in some cases, REM sleep behavior disorder (RBD). In a portion of the literature evaluated, the patient’s symptoms and overall clinical picture is, in our opinion, more consistent with the proposed criteria for TSD.

As the world’s population ages, age-related disorders such as Parkinson disease (PD) threaten to become a significant financial and social burden (1), on top of the personal burden carried by the affected individuals and their families. PD is the most common neurodegenerative movement disorder, affecting 1-2% of the population older than 60 years (2-4), and the projected number of PD patients in 2030 in 15 of the most populous nations is estimated to be 8.67 million patients (5). PD is pathologically characterized by degeneration of the substantia nigra (SN) and the presence of Lewy bodies, which are aggregates of various proteins, primarily α-synuclein (6). As such, it is part of a family of disorders collectively termed synucleinopathies, mainly including PD, dementia with Lewy bodies (DLB), and multiple system atrophy (MSA) (7). Other diseases may also have α-synuclein depositions, and while this is a shared feature, it does not imply that α-synuclein is the sole cause for these disorders.

The pathogenic process leading to PD begins many years before diagnosis, which is traditionally based on classical motor symptoms; therefore, the course of PD can be divided accordingly, to preclinical PD, prodromal PD (non-motor PD) and clinical PD, when motor symptoms appear (8). This recent division aims to distinguish between the different phases of PD, first, when neurodegeneration started but no symptoms are present (preclinical PD), then when early symptoms appear but PD is not diagnosed yet (prodromal PD), and lastly when motor symptoms present (clinical PD) (8). Clinical PD occurs when about half of the dopaminergic neurons in the SN had already been irreversibly degenerated and died, and the typical motor symptoms appear (9). One of the main challenges in PD research is identifying individuals during the prodromal phase of PD; when neuroprotective therapy is available, early diagnosis of PD will be crucial to slow or stop the degenerative process prior to motor parkinsonism.

Over the past decade, the relationship between obesity and sleep has become more salient. Obesity has been identified as an important risk factor for the obstructive sleep apnea syndrome (OSAS) [1-6]; therefore, this syndrome will be the main focus of this review. OSAS is a common disorder with prevalence estimates of 15-25% in adult men and 5-10% in adult women [6-11], and between 2-15% in children [2, 12, 13]. It is associated with intermittent hypoxemia, hypercapnia, arousals and sleep fragmentation. Symptoms include snoring, snorting, pauses in breathing, mouth breathing and daytime sleepiness. Children may also exhibit hyperactivity or daytime behavioral problems [14-16]. In adults, there is an association with increased morbidity and mortality, stroke, hypertension, atrial fibrillation, injuries, and cognitive impairment and Alzheimer’s disease [17-21]. Short- and long-term effects of untreated OSAS in pediatric patients include significant morbidity such growth failure [22], systemic [23-25] and pulmonary hypertension [26, 27], endothelial dysfunction [28, 29], and cognitive and behavioral deficits [16, 30-34]. Children who have both obesity and OSAS have increased cardiometabolic risk compared to children who are obese without OSAS. They also present with sleepiness, attention and executive dysfunction, mood concerns, and decreased quality of life [35-41]. There are little data regarding the long-term consequences of having both pediatric obesity and OSAS. One common risk factor for OSAS in adults is excess adiposity [4-6, 10, 11, 42]. An estimated 1% increase in BMI is associated with a 3% increase in the apnea hypopnea index (AHI) [4]. In children 2-5 years of age, the most common cause of OSAS is adenotonsillar hypertrophy. However, as the prevalence of obesity in youth has dramatically increased, it is now recognized as a significant contributor to OSAS, particularly in adolescence [1-3]. Further, there is a bidirectional relationship such that OSAS may promote further weight gain or may hinder weight loss efforts [42-48]. There are currently three interventions for weight loss: lifestyle modification altering diet and/or physical activity along with behavior change procedures, pharmacologic and surgical modalities. Often pharmacologic and surgical therapies are paired with lifestyle modification strategies. However, these are more limited in the pediatric population, reserved for the most severely obese and most often delayed until adolescence. We will discuss the three main modalities of weight loss as they relate to sleep with a primary focus on OSAS. Their impact on sleep duration, sleep architecture, and insomnia will also be discussed.

