ResearchPad - sleep-disorders https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[The prevalence of poor sleep quality and associated risk factors among Chinese elderly adults in nursing homes: A cross-sectional study]]> https://www.researchpad.co/article/elastic_article_14729 Sleep problems have become the most common complaints among the elderly. There are a few studies that explored the prevalence of poor sleep quality and its associated factors among the elderly in nursing homes. Therefore, this study aimed to examine the prevalence of poor sleep quality and its associated factors among the Chinese elderly in nursing homes.MethodsA total of 817 elderly residents, from 24 nursing homes, were included in this cross-sectional study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and poor sleep quality was defined as PSQI >5. Multiple binary logistic regression was used to estimate the strength of the association between risk factors and poor sleep quality in terms of adjusted odds ratios (AORs) and their 95% confidence intervals (CIs), and interactions of risk factors for poor sleep quality were also examined.ResultsThe prevalence of poor sleep quality was 67.3% (95% CI: 64.0, 70.5%) among the Chinese elderly in nursing homes. Multiple binary logistic regression results showed that participants with the following characteristics had an increased risk of poor sleep quality after adjustments for other confounders: being 70–79 years old (AOR: 1.78, 95% CI: 1.08, 2.92) or 80 years old and above (AOR: 2.67, 95% CI: 1.68, 4.24); having one to two kinds of chronic diseases (AOR: 2.05, 95% CI: 1.39, 3.01) or three or more kinds of chronic diseases (AOR: 2.35, 95% CI: 1.39, 4.00); depression symptoms (AOR: 1.08, 95% CI: 1.04, 1.11), anxiety symptoms (AOR: 1.11, 95% CI: 1.05, 1.18), and social support(AOR: 0.97, 95% CI: 0.95, 0.99). Additive interactions were detected between age and anxiety symptoms (AOR: 8.34, 95% CI: 4.43, 15.69); between chronic disease and anxiety symptoms (AOR: 8.61, 95% CI; 4.28, 17.31); and between social support and anxiety symptoms (AOR: 6.43, 95% CI: 3.22, 12.86).ConclusionsThe prevalence of poor sleep quality among the elderly in nursing homes is relatively high. Besides, anxiety symptoms has additive interactions with age, chronic disease and social support for poor sleep quality. These findings have significant implications for interventions that aim to improve sleep quality among elderly residents in nursing homes. ]]> <![CDATA[Epidemiological characteristics of obstructive sleep apnea in a hospital-based historical cohort in Lebanon]]> https://www.researchpad.co/article/elastic_article_14697 The objective of our study was to characterize and analyze the associations between OSA (obstructive sleep apnea) and other clinical variables in adult patients referred for sleep evaluation by polysomnography at a referral center in Beirut, Lebanon, in terms of sociodemographic features, symptoms presentation and comorbidities, and evaluate the burden of comorbidities associated with this disease. All individuals with suspected Sleep Apnea referred (January 2010-September 2017) for a one-night polysomnography were included. Demographics, self-reported symptoms and comorbidities were documented. The relationship between OSA severity and the presence of symptoms and comorbidities were evaluated using multivariate logistic regression. Overall, 663 subjects were assessed. Of these, 57.3% were referred from chest physicians, and sleep test results were abnormal in 589 subjects (88.8%) of whom 526 patients (89.3%) fulfilled diagnostic criteria for OSA; 76.3% were men and women were on average older. OSA was severe in 43.2% and more severe in men. Almost all patients were symptomatic with ~2–4 symptoms per patient and women presented with symptoms that are more atypical. Comorbidities were significantly higher in women. In the multivariate analysis, age, male sex, obesity, symptoms of snoring, excessive daytime somnolence and witnessed apneas were associated with OSA severity. Only age and obesity were associated with self-reported diagnosis of hypertension and diabetes. This is the first study in Lebanon to explore the characteristics of patients with polysomnography-diagnosed OSA. High prevalence of severe OSA and low referral rates in the medical community support promoting awareness for an earlier diagnosis and more personalized approach in this country.

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<![CDATA[Risk and protective factors for post-traumatic stress among New Zealand military personnel: A cross sectional study]]> https://www.researchpad.co/article/N88434cd0-9137-4283-905a-485946610b9a

Background

Post-traumatic stress (PTS) is prevalent among military personnel. Knowledge of the risk and protective factors associated with PTS in this population may assist with identifying personnel who would benefit from increased or targeted support.

Aims

To examine factors associated with PTS among New Zealand military personnel.

