Sleep最新文献

Study objectives: To examine the prognostic value of the apnea-hypopnea index (AHI), desaturation severity parameters, and cardiac troponins alone and combined for major cardiovascular events (MACE).

Methods: MACE data were retrieved in 2021 from the Norwegian Patient Registry for 518 participants in the Akershus Sleep APnea (ASAP) cohort. Baseline polysomnography and fasting blood samples were collected between June 2006 and January 2008. Desaturation duration (DesDur) and severity (DesSev) were calculated using ABOSA software. Cox regression models estimated hazard ratios (HRs) for MACE. Predictive properties of combining troponins and obstructive sleep apnea (OSA) severity were calculated by comparing established clinical thresholds for cardiac troponin I (cTnI) and T (cTnT) with AHI clinical thresholds of ≥15 and ≥30 respectively.

Results: High AHI, DesDur, DesSev, cTnI, and cTnT associated with increased MACE risk. However, only cTnI independently predicted MACE after adjustment (HR: 1.74, 95% CI: 1.32-2.29). The HR for MACE was 2.68 (95% CI: 1.03-6.97) in patients with both high cTnI and AHI ≥30 events/h.

Conclusion: In this 15-year follow-up, cTnI associated independently with higher MACE risk, whereas the AHI, desaturation parameters, and cTnT were not independent predictors. cTnI, especially when combined with AHI, was a stronger MACE predictor than cTnT. Provided our findings are validated in clinical OSA populations, the measurement of cTnI may be considered for cardiovascular risk stratification.

Study objectives: The cerebral adenosinergic system is involved in sleep-wake regulation and presumably represents a neuro-molecular correlate of homeostatic sleep pressure. For acute sleep deprivation, it has been shown that increased cerebral A1 adenosine receptor (A1AR) availability was related to impairments in cognitive performance. The present study examined A1AR availability in response to chronic sleep restriction and recovery.

Methods: To quantify A1AR availability we used [18F]CPFPX positron emission tomography in 21 volunteers after 5 nights with 5-h sleep opportunities followed by 8 h recovery sleep. Data were compared to a control group of 15 volunteers who slept 8 h each night. In addition, polysomnography, cognitive performance, and alertness were recorded.

Results: Chronic sleep restriction did not increase the A1AR availability. Slow wave sleep (SWS) and EEG slow-wave-activity (SWA) in the first 5 h of sleep did not differ from baseline, but SWA in the last 3 h of sleep was increased and cognitive performance and alertness were impaired. While SWA returned to baseline in the last 3 h of recovery sleep, performance and alertness remained impaired.

Conclusion: The results indicate that chronic sleep loss likely induces parallel upregulations of extracellular adenosine and A1AR resulting in no net gain in receptor availability. The results contrast with findings from acute sleep deprivation in which we found impaired performance and increased A1AR availability that were restored to rested levels after recovery sleep. The findings reveal fundamental differences in the mechanisms through which acute and chronic sleep loss affect adenosinergic regulation and cognitive performance.

Study objectives: Adolescent brain maturation is characterized by profound structural changes to grey and white matter. While cross-sectional studies in youth indicate that measures such as sleep duration and regularity are linked to regional grey matter volumes, there is less evidence on how sleep may shape developmental trajectories over time. Therefore, the goal of this study was to test whether objectively measured sleep is a moderator of grey matter volume changes in early adolescence.

Methods: Structural MRI was acquired longitudinally at two time points six months apart in 39 healthy adolescents aged 10 to 14 years (mean age = 12.72 ± 1.00 years). Between the two MRI scans, we collected daily objective sleep/wake behavior using actigraphy (mean = 129.95 ± 34.01 nights). We then examined how sleep duration, efficiency, timing, and regularity moderate changes in seven regions-of-interest (ROIs) linked to social/emotional functioning using univariate simple moderation models for each ROI and sleep characteristic.