Sleep plays an important role in mental and physical recovery for athletes training hard on a daily basis [1]. Multiple recent systematic reviews have suggested that athletes’ insufficient quality and quantity of sleep leads to potential decline in physical performance (e.g., sudden power and 5 endurance), decline in cognitive performance (e.g., attention and memory), and increase the risk of illness or injury [2,3]. It has also been reported that 30.6% of top athletes have sleep disorders [4]. Therefore, prevention and improvement of sleep disorders are essential for improving competitive abilities and maintaining athletic conditioning. Lifestyle habits are serious risk factors for sleep disorders. Research on adolescents and adults has reported that smoking [5], drinking [6], regularity of mealtimes [7], skipping breakfast [8], late night part-time jobs [9], and use of electronics such as smartphones/cellphones after lights out [10] are all related to sleep disorders. However, the relation between these lifestyle habits and sleep disorders among athletes has not yet been studied. In general, exercise is considered to contribute to improved sleep quality and longer sleep duration [11]; however, over-exercising can possibly increase arousal levels and inhibit sleep [12]. Thus far, research has reported that an increase in practices causes sleep disorders among athletes [13], and those with early morning practices have shorter sleep duration [14]. Yet these studies are insufficient. Furthermore, empirical studies on sleep and psychological stressors have been conducted mainly in the work field, reporting that high occupational stressors related to poor sleep quality [15], long sleep latency [15], and insomnia [16]. Therefore, presumably, competition stress becomes a risk factor in sleep disorders for athletes. However it has only been reported that feeling stagnated with respect to competition results is related to sleep disturbances [17], and such studies are insufficient. It is also well known that the impact of psychological factors such as depressive symptoms and psychological distress negatively affect sleep [18]. Previous studies found that depressive symptoms were strong risk factors of sleep disorders among university students [19,20]. Although a few study reported that depressive symptoms related sleep disorders among adolescent athletes [21], there is no study investigating these relationships considering the effect of lifestyle habits and competition activities.

Cerebral neurodegenerative disorders, such as Parkinson disease (PD) and dementia, are increasing in prevalence as the population ages. These disorders are characterized by neuronal cell loss and abnormal accumulation of protein in cells of the brain. Symptoms, such as tremor, muscle rigidity, imbalance, and impaired cognition, progressively worsen with time. Not only are there challenges in managing the primary symptoms of these conditions, but many of these patients also suffer from sleep complaints, such as insomnia or hypersomnia. Others may suffer from abnormal movements during sleep, known as rapid eye movement (REM) sleep behavior disorder (RBD). This disorder may be dangerous and disruptive to sleep, and can sometimes precede the development of other symptoms of neurodegenerative disorders by years or even decades. High rates of sleep disorders, such as insomnia, hypersomnia, sleep apnea, restless legs syndrome (RLS), and circadian rhythm disorders, in older adults with neurodegenerative disorders are likely caused by the underlying symptoms of the disease along with damage to sleep-controlling regions of the brain. It is important to recognize and properly manage these sleep disorders because treatment may improve symptoms of the neurodegenerative condition and improve quality of life.

PARKINSON DISEASE AND OTHER SYNUCLEINOPATHIES PD

is a progressive neurodegenerative condition that causes motor symptoms of bradykinesia, shuffling gait, tremor, and rigidity. It is the second most common neurodegenerative condition affecting more than 1% of the population older than 60 years of age.1 Patients commonly present with postural instability and falls. The pathologic hallmark of PD is Lewy bodies, which are intraneuronal a-synuclein inclusions. Lewy bodies first involve lower brainstem areas before spreading next to the substantia nigra and eventually areas throughout the brain. Motor symptoms of PD typically respond well to dopamine therapy early in the course of the disease. There are a variety of nonmotor symptoms of PD, including autonomic, olfactory, and mood dysfunction, and poor sleep. Sleep disorders are seen in most patients with PD.2 The most common sleep disorders are insomnia, periodic limb movement disorder, sleep-disordered breathing, and RBD. In addition to PD, other synucleinopathies (which are central nervous system degenerative conditions caused by abnormal a-synuclein accumulation) include Lewy body dementia and multiple system atrophy, which are also associated with high rates of the same sleep disorders typically seen in patients with PD.

مقاله سال 2016

روش ها: 65 بیمار مبتلا به مولتیپل اسکلروزیس(ام اس) که به طور متوالی وارد مطالعه شدند ، به صورت گذشته نگر به دو صورت “دارای خواب خوب” (GS)( PSQI ≤ 5) و “دارای خواب ضعیف”( PS)( PSQI > 5) طبقه بندی شدند. داده های حاصل از پلی سومنوگرافی و نمرات مقیاس آنالوگ دیداری خستگی(VAS) ، مقیاس اصلاح شده اثر خستگی (MFIS)، مقیاس شدت خستگی(FSS)، مقیاس خواب آلودگی ایپورث(ESS) و پرسشنامه افسردگی بک(BDI) مورد مقایسه قرار گرفتند.