Methods

For this cross-sectional study, currently serving and retired military personnel were invited to complete a questionnaire. The questionnaire included a measure of PTS (the Military Post-traumatic Stress Disorder Checklist; PCL-M), where scores ≥30 indicate the experience of significant PTS symptoms and scores ≥45 indicate a presumptive clinical diagnosis of post-traumatic stress. Potential risk and protective factors associated with PTS were examined using logistic regression modelling.

Results

1817 military personnel completed the questionnaire. PCL-M scores were ≥30 for 549 (30%) participants and ≥45 for 179 (10%) participants. Factors associated with higher PCL-M scores were trauma exposure, older age, male sex, and Māori ethnicity. Factors associated with lower PCL-M scores were greater length of service, psychological flexibility, and better quality sleep.

Conclusions

PTS was found to be prevalent among New Zealand military personnel. The experience of trauma was strongly associated with PTS. However, factors such as psychological flexibility (the ability to adapt to changes in circumstances) and good sleep were protective, suggesting that these factors could be key targets for interventions designed to reduce PTS among military personnel in New Zealand.

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<![CDATA[Nocturnal hypercapnia with daytime normocapnia in patients with advanced pulmonary arterial hypertension awaiting lung transplantation]]> https://www.researchpad.co/article/Nacc6463a-eb28-4f4a-acf0-c81fc9df01f4

Background

Pulmonary arterial hypertension (PAH) is frequently complicated by sleep disordered breathing (SDB), and previous studies have largely focused on hypoxemic SDB. Even though nocturnal hypercapnia was shown to exacerbate pulmonary hypertension, the clinical significance of nocturnal hypercapnia among PAH patients has been scarcely investigated.

Method

Seventeen patients with PAH were identified from 246 consecutive patients referred to Kyoto University Hospital for the evaluation of lung transplant registration from January 2010 to December 2017. Included in this study were 13 patients whose nocturnal transcutaneous carbon dioxide partial pressure (PtcCO2) monitoring data were available. Nocturnal hypercapnia was diagnosed according to the guidelines of the American Academy of Sleep Medicine. Associations of nocturnal PtcCO2 measurements with clinical features, the findings of right heart catheterization and pulmonary function parameters were evaluated.

Results

Nocturnal hypercapnia was diagnosed in six patients (46.2%), while no patient had daytime hypercapnia. Of note, nocturnal hypercapnia was found for 5 out of 6 patients with idiopathic PAH (83.3%). Mean nocturnal PtcCO2 levels correlated negatively with the percentage of predicted total lung capacity (TLC), and positively with cardiac output and cardiac index.

Conclusion

Nocturnal hypercapnia was prevalent among advanced PAH patients who were waiting for lung transplantation, and associated with %TLC. Nocturnal hypercapnia was associated with the increase in cardiac output, which might potentially worsen pulmonary hypertension especially during sleep. Further studies are needed to investigate hemodynamics during sleep and to clarify whether nocturnal hypercapnia can be a therapeutic target for PAH patients.

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<![CDATA[Impact of moderate to severe obstructive sleep apnea on the cognition in idiopathic pulmonary fibrosis]]> https://www.researchpad.co/article/5c5df31bd5eed0c484580d2d

Introduction

Idiopathic pulmonary fibrosis (IPF) is a relentlessly progressive lung disease with a fatal prognosis to whose rapid evolution multiple comorbidities may contribute, one of the most common being obstructive sleep apnea (OSA). There are several potential factors and conditions for the emergence of a cognitive deficit in relation to IPF or associated morbidities.

Objectives

The goals of this study were to assess cognition in patients with IPF in stable phase and to identify clinical cognition modifiers.

Methods

In a cross-sectional study, 23 patients with IPF were evaluated using Montreal Cognitive Assessment (MoCA), an instrument for detecting mild cognitive impairments and were screened for OSA through overnight cardiorespiratory polygraphy and for anxiety and depression with three specific scale (Generalized Anxiety Disorder 7-item scale: GAD-7; the Patient Health Questionnaire: PHQ-9; Hospital Anxiety and Depression Scale: HADS).