Results: Sleep duration and efficiency moderated grey matter volume changes in regions including the thalamus, precuneus, orbitofrontal cortex, and amygdala (.11 ≤ ΔR2 ≥ .50; .001 < p<.020). Shorter and more disrupted sleep was associated with attenuated structural changes. Sleep regularity and sleep midpoint further moderated changes in grey matter volume (.05 ≤ ΔR2 ≥ .30, .001 < p<.043), indicating a role for these parameters in brain development.

Conclusion: These findings highlight the potential role of sleep in adolescent neurodevelopment and underscore the potential for targeted interventions to support brain health during this critical window.

Initiating and maintaining sleep requires gating of sensory input. Sensory processing differences, such as elevated sensory reactivity, have emerged as a potential driver of sleep difficulties in autism. Both sensory and sleep difficulties are prevalent in autistic individuals and emerge early in development. Here, we use polysomnography to understand how infant sensory reactivity affects the ability to maintain sleep in a quiet or noisy environment. Forty-four 8- to 11-month-old infants at typical and elevated likelihood for autism participated in a lab-based nap study consisting of two counterbalanced visits, a baseline and an auditory stimulation condition. In the stimulation condition, 60dB pure tones were played during sleep. We measured slow waves and sleep spindles, EEG features previously linked to the ability to protect sleep from sensory disturbance. We show that higher caregiver-reported sensory reactivity was significantly associated with lower slow wave activity and density, across both nap conditions. In the stimulation condition, infants with elevated sensory reactivity had even further decreased slow wave density and lower sleep spindle density. Comparisons of pre- and post-stimulus windows showed that, rather than triggering immediate event-related disruptions, auditory input and sensory reactivity alter sleep micro-structure across the longer timescale of the entire nap. Thus, highly reactive infants experience disruptions in their ability to enter or maintain periods of sensory disconnection, accentuated by the presence of auditory noise.

Study objectives: Large long-term assessments of opioid effectiveness and dose stability for those with dopamine agonist augmentation of restless legs syndrome (RLS) are lacking. We present 5-year longitudinal findings from the National RLS Opioid Registry.

Methods: Five-hundred participants taking opioids for RLS were interviewed at baseline about RLS symptoms, opioid medications and doses, sleep and mental health. Participants subsequently completed online surveys every 6 months. Changes from baseline to 5-year follow-up in morphine milligram equivalents (MME), excluding those taking buprenorphine, were evaluated by group-based trajectory modeling. Independent associations with opioid dose changes were determined using multiple logistic regression.

Results: At 5-years of follow-up, 410 (364 excluding any taking buprenorphine) participants remained for this analysis. Most participants are female (57.1%) and white (98.3%), with an average age of 64.7 (±10.6) and 88.8% had a history of dopamine agonist augmentation. The median daily MME at 5-years was 37.5 (equivalent to methadone 8.0 mg or oxycodone 25.0 mg), an increase of 7.5 MME from baseline. Opioid doses increased from baseline to 5-years in 49.5% of participants and decreased in 20.0% of participants. Group-based trajectory analysis identified four distinct groups: decrease (3.4% of participants; average MME change=-15.7±12.4), no/little change (66.1% of participants; average MME change=1.5±8.0), small increase (23.9% of participants; average MME change=22.0±11.6), and large increase (3.4% of participants; average MME change=49.2±18.7). RLS severity was stable from baseline (13.3±9.6) to 5-years (13.1±9.0) according to the IRLS severity scale.

Conclusions: Opioid doses in augmented RLS remain largely stable over five years of follow-up. Low-dose opioids provide an effective long-term option for augmented RLS.

Study objectives: PROK2 is a peptide expressed in the adult brain mediating neuroprotective functions. Previous studies reported an upregulation of prokineticin system in PD, but evidence in prodromal α-synucleinopathies was lacking. We investigated the expression of prokineticin-2 (PROK2) and its receptors (PKR1 and PKR2), along with oligomeric α-synuclein (oligo α-syn) as a marker of α-synuclein pathology, in olfactory neurons (ONs) from individuals with idiopathic REM sleep behavior disorder (iRBD).