نتایج: هیچ تفاوت آماری معنی داری بین داده های حاصل از پلی سومنوگرافی یا نمرات مقیاس خواب آلودگی ایپورث ، مقیاس اصلاح شده اثر خستگی و مقیاس شدت خستگی وجود نداشت اما بیماران دارای خواب ضعیف افزایش معنی دار در نمرات پرسشنامه افسردگی بک و مقیاس آنالوگ دیداری خستگی را نشان داد.

1- مقدمه
در چندین مطالعه، نمرات شاخص کیفیت خواب پیتزبرگ با متغیرهای ثبت رویدادهای خواب و مقیاس افسردگی همبستگی داشت اما با داده های حاصل از اکتی گرافی و پلی سومنوگرافی همبستگی نداشت.
مقیاس کیفیت خواب پیتزبرگ یک پرسشنامه خود ارزیابی(توسط خود بیمار تکمیل می گردد) می باشد که کیفیت خواب و اختلال خواب را با نمرات هفت مولفه ای مورد ارزیابی قرار می دهد( کیفیت خواب ذهنی، تاخیر خواب، دوره خواب، کفایت خواب عادتی، اختلال خواب، استفاده از داروهای خواب آور، و اختلال عملکرد طول روز). افرادی با خواب خوب ، نمرات مقیاس کیفیت خواب پیتزبرگ ≤5 را نشان دادند در حالیکه افرادی با خواب بد با نمرات > 5 تعریف می شوند.

مقاله سال 2016

مقدمه: بیماری پارکینسون یک بیماری پیشرونده تخریبی اعصاب می باشد که در سن بالای 60 سال بسیار شایع می باشد. بیماری پارکینسون از نظر دسته بندی با ویژگی های حرکتی مشخص می گردد، با اینحال ممکن است بیماران نشانه های غیر حرکتی را نیز تجربه کنند. اختلال خواب مانند اختلال رفتار حرکت سریع چشم (REM) (RBD)، در بیماران مبتلا به پارکینسون شایع می باشد و ممکن است پیش درآمد ابتلا به پارکینسون باشد.

روش ها: داده ها از بیماران مبتلا به پارکینسون (358 نفر) در یک کلینیک اختلال حرکتی در بیمارستان شبکه ایمنی جمع آوری شدند. در این تحلیل داده های گذشته نگر، ارتباط بین عوارض پارکینسون با سن شروع، با استفاده از تست کای دو و رگرسیون لوجستیک مورد ارزیابی قرار گرفت.

نتایج: از عوارض مورد تحلیل قرار گرفته پارکینسون، تفاوت معنی داری در اختلالات خواب بر اساس سن به دست آمد. از بین 358 بیمار مبتلا به پارکینسون(موجود در مرکز)، نفر(33.5%) اطلاعاتی در مورد وجود یا عدم وجود اختلال خواب120 نفر داشتند. یک تفاوت معنی دار بین گروه های با شروع زودرس(شروع <50) و شروع دیر رس( ≥50) با شانس داشتن اختلال خواب برای گروه زودرس1.6 برابر نسبت به گروه دیررس (p = 0.03) وجود داشت.در افرادی که خواهر یا برادرشان نیز مبتلا به بیماری پارکینسون بود، دو برابر احتمال داشتن اختلال خواب در مقایسه با آنها که خواهر و برادر بیمار نداشتند، وجود داشت(p = 0.02).

نتیجه گیری: هیچ یک از نشانه های غیر حرکتی مانند اختلال خواب ، به عنوان پیشگویی کننده مفید برای شروع بیماری پارکینسون نمی باشند. اجزای ژنتیکی بیماری پارکینسون هم جنبه های حرکتی و هم جنبه های غیر حرکتی بیماری را تحت تاثیر قرار می دهند.

مقدمه
بیماری پارکینسون یک بیماری پیشرونده تخریبی اعصاب می باشد که در محدوده سنی وسیعی خود را نشان می دهد. بیماری پارکینسون در سن بالای 60 سال با میانگین سنی تشخیصی 70.5 سال بسیار شایع می باشد و در افراد زیر 40 سال شایع نیست. یماری پارکینسون از نظر بالینی با چهار ویژگی حرکتی: لرزش، کندی حرکتی، سفتی عضلات و راه رفتن ناپایدار (غیرمتعادل) مشخص می گردد. هر چند که به طور اولیه این ویژگی های حرکتی برای تشخیص بیماری پارکینسون مورد استفاده قرار می گیرد، اما بیماران علاوه بر اینها با نشانه های غیر حرکتی نیز درگیر می باشند.