Results

MoCA score was lower in patients with IPF when compared to controls subjects (24 [21,26] vs. 27 [26,28], p = 0.003) but not as significantly as in COPD patients (21 [18.8,23.3], p<0.0001). OSA was diagnosed in 19 (82.6%) IPF patients, 12 patients showed the presence of moderate-severe forms (63.15%). IPF patients with cognitive impairment (MoCA<23) exhibit a higher severity of OSA (apneea hypopnea index–AHI: 33.0±19.1 vs. 12.44±8.2, p = 0.018), and a higher Epworth score (7.1±3.3 vs. 4.3±1.8, p = 0.013). Anxiety and depression scores were not correlated with MoCA results.

Conclusions

Impaired cognition in patients with IPF is mild and affect the areas of visuospatial abilities, language and working memory. OSA could be a possible predictor of IPF cognition deficit. Given the high prevalence of multiple types of sleep disorders in IPF patients, these should be investigated at least by cardiorespiratory polygraphy.

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<![CDATA[The influence of sleep apnea syndrome and intermittent hypoxia in carotid adventitial vasa vasorum]]> https://www.researchpad.co/article/5c63397cd5eed0c484ae689b

Subjects with sleep apnea-hypopnea syndrome (SAHS) show an increased carotid intima-media thickness. However, no data exist about earlier markers of atheromatous disease, such as the proliferation and expansion of the adventitial vasa vasorum (VV) to the avascular intima in this setting. Our aim was to assess carotid VV density and its relationship with sleep parameters in a cohort of obese patients without prior vascular events. A total of 55 subjects evaluated for bariatric surgery were prospectively recruited. A non-attended respiratory polygraphy was performed. The apnea-hypopnea index (AHI) and the cumulative percentage of time spent with oxygen saturation below 90% (CT90) were assessed. Serum concentrations of soluble intercellular adhesion molecule 1, P-selectin, lipocalin-2 and soluble vascular cell adhesion molecule 1 (sVCAM-1) were measured. Contrast-enhanced carotid ultrasound was used to assess the VV density. Patients with SAHS (80%) showed a higher adventitial VV density (0.801±0.125 vs. 0.697±0.082, p = 0.005) and higher levels of sVCAM-1 (745.2±137.8 vs. 643.3±122.7 ng/ml, p = 0.035) than subjects with an AHI lower than 10 events/hour. In addition, a positive association exist between mean VV density and AHI (r = 0.445, p = 0.001) and CT90 (r = 0.399, p = 0.005). Finally, in the multiple linear regression analysis, female sex, fasting plasma glucose and AHI (but not CT90) were the only variables independently associated with the mean adventitial VV density (R2 = 0.327). In conclusion, a high VV density is present in obese subjects with SAHS, and chronic intermittent hypoxia is pointed as an independent risk factor for the development of this early step of atheromatous disease.

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<![CDATA[Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia]]> https://www.researchpad.co/article/5c478c95d5eed0c484bd3414

Dementia is a neurological and cognitive condition that affects millions of people around the world. At any given time in the United Kingdom, 1 in 4 hospital beds are occupied by a person with dementia, while about 22% of these hospital admissions are due to preventable causes. In this paper we discuss using Internet of Things (IoT) technologies and in-home sensory devices in combination with machine learning techniques to monitor health and well-being of people with dementia. This will allow us to provide more effective and preventative care and reduce preventable hospital admissions. One of the unique aspects of this work is combining environmental data with physiological data collected via low cost in-home sensory devices to extract actionable information regarding the health and well-being of people with dementia in their own home environment. We have worked with clinicians to design our machine learning algorithms where we focused on developing solutions for real-world settings. In our solutions, we avoid generating too many alerts/alarms to prevent increasing the monitoring and support workload. We have designed an algorithm to detect Urinary Tract Infections (UTI) which is one of the top five reasons of hospital admissions for people with dementia (around 9% of hospital admissions for people with dementia in the UK). To develop the UTI detection algorithm, we have used a Non-negative Matrix Factorisation (NMF) technique to extract latent factors from raw observation and use them for clustering and identifying the possible UTI cases. In addition, we have designed an algorithm for detecting changes in activity patterns to identify early symptoms of cognitive decline or health decline in order to provide personalised and preventative care services. For this purpose, we have used an Isolation Forest (iForest) technique to create a holistic view of the daily activity patterns. This paper describes the algorithms and discusses the evaluation of the work using a large set of real-world data collected from a trial with people with dementia and their caregivers.

