Accuracy of Actigraphy Compared to Concomitant Ambulatory Polysomnography in Narcolepsy and Other Sleep Disorders

Estimating the prevalence and clinical causality of obstructive sleep apnea in paediatric narcolepsy patients

BACKGROUND

Numerous risk factors in paediatric narcolepsy may predispose them to obstructive sleep apnea (OSA). The concurrent presence of OSA in these patients might lead to underdiagnosing narcolepsy. This research investigates the prevalence and potential causality between OSA and paediatric narcolepsy.

METHODS

A case-control study coupled with a two-sample Mendelian randomization (MR) analysis was employed to explore the prevalence and causal link between paediatric narcolepsy and OSA risk.

RESULTS

The case-control study revealed that paediatric narcolepsy patients are at an increased risk of OSA, with an Odds ratio (OR) of 4.87 (95% CI: 2.20-10.71; P < 0.001). The inverse-variance weighted (IVW) model further suggests a potential causal link between narcolepsy and OSA (IVW OR: 4.671, 95% CI: 1.925-11.290; P < 0.001). Additionally, sensitivity analysis confirmed these findings' reliability.

CONCLUSION

The findings highlight an elevated prevalence and genetic susceptibility to OSA among paediatric narcolepsy patients, underscoring the necessity for clinical screening of OSA. Continued research is essential to clarify the pathogenic mechanisms and develop potential treatments.

Assessment of sleep parameters in adults with persistent post-concussive symptoms

OBJECTIVES

The primary aim of this study was to characterize sleep in adults with persistent post-concussive symptoms (PPCS). Secondary aims explored relationships between sleep parameters, injury characteristics, and symptom questionnaires.

METHODS

This case-controlled, cross-sectional study recruited adults (18-65yrs) diagnosed with PPCS and age and sex-matched controls. Participants wore a wrist-worn actigraph for 3-7 nights and completed daily sleep diaries. Participants completed questionnaires examining daytime sleepiness, fatigue, anxiety/depressive symptoms, and sedentariness. Sleep parameters were compared between groups using Mann-Whitney U tests. Secondary analyses used two-way ANOVA and Spearman's rank correlations.

RESULTS

Fifty adults with PPCS (43.7 ± 10.6yrs, 78 % female) and 50 controls (43.6 ± 11.0yrs) were included in this study. Adults with PPCS had significantly longer sleep onset latency (PPCS 16.99 ± 14.51min, Controls 8.87 ± 6.44min, p < 0.001) and total sleep time (PPCS 8.3 ± 1.0hrs, Control 7.6 ± 0.9hrs, p = 0.030) compared to controls, but woke up later (PPCS 7:57:27 ± 1:36:40, Control 7:17:16 ± 0:50:08, p = 0.026) and had poorer sleep efficiency (PPCS 77.9 ± 7.5 %, Control 80.8 ± 6.0 %, p = 0.019) than controls. Adults with PPCS reported more daytime sleepiness (Epworth Sleepiness Scale: PPCS 8.70 ± 4.61, Control 4.28 ± 2.79, p < 0.001) and fatigue (Fatigue Severity Scale: PPCS 56.54 ± 12.92, Control 21.90 ± 10.38, p < 0.001). Injury characteristics did not significantly affect sleep parameters in adults with PPCS. Actigraphy parameters were not significantly correlated to questionnaire measures.

CONCLUSION

Several actigraphy sleep parameters were significantly altered in adults with PPCS compared to controls, but did not correlate with sleep questionnaires, suggesting both are useful tools in characterizing sleep in PPCS. Further, this study provides potential treatment targets to improve sleep difficulties in adults with PPCS.

Temporal Feature Extraction and Machine Learning for Classification of Sleep Stages Using Telemetry Polysomnography

Accurate sleep stage detection is crucial for diagnosing sleep disorders and tailoring treatment plans. Polysomnography (PSG) is considered the gold standard for sleep assessment since it captures a diverse set of physiological signals. While various studies have employed complex neural networks for sleep staging using PSG, our research emphasises the efficacy of a simpler and more efficient architecture. We aimed to integrate a diverse set of feature extraction measures with straightforward machine learning, potentially offering a more efficient avenue for sleep staging. We also aimed to conduct a comprehensive comparative analysis of feature extraction measures, including the power spectral density, Higuchi fractal dimension, singular value decomposition entropy, permutation entropy, and detrended fluctuation analysis, coupled with several machine-learning models, including XGBoost, Extra Trees, Random Forest, and LightGBM. Furthermore, data augmentation methods like the Synthetic Minority Oversampling Technique were also employed to rectify the inherent class imbalance in sleep data. The subsequent results highlighted that the XGBoost classifier, when used with a combination of all feature extraction measures as an ensemble, achieved the highest performance, with accuracies of 87%, 90%, 93%, 96%, and 97% and average F1-scores of 84.6%, 89%, 90.33%, 93.5%, and 93.5% for distinguishing between five-stage, four-stage, three-stage, and two distinct two-stage sleep configurations, respectively. This combined feature extraction technique represents a novel addition to the body of research since it achieves higher performance than many recently developed deep neural networks by utilising simpler machine-learning models.

