Sleep medicine最新文献

Objective

Methods

Results

Conclusions

Study objectives

Methods

Results

Conclusions

Background

Methodology

Results

Conclusion

Objective/Background

Patients/methods

Results

Conclusions

Background

Sleep paralysis (SP) is a rapid eye movement (REM) parasomnia that occurs during the transition between wakefulness and sleep. During this brief state, a person is conscious but unable to move or speak, often experiencing hallucinations. It is ‘isolated’ when it occurs without other symptoms of narcolepsy or sleep disorders. Despite its prevalence, much remains unknown about its clinical features and associated beliefs.

Objectives

This study examines the frequency of self-reported SP experiences and its associated demographic characteristics, along with participants' beliefs about the condition.

Methods

A cross-sectional survey was conducted among visitors at a shopping mall, using the Unusual Sleep Experiences Questionnaire (USEQ) to assess the features of SP episodes and the common beliefs surrounding them.

Results

A total of 350 participants were surveyed (mean age = 25.5 ± 9.30 years; 55.4 % females). Participants who experienced SP at least once in their life time (39.1 %) reported feeling pressure on their chest (67.2 %), an inability to open their eyes (71.5 %), and difficulty speaking (81.0 %) during the episode. The majority of the individuals reported having their first episode at a young age (16–20 years). Most people (24.5 %) were unaware that this condition was known as sleep paralysis, and many (23.5 %) thought that it was just ‘a dream’.

Conclusion

Isolated sleep paralysis episodes are fairly prevalent, with many people experiencing their first episode at a young age. A typical episode entails a sense of pressure on the chest and difficulty in vocalizing. Misconceptions about the condition are common and wage further exploration.

Introduction

The diagnostic process for idiopathic hypersomnia (IH) is complex due to the diverse aetiologies of daytime somnolence, ambiguous pathophysiological understanding, and symptom variability. Current diagnostic instruments, such as the multiple sleep latency test (MSLT), are limited in their ability to fully represent IH's diverse nature. This study endeavours to delineate subgroups among IH patients via cluster analysis of polysomnographic data and to examine the temporal evolution of their symptomatology, aiming to enhance the granularity of understanding and individualized treatment approaches for IH.

Methods

This study included individuals referred to the Uppsala Centre for Sleep Disorders from 2010 to 2019, who were diagnosed with IH based on the International Classification of Sleep Disorders-3 (ICSD-3) criteria, following a thorough diagnostic evaluation. The final cohort, after excluding participants with incomplete data or significant comorbid sleep-related respiratory conditions, comprised 69 subjects, including 49 females and 20 males, with an average age of 40 years. Data were collected through polysomnography (PSG), MSLT, and standardized questionnaires. A two-step cluster analysis was employed to navigate the heterogeneity within IH, focusing on objective time allocation across different sleep stages and sleep efficiency derived from PSG. The study also aimed to track subgroup-specific changes in symptomatology over time, with follow-ups ranging from 21 to 179 months post-diagnosis.

Results

The two-step cluster analysis yielded two distinct groups with a satisfactory silhouette coefficient: Cluster 1 (n = 29; 42 %) and Cluster 2 (n = 40; 58 %). Cluster 1 exhibited increased deep sleep duration, reduced stage 2 sleep, and higher sleep maintenance efficiency compared to Cluster 2. Further analyses of non-clustering variables indicated shorter wake after sleep onset in Cluster 1, but no significant differences in other sleep parameters, MSLT outcomes, body mass index, age, or self-reported measures of sleep inertia or medication usage. Long-term follow-up assessments showed an overall improvement in excessive daytime sleepiness, with no significant inter-cluster differences.

Conclusion

This exploratory two-step cluster analysis of IH-diagnosed patients discerned two subgroups with distinct nocturnal sleep characteristics, aligning with prior findings and endorsing the notion that IH may encompass several phenotypes, each potentially requiring tailored therapeutic strategies. Further research is imperative to substantiate these findings.

Objective

To assesses the prevalence and co-occurrence of anxiety, depressive symptoms, suicidal thoughts, and hopelessness in patients with narcolepsy type 1 (NT1).

Patients/Methods. In this cross-sectional study, 127 patients with NT1 (mean age 38.2 ± 15.5 years, 53.5 % female) and 131 controls (mean age 37.4 ± 14.3 years, 59.5 % female) matched for age, sex, and education, filled in the following validated questionnaires: Beck Depression Inventory-II (BDI), State-Trait Anxiety Inventory (STAI), and Beck Hopelessness Scale (BHS). Comparisons between groups and multivariable logistic regression analyses were performed.

Results

Patients with NT1 presented significantly higher scores in BDI, suicidal thoughts (BDI-item-9), STAI-trait, STAI-state, and BHS than controls. Adjusted for age, sex, and educational level, NT1 was significantly associated with depressive symptoms (BDI≥13; OR 3.23, 95%CI 1.71–6.10), trait anxiety symptoms (STAI-trait≥38; OR 1.91, 95%CI 1.14–3.21), co-occurrence of BDI≥13 with STAI-trait≥38 (OR 2.72, 95%CI 1.47–5.05), and with STAI-state≥38 (OR 2.24, 95%CI 1.17–4.30), and moderate to severe hopelessness (BHS≥9; OR 2.95, 95%CI 1.55–5.63).