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<![CDATA[Adhesion molecule gene variants and plasma protein levels in patients with suspected obstructive sleep apnea]]> https://www.researchpad.co/article/5c605a1dd5eed0c4847cc9bd

Study objectives

Untreated obstructive sleep apnea (OSA) patients have an increased risk of cardiovascular disease (CVD). Adhesion molecules, including soluble E-selectin (sE-selectin), intercellular adhesion molecule-1 (ICAM-1), and vascular adhesion molecule-1 (VCAM-1), are associated with incident CVD. We hypothesized that specific genetic variants will be associated with plasma levels of adhesion molecules in suspected OSA patients. We also hypothesized that there may be an interaction between these variants and OSA.

Methods

We measured levels of sE-selectin, sICAM-1 and sVCAM-1 in 491 patients with suspected OSA and genotyped them for 20 polymorphisms.

Results

The most significant association was between the ABO rs579459 polymorphism and sE-selectin levels (P = 7×10−21), with the major allele T associated with higher levels. The direction of effect and proportion of the variance in sE-selectin levels accounted for by rs579459 (16%) was consistent with estimates from non-OSA cohorts. In a multivariate regression analysis, addition of rs579459 improved the model performance in predicting sE-selectin levels. Three polymorphisms were nominally associated with sICAM-1 levels but none with sVCAM-1 levels. The combination of severe OSA and two rs579459 T alleles identified a group of patients with high sE-selectin levels; however, the increase in sE-selectin levels associated with severe OSA was greater in patients without two T alleles (P = 0.05 test for interaction).

Conclusions

These genetic polymorphisms may help to identify patients at greatest risk of incident CVD and may help in developing a more precision-based approach to OSA care.

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<![CDATA[AMPK signaling linked to the schizophrenia-associated 1q21.1 deletion is required for neuronal and sleep maintenance]]> https://www.researchpad.co/article/5c23f31ad5eed0c48404a683

The human 1q21.1 deletion of ten genes is associated with increased risk of schizophrenia. This deletion involves the β-subunit of the AMP-activated protein kinase (AMPK) complex, a key energy sensor in the cell. Although neurons have a high demand for energy and low capacity to store nutrients, the role of AMPK in neuronal physiology is poorly defined. Here we show that AMPK is important in the nervous system for maintaining neuronal integrity and for stress survival and longevity in Drosophila. To understand the impact of this signaling system on behavior and its potential contribution to the 1q21.1 deletion syndrome, we focused on sleep, an important role of which is proposed to be the reestablishment of neuronal energy levels that are diminished during energy-demanding wakefulness. Sleep disturbances are one of the most common problems affecting individuals with psychiatric disorders. We show that AMPK is required for maintenance of proper sleep architecture and for sleep recovery following sleep deprivation. Neuronal AMPKβ loss specifically leads to sleep fragmentation and causes dysregulation of genes believed to play a role in sleep homeostasis. Our data also suggest that AMPKβ loss may contribute to the increased risk of developing mental disorders and sleep disturbances associated with the human 1q21.1 deletion.

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<![CDATA[The validity of two commercially-available sleep trackers and actigraphy for assessment of sleep parameters in obstructive sleep apnea patients]]> https://www.researchpad.co/article/5c3fa560d5eed0c484ca3a0a

Objective

The use of activity and sleep trackers that operate through dedicated smartphone applications has become popular in the general population. However, the validity of the data they provide has been disappointing and only Total Sleep Time (TST) is reliably recorded in healthy individuals for any of the devices tested. The purpose of this study was to evaluate the ability of two sleep trackers (Withings pulse 02 (W) and Jawbone Up (U)) to measure sleep parameters in patients suffering from obstructive sleep apnea (OSA).

Methods

All patients evaluated for OSA in our sleep laboratory underwent overnight polysomnography (PSG). PSG was conducted simultaneously with three other devices: two consumer-level sleep monitors (U and W) and one actigraph (Bodymedia SenseWear Pro Armband (SWA)).

Results

Of 36 patients evaluated, 22 (17 men) were diagnosed with OSA (mean apnea-hypopnea index of 37+ 23/h). Single comparisons of sleep trackers (U and W) and actigraph (SWA) were performed. Compared to PSG, SWA correctly assessed TST and Wake After Sleep Onset (WASO), and U and W correctly assessed Time In Bed (TIB) and light sleep. Intraclass correlations (ICC) revealed poor validity for all parameters and devices, except for WASO assessed by SWA.

Conclusions

This is the first study assessing the validity of sleep trackers in OSA patients. In this series, we have confirmed the limited performance of wearable sleep monitors that has been previously observed in healthy subjects. In OSA patients, wearable app-based health technologies provide a good estimation of TIB and light sleep but with very poor ICC.