Actigraphy Analysis of Sleep Associates with Salivary IL-6 Concentration in Institutionalized Older Individuals

Sleep disorders are common in older individuals and are most prevalent in those who are institutionalized. Sleep complaints are often comorbid with medical and neuro-psychiatric illness and associated with polypharmacy. Various studies show an association between sleep disorders and altered levels of inflammatory cytokines, especially IL-6. In this study, an objective sleep analysis was performed using actigraphy, and IL-6 measurements in saliva in 61 older people residing in long-term nursing homes (72.1% women). Almost half (49.2%) of the people had no or mild cognitive impairment, and the rest suffered from moderate to severe dementia, mainly due to Alzheimer's disease (25 out of 31 individuals). A significant correlation was found between salivary IL6 and sleep parameters; e.g., less salivary IL-6 had significantly (p < 0.05) worse sleep efficiency and more night awakenings. In turn, actigraphy detected alterations in people with dementia in average sleep time, daily bedtime, and average daily time out of bed. There was no significant correlation between these sleep patterns and the total number of psychotropic drugs. No significant differences were found in salivary IL-6 between individuals with or without dementia. These results should be considered in future research with institutionalized people to detect sleep disturbances and to establish interventions aimed to improve sleep quality.

Four Weeks of a Neuro-Meditation Program Improves Sleep Quality and Reduces Hypertension in Nursing Staff During the COVID-19 Pandemic: A Parallel Randomized Controlled Trial

The purpose of this study was to examine the effectiveness of a neuro-meditation program to support nurses during the COVID-19 pandemic. Forty-five (10 men and 35 women) nurses were classified into three groups based on their systolic blood pressure: normotensive (G-nor; n = 16, 43.8 ± 11.0 year), hypertensive (G-hyp; n = 13, 45.2 ± 10.7 year) and control (G-con; n = 16, 44.9 ± 10.6 year). Using a parallel, randomly controlled design across a 4-week period, 10 × 30-min sessions using the Rebalance© Impulse were completed. Sleep was assessed by wrist actigraphy and subjective sleep questionnaires; perceived sleep quality, Ford Insomnia Response to Stress Test questionnaire and the Spiegel Sleep Quality questionnaire (SSQ). Blood pressure, resting heart rate, mean heart rate (HRmean), heart rate variability index (RMSSD), cortisol, and alpha-amylase were also measured. Statistical analysis was completed using factorial ANOVA. Sleep improved in the G-hyp group; SSQ (p < 0.01); perceived sleep quality (p < 0.01); sleep efficiency and fragmentation index (p < 0.05). In the G-nor group, sleep was improved to a lesser extent; perceived sleep quality (p < 0.01). A significant time-group interaction was reported in resting heart rate (p < 0.01), systolic blood pressure (p < 0.01), and diastolic blood pressure (p < 0.05) with these measures being significantly reduced in the G-hyp group. RMSSD increased in the G-nor group (p < 0.01). This initial evidence suggests that neuro-meditation reduces excessive sympathetic activity, promoting enhanced sleep quality and autonomic control during periods of increased work-related stress.

Clinical Trial Registration

The study was conducted at Bioesterel, Sophia-Antipolis, France as a clinical trial: Neuro-meditation improves sleep quality, https://www.drks.de/ui_data_web/DrksUI.html?locale=en, DRKS00025731.

Disrupted nighttime sleep and sleep instability in narcolepsy

STUDY OBJECTIVES

This review aimed to summarize current knowledge about disrupted nighttime sleep (DNS) and sleep instability in narcolepsy, including self-reported and objective assessments, potential causes of sleep instability, health consequences and functional burden, and management.

METHODS

One hundred two peer-reviewed publications from a PubMed search were included.

RESULTS

DNS is a key symptom of narcolepsy but has received less attention than excessive daytime sleepiness and cataplexy. There has been a lack of clarity regarding the definition of DNS, as many sleep-related symptoms and conditions disrupt sleep quality in narcolepsy (eg, hallucinations, sleep paralysis, rapid eye movement sleep behavior disorder, nightmares, restless legs syndrome/periodic leg movements, nocturnal eating, sleep apnea, depression, anxiety). In addition, the intrinsic sleep instability of narcolepsy results in frequent spontaneous wakings and sleep stage transitions, contributing to DNS. Sleep instability likely emerges in the setting of orexin insufficiency/deficiency, but its exact pathophysiology remains unknown. DNS impairs quality of life among people with narcolepsy, and more research is needed to determine its contributions to cardiovascular risk. Multimodal treatment is appropriate for DNS management, including behavioral therapies, counseling on sleep hygiene, and/or medication. There is strong evidence showing improvement in self-reported sleep quality and objective sleep stability measures with sodium oxybate, but rigorous clinical trials with other pharmacotherapies are needed. Treatment may be complicated by comorbidities, concomitant medications, and mood disorders.

CONCLUSIONS

DNS is a common symptom of narcolepsy deserving consideration in clinical care and future research.

CITATION

Maski K, Mignot E, Plazzi G, Dauvilliers Y. Disrupted nighttime sleep and sleep instability in narcolepsy. J Clin Sleep Med. 2022;18(1):289-304.