Conclusions

Patients with NT1 present a multidimensional psychiatric burden and comorbidity between symptoms of depression and anxiety and suicidal thoughts, a concern that deserves tailored interventions.

Insomnia, i.e., difficulties in sleep onset and sleep maintenance, may increase the risk of anxiety symptoms, although long-term follow-up studies are rarely reported. Here, we examined whether insomnia symptoms may predict anxiety symptoms in a 9-year follow-up, and whether inflammation may play a mediating role. Data from 1355 participants (63.44 ± 7.47 years, 55.1 % females) from the English Longitudinal Study of Ageing (ELSA) were analysed. Insomnia symptoms were assessed in 2012/13. High-sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation, was measured in 2016/17. Anxiety symptoms were assessed in 2020/21. After adjusting for confounders and baseline levels, structural equation modelling (SEM) revealed that insomnia symptoms significantly predicted anxiety symptoms (β = 0.357, p < .001) but not hs-CRP (β = −0.016, p = .634). Similarly, hs-CRP was not related to anxiety symptoms (β = −0.024, p = .453). The hs-CRP mediation hypothesis was therefore rejected (β = 0.0004; 95 % BCI -0.001 to 0.005), and multi-group SEM showed that sex did not moderate these paths. However, baseline diagnoses of anxiety disorders prospectively predicted higher hs-CRP (B = 0.083, p = .030). Results of the current study suggest that individuals with baseline anxiety disorders may be at higher risk of developing low-grade chronic inflammation. Several alternative psychophysiological mechanisms linking insomnia and anxiety symptoms should be explored, including autonomic and cortical pre-sleep arousal, cortisol reactivity, and pro-inflammatory cytokines. Finally, insomnia symptoms may be a treatment target to lower the risk of anxiety symptoms in elderly.

Introduction

Sleep disturbances including obstructive sleep apnea (OSA) and poor sleep quality are common after stroke, while its association with cognitive changes following transient ischemic attack (TIA) or mild stroke remains unclear. We aim to determine whether sleep duration, OSA parameters, or nocturnal hypoxemia is associated with a greater cognitive decline after stroke.

Methods

We prospectively followed-up patients with acute TIA/mild stroke [National Institute Health Stroke Scale (NIHSS) < 7] who underwent baseline sleep questionnaire [Pittsburgh Sleep Quality Index (PSQI)], and serial cognitive assessments [Montreal Cognitive Assessment (MoCA) 5-min, Stroop Test] at baseline and one-year. We also evaluated apnea-hypopnea index (AHI) and nocturnal hypoxemia by Home Sleep Apnea Test (HSAT) at one-year. Primary outcome was one-year change in MoCA 5-min score.

Results

One hundred and five patients with TIA/mild stroke (mean age 63 years, 65 % male) were included. Baseline short sleep (< 6 hour/night) and AHI $\ge$ 20/hour at one-year were independently associated with a decline in the MoCA 5-min total score after covariates adjustment [short sleep: β = −2.36 95 % confidence interval (CI) (−4.13, −0.59), p = 0.009; AHI $\ge$ 20/hour: β = −1.79 (−3.26, −0.32), p = 0.017; remained significant after multiple comparisons correction]. A lower mean MinSpO₂ was associated with a decline in executive function [Stroop interference index: β = 0.29 (0.04, 0.53), p = 0.021], but not with MoCA 5-min score at one-year. Moderation analysis indicated AHI $\ge$ 20/hour was associated with a pronounced decline in executive function only in men.

Conclusions

Short sleep after stroke onset, AHI $\ge$ 20/hour and nocturnal hypoxemia at one-year contributed to an impaired cognitive trajectory at one-year following stroke in patients with TIA/mild stroke.

Purpose

To quantitatively measure and compare whole-brain iron deposition between OSA patients and a healthy control group, we initially utilized QSM and evaluated its correlation with PSG results and cognitive function.

Materials and methods

A total of 28 OSA patients and 22 healthy control subjects matched in age, education level, and BMI were enrolled in our study. Each participant underwent scanning with 3D T1 and multi-echo GRE sequences. Additionally, PSG results were collected from OSA patients, and they underwent simple cognitive assessments. Finally, we analyzed the relationship between iron content in different brain regions, PSG results, and cognitive ability.

Results

In OSA patients, iron content increased in the left temporal-pole-sup and right putamen, while it decreased in the left fusiform gyrus, left middle temporal gyrus, right inferior occipital gyrus, and right superior temporal gyrus. The correlation analysis between brain iron content and PSG results/cognitive scales is as follows: left fusiform gyrus and MMSE (r = −0.416, p = 0.028); right superior temporal gyrus and MMSE (r = 0.422, p = 0.025); left middle temporal gyrus and average oxygen saturation (r = −0.418, p = 0.027); left temporal-pole-sup and REM stage (rs = 0.466, p = 0.012); the right putamen and N1 stage (rs = 0.393. p = 0.039). Moreover, both MoCA (r = 0.598, p = 0.001) and MMSE (r = 0.456, p = 0.015) show a positive correlation with average oxygen saturation.

Conclusion

This study is the first to use QSM technology to show abnormal brain iron levels in OSA. Correlations between brain iron content, PSG, and cognition in OSA may reveal neuropathological mechanisms, aiding OSA diagnosis.