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<![CDATA[Wavelet analysis of oximetry recordings to assist in the automated detection of moderate-to-severe pediatric sleep apnea-hypopnea syndrome]]> https://www.researchpad.co/article/5c141eb6d5eed0c484d27e15

Background

The gold standard for pediatric sleep apnea hypopnea syndrome (SAHS) is overnight polysomnography, which has several limitations. Thus, simplified diagnosis techniques become necessary.

Objective

The aim of this study is twofold: (i) to analyze the blood oxygen saturation (SpO2) signal from nocturnal oximetry by means of features from the wavelet transform in order to characterize pediatric SAHS; (ii) to evaluate the usefulness of the extracted features to assist in the detection of pediatric SAHS.

Methods

981 SpO2 signals from children ranging 2–13 years of age were used. Discrete wavelet transform (DWT) was employed due to its suitability to deal with non-stationary signals as well as the ability to analyze the SAHS-related low frequency components of the SpO2 signal with high resolution. In addition, 3% oxygen desaturation index (ODI3), statistical moments and power spectral density (PSD) features were computed. Fast correlation-based filter was applied to select a feature subset. This subset fed three classifiers (logistic regression, support vector machines (SVM), and multilayer perceptron) trained to determine the presence of moderate-to-severe pediatric SAHS (apnea-hypopnea index cutoff ≥ 5 events per hour).

Results

The wavelet entropy and features computed in the D9 detail level of the DWT reached significant differences associated with the presence of SAHS. All the proposed classifiers fed with a selected feature subset composed of ODI3, statistical moments, PSD, and DWT features outperformed every single feature. SVM reached the highest performance. It achieved 84.0% accuracy (71.9% sensitivity, 91.1% specificity), outperforming state-of-the-art studies in the detection of moderate-to-severe SAHS using the SpO2 signal alone.

Conclusion

Wavelet analysis could be a reliable tool to analyze the oximetry signal in order to assist in the automated detection of moderate-to-severe pediatric SAHS. Hence, pediatric subjects suffering from moderate-to-severe SAHS could benefit from an accurate simplified screening test only using the SpO2 signal.

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<![CDATA[A phenotype of increased sleepiness in a mouse model of pulmonary hypertension and right ventricular hypertrophy]]> https://www.researchpad.co/article/5c141f0ad5eed0c484d29621

The relationship between cardiovascular disease and abnormalities in sleep architecture is complex and bi-directional. Sleep disordered breathing (SDB) often confounds human studies examining sleep in the setting of heart failure, and the independent impact of isolated right or left heart failure on sleep is difficult to assess. We utilized an animal model of right heart failure using pulmonary artery banding (PAB) in mice to examine the causal effect of right heart failure on sleep architecture. Four weeks after PAB or sham (control) surgery, sleep was measured by polysomnography for 48 hours and right ventricular (RV) hypertrophy confirmed prior to sacrifice. PAB resulted in right ventricular hypertrophy based on a 30% increase in the Fulton Index (p < 0.01). After PAB, mice spent significantly more time in NREM sleep compared to the control group over a 24 hour period (53.5 ± 1.5% vs. 46.6 ± 1.4%; p < 0.01) and exhibited an inability to both cycle into REM sleep and decrease delta density across the light/sleep period. Our results support a phenotype of impaired sleep cycling and increased ‘sleepiness’ in a mouse model of RV dysfunction.

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<![CDATA[Evidence of Increased Muscle Atrophy and Impaired Quality of Life Parameters in Patients with Uremic Restless Legs Syndrome]]> https://www.researchpad.co/article/5989daa4ab0ee8fa60ba6c1d

Background

Restless Legs Syndrome is a very common disorder in hemodialysis patients. Restless Legs Syndrome negatively affects quality of life; however it is not clear whether this is due to mental or physical parameters and whether an association exists between the syndrome and parameters affecting survival.

Methodοlogy/Principal Findings

Using the Restless Legs Syndrome criteria and the presence of Periodic Limb Movements in Sleep (PLMS/h >15), 70 clinically stable hemodialysis patients were assessed and divided into the RLS (n = 30) and non-RLS (n = 40) groups. Physical performance was evaluated by a battery of tests: body composition by dual energy X ray absorptiometry, muscle size and composition by computer tomography, while depression symptoms, perception of sleep quality and quality of life were assessed through validated questionnaires. In this cross sectional analysis, the RLS group showed evidence of thigh muscle atrophy compared to the non-RLS group. Sleep quality and depression score were found to be significantly impaired in the RLS group. The mental component of the quality of life questionnaire appeared significantly diminished in the RLS group, reducing thus the overall quality of life score. In contrast, there were no significant differences between groups in any of the physical performance tests, body and muscle composition.

Conclusions

The low level of quality of life reported by the HD patients with Restless Legs Syndrome seems to be due mainly to mental health and sleep related aspects. Increased evidence of muscle atrophy is also observed in the RLS group and possibly can be attributed to the lack of restorative sleep.

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<![CDATA[Association between fibromyalgia syndrome and peptic ulcer disease development]]> https://www.researchpad.co/article/5989db50ab0ee8fa60bdc1ab

Purpose

The correlation of fibromyalgia syndrome (FMS) with peptic ulcer disease (PUD) is unclear. We therefore conducted a cohort study to investigate whether FMS is correlated with an increased risk of PUD.

Methods

In this study, we established an FMS cohort comprising 26068 patients aged more than 20 years who were diagnosed with FMS from 2000 to 2011. Furthermore, we established a control cohort by randomly choosing 104269 people without FMS who were matched to the FMS patients by gender, age, and index year. All patients were free of PUD at the baseline. Cox proportional hazard regressions were performed to compute the hazard ratio of PUD after adjustment for demographic characteristics and comorbidities.

Results

The prevalence of comorbidities was significantly higher in the FMS patients than in the controls. The incidence of PUD was 29.8 and 19.4 per 1000 person-years in the FMS and control cohorts, respectively. In addition, the FMS cohort exhibited a 1.40-fold higher risk of PUD (95% confidence interval = 1.35–1.45) compared with the control cohort. After control for confounding factors, the medications (selective serotonin reuptake inhibitors, serotonin–norepinephrine reuptake inhibitors, and antidepressants) taken by the FMS patients did not increase the risk of PUD.

Conclusion

FMS patients exhibit a higher risk of PUD than that of patients without FMS.

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<![CDATA[The Accuracy of Portable Monitoring in Diagnosing Significant Sleep Disordered Breathing in Hospitalized Patients]]> https://www.researchpad.co/article/5989daffab0ee8fa60bc5e1e

Background

Polysomnograms are not always feasible when sleep disordered breathing (SDB) is suspected in hospitalized patients. Portable monitoring is a practical alternative; however, it has not been recommended in patients with comorbidities.

Objective

We evaluated the accuracy of portable monitoring in hospitalized patients suspected of having SDB.

Design

Prospective observational study.

Setting

Large, public, urban, teaching hospital in the United States.

Participants

Hospitalized patients suspected of having SDB.

Methods

Patients underwent portable monitoring combined with actigraphy during the hospitalization and then polysomnography after discharge. We determined the accuracy of portable monitoring in predicting moderate to severe SDB and the agreement between the apnea hypopnea index measured by portable monitor (AHIPM) and by polysomnogram (AHIPSG).

Results

Seventy-one symptomatic patients completed both tests. The median time between the two tests was 97 days (IQR 25–75: 24–109). Forty-five percent were hospitalized for cardiovascular disease. Mean age was 52±10 years, 41% were women, and the majority had symptoms of SDB. Based on AHIPSG, SDB was moderate in 9 patients and severe in 39. The area under the receiver operator characteristics curve for AHIPM was 0.8, and increased to 0.86 in patients without central sleep apnea; it was 0.88 in the 31 patients with hypercapnia. For predicting moderate to severe SDB, an AHIPM of 14 had a sensitivity of 90%, and an AHIPM of 36 had a specificity of 87%. The mean±SD difference between AHIPM and AHIPSG was 2±29 event/hr.

Conclusion

In hospitalized, symptomatic patients, portable monitoring is reasonably accurate in detecting moderate to severe SDB.

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<![CDATA[Correlation Analysis between Polysomnography Diagnostic Indices and Heart Rate Variability Parameters among Patients with Obstructive Sleep Apnea Hypopnea Syndrome]]> https://www.researchpad.co/article/5989daa1ab0ee8fa60ba5ec5

Heart rate variability (HRV) can reflect the changes in the autonomic nervous system (ANS) that are affected by apnea or hypopnea events among patients with obstructive sleep apnea hypopnea syndrome (OSAHS). To evaluate the possibility of using HRV to screen for OSAHS, we investigated the relationship between HRV and polysomnography (PSG) diagnostic indices using electrocardiography (ECG) and PSG data from 25 patients with OSAHS and 27 healthy participants. We evaluated the relationship between various PSG diagnostic indices (including the apnea hypopnea index [AHI], micro-arousal index [MI], oxygen desaturation index [ODI]) and heart rate variability (HRV) parameters using Spearman’s correlation analysis. Moreover, we used multiple linear regression analyses to construct linear models for the AHI, MI, and ODI. In our analysis, the AHI was significantly associated with relative powers of very low frequency (VLF [%]) (r = 0.641, P = 0.001), relative powers of high frequency (HF [%]) (r = -0.586, P = 0.002), ratio between low frequency and high frequency powers (LF/HF) (r = 0.545, P = 0.049), normalized powers of low frequency (LF [n.u.]) (r = 0.506, P = 0.004), and normalized powers of high frequency (HF [n.u.]) (r = -0.506, P = 0.010) among patients with OSAHS. The MI was significantly related to standard deviation of RR intervals (SDNN) (r = 0.550, P = 0.031), VLF [%] (r = 0.626, P = 0.001), HF [%] (r = -0.632, P = 0.001), LF/HF (r = 0.591, P = 0.011), LF [n.u.] (r = 0.553, P = 0.004), HF [n.u.] (r = -0.553, P = 0.004), and absolute powers of very low frequency (VLF [abs]) (r = 0.525, P = 0.007) among patients with OSAHS. The ODI was significantly correlated with VLF [%] (r = 0.617, P = 0.001), HF [%] (r = -0.574, P = 0.003), LF [n.u.] (r = 0.510, P = 0.012), and HF [n.u.] (r = -0.510, P = 0.012) among patients with OSAHS. The linear models for the PSG diagnostic indices were AHI = -38.357+1.318VLF [%], MI = -13.389+11.297LF/HF+0.266SDNN, and ODI = -55.588+1.715VLF [%]. However, the PSG diagnostic indices were not related to the HRV parameters among healthy participants. Our analysis suggests that HRV parameters are powerful tools to screen for OSAHS patients in place of PSG monitoring.

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<![CDATA[Cerebrospinal Fluid Hypocretin-1 (Orexin-A) Level Fluctuates with Season and Correlates with Day Length]]> https://www.researchpad.co/article/5989da4eab0ee8fa60b8d50a

The hypocretin/orexin neuropeptides (hcrt) are key players in the control of sleep and wakefulness evidenced by the fact that lack of hcrt leads to the sleep disorder Narcolepsy Type 1. Sleep disturbances are common in mood disorders, and hcrt has been suggested to be poorly regulated in depressed subjects. To study seasonal variation in hcrt levels, we obtained data on hcrt-1 levels in the cerebrospinal fluid (CSF) from 227 human individuals evaluated for central hypersomnias at a Danish sleep center. The samples were taken over a 4 year timespan, and obtained in the morning hours, thus avoiding impact of the diurnal hcrt variation. Hcrt-1 concentration was determined in a standardized radioimmunoassay. Using biometric data and sleep parameters, a multivariate regression analysis was performed. We found that the average monthly CSF hcrt-1 levels varied significantly across the seasons following a sine wave with its peak in the summer (June—July). The amplitude was 19.9 pg hcrt/mL [12.8–26.9] corresponding to a 10.6% increase in midsummer compared to winter. Factors found to significantly predict the hcrt-1 values were day length, presence of snow, and proximity to the Christmas holiday season. The hcrt-1 values from January were much higher than predicted from the model, suggestive of additional factors influencing the CSF hcrt-1 levels such as social interaction. This study provides evidence that human CSF hcrt-1 levels vary with season, correlating with day length. This finding could have implications for the understanding of winter tiredness, fatigue, and seasonal affective disorder. This is the first time a seasonal variation of hcrt-1 levels has been shown, demonstrating that the hcrt system is, like other neurotransmitter systems, subjected to long term modulation.

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<![CDATA[Short Meditation Trainings Enhance Non-REM Sleep Low-Frequency Oscillations]]> https://www.researchpad.co/article/5989dae4ab0ee8fa60bbcc70

Study Objectives

We have recently shown higher parietal-occipital EEG gamma activity during sleep in long-term meditators compared to meditation-naive individuals. This gamma increase was specific for NREM sleep, was present throughout the entire night and correlated with meditation expertise, thus suggesting underlying long-lasting neuroplastic changes induced through prolonged training. The aim of this study was to explore the neuroplastic changes acutely induced by 2 intensive days of different meditation practices in the same group of practitioners. We also repeated baseline recordings in a meditation-naive cohort to account for time effects on sleep EEG activity.

Design

High-density EEG recordings of human brain activity were acquired over the course of whole sleep nights following intervention.

Setting

Sound-attenuated sleep research room.

Patients or Participants

Twenty-four long-term meditators and twenty-four meditation-naïve controls.

Interventions

Two 8-h sessions of either a mindfulness-based meditation or a form of meditation designed to cultivate compassion and loving kindness, hereafter referred to as compassion meditation.

Measurements and Results

We found an increase in EEG low-frequency oscillatory activities (1–12 Hz, centered around 7–8 Hz) over prefrontal and left parietal electrodes across whole night NREM cycles. This power increase peaked early in the night and extended during the third cycle to high-frequencies up to the gamma range (25–40 Hz). There was no difference in sleep EEG activity between meditation styles in long-term meditators nor in the meditation naïve group across different time points. Furthermore, the prefrontal-parietal changes were dependent on meditation life experience.

Conclusions

This low-frequency prefrontal-parietal activation likely reflects acute, meditation-related plastic changes occurring during wakefulness, and may underlie a top-down regulation from frontal and anterior parietal areas to the posterior parietal and occipital regions showing chronic, long-lasting plastic changes in long-term meditators.

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<![CDATA[The Spread of Sleep Loss Influences Drug Use in Adolescent Social Networks]]> https://www.researchpad.co/article/5989da1aab0ee8fa60b7c61b

Troubled sleep is a commonly cited consequence of adolescent drug use, but it has rarely been studied as a cause. Nor have there been any studies of the extent to which sleep behavior can spread in social networks from person to person to person. Here we map the social networks of 8,349 adolescents in order to study how sleep behavior spreads, how drug use behavior spreads, and how a friend's sleep behavior influences one's own drug use. We find clusters of poor sleep behavior and drug use that extend up to four degrees of separation (to one's friends' friends' friends' friends) in the social network. Prospective regression models show that being central in the network negatively influences future sleep outcomes, but not vice versa. Moreover, if a friend sleeps ≤7 hours, it increases the likelihood a person sleeps ≤7 hours by 11%. If a friend uses marijuana, it increases the likelihood of marijuana use by 110%. Finally, the likelihood that an individual uses drugs increases by 19% when a friend sleeps ≤7 hours, and a mediation analysis shows that 20% of this effect results from the spread of sleep behavior from one person to another. This is the first study to suggest that the spread of one behavior in social networks influences the spread of another. The results indicate that interventions should focus on healthy sleep to prevent drug use and targeting specific individuals may improve outcomes across the entire social network.

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<![CDATA[Total Sleep Time Severely Drops during Adolescence]]> https://www.researchpad.co/article/5989d9f5ab0ee8fa60b6fcb1

Restricted sleep duration among young adults and adolescents has been shown to increase the risk of morbidities such as obesity, diabetes or accidents. However there are few epidemiological studies on normal total sleep time (TST) in representative groups of teen-agers which allow to get normative data.

Purpose

To explore perceived total sleep time on schooldays (TSTS) and non schooldays (TSTN) and the prevalence of sleep initiating insomnia among a nationally representative sample of teenagers.

Methods

Data from 9,251 children aged 11 to 15 years-old, 50.7% of which were boys, as part of the cross-national study 2011 HBSC were analyzed. Self-completion questionnaires were administered in classrooms. An estimate of TSTS and TSTN (week-ends and vacations) was calculated based on specifically designed sleep habits report. Sleep deprivation was estimated by a TSTN – TSTS difference >2 hours. Sleep initiating nsomnia was assessed according to International classification of sleep disorders (ICSD 2). Children who reported sleeping 7 hours or less per night were considered as short sleepers.

Results

A serious drop of TST was observed between 11 yo and 15 yo, both during the schooldays (9 hours 26 minutes vs. 7 h 55 min.; p<0.001) and at a lesser extent during week-ends (10 h 17 min. vs. 9 h 44 min.; p<0.001). Sleep deprivation concerned 16.0% of chidren aged of 11 yo vs. 40.5% of those of 15 yo (p<0.001). Too short sleep was reported by 2.6% of the 11 yo vs. 24.6% of the 15 yo (p<0.001).

Conclusion

Despite the obvious need for sleep in adolescence, TST drastically decreases with age among children from 11 to 15 yo which creates significant sleep debt increasing with age.

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