Methods: ONs, obtained by nasal brush from 28 iRBD subjects (age:71.2 ± 7.4 years; males:89.3%; duration:4.9 ± 2.5 years) and 28 healthy controls (HCs) (age:67.2 ± 11.5 years; males:64.2%), were analyzed using real-time polymerase-chain-reaction (RT-PCR), immunofluorescence (IF), and western blot (WB). In a subgroup of subjects, results were validated in serum.

Results: In the iRBD group, PROK2 protein expression was reduced in both ONs (IF: F(1,26) = 15.289, p<.001; WB: F(1,12) = 9.073, p=.011) and serum compared with HCs (WB: F(1,12) = 4.557, p=.050). iRBD subjects showed lower mRNA expression of prokineticin receptors compared with HCs (RT-PCR for PKR1: F(1,26) = 16.131, p<.001; RT-PCR for PKR2: F(1,39) = 4.946, p=.032). Oligo α-syn accumulation in ONs was higher in iRBD than HCs, yet the difference only tended to statistical significance (IF: F(1,18) = 3.169, p=.092).

Conclusions: In contrast with findings in PD, we found a downregulation of prokineticin system in iRBD. The causes of prokineticin system downregulation in this prodromal stage may be multiple. The absence of clear oligo α-syn accumulation, known trigger of PROK2, may play a role. On the other hand, a lack of activation of this system might act as predisposing factor for the development of iRBD and, subsequently, full-blown neurodegeneration.

Study objectives: Fetal sleep is a vital yet underexplored aspect of prenatal neurodevelopment. Its cyclic organization reflects the maturation of central neural circuits, and disturbances in these patterns may offer some of the earliest detectable signs of neurological compromise. This is the first review to integrate more than seven decades of research into a unified, cross-species synthesis of fetal sleep. We examine: (i) Physiology and Ontogeny-comparing human fetuses with animal models; and (ii) Methodological Evolution-transitioning from invasive neurophysiology to non-invasive monitoring and deep learning frameworks.

Methods: A structured narrative synthesis was guided by a systematic literature search across four databases (PubMed, Scopus, IEEE Xplore, and Google Scholar). From 2,925 identified records, 171 studies involving fetal sleep-related physiology, sleep-state classification, or signal-based monitoring were included in this review.

Results: Across the 171 studies, fetal sleep states become clearly observable as the brain matures. In fetal sheep and baboons, organized cycling between active and quiet sleep emerges at approximately 80%-90% gestation. In humans, this differentiation occurs later, around 95% gestation, with full maturation reached near term. Despite extensive animal research, no unified, clinically validated framework exists for defining fetal sleep states, limiting translation into routine obstetric practice.

Conclusions: By integrating evidence across species, methodologies, and clinical contexts, this review provides the scientific foundation for developing objective, multimodal, and non-invasive fetal sleep monitoring technologies-tools that may ultimately support earlier detection of neurological compromise and guide timely prenatal intervention.

Study objectives: Weight gain after continuous positive airway pressure (CPAP) initiation in obstructive sleep apnea (OSA) is common, but its mechanism and relevance remain unclear. This open-label randomized trial evaluated CPAP effects on energy expenditure, intake, body composition, physical activity, and appetite-regulatory hormones.

Methods: Patients with OSA were randomized (1:1) to 12-week CPAP or inactive control. The primary outcome was resting energy expenditure (REE). Secondary outcomes included dietary intake, eating behavior, fat mass (FM), fat-free mass (FFM), and activity count. Tertiary outcomes included appetite-regulatory hormones. CPAP effects were assessed as baseline-adjusted between-group differences using intention-to-treat (ITT) analysis; Per-protocol analysis (completers) served as sensitivity analysis.

Results: Of 52 randomized participants, 45 completed the study. In ITT analysis, CPAP had no effect on REE (8.6 kcal/day [95% CI = -51.5 to 68.7]; p = .774) or caloric intake (144.4 kcal/day [95% CI = -123.1 to 411.9]; p = .283). Although insignificant in morning, CPAP significantly increased evening body weight (p = .017) and body mass index in morning and evening (p = .040 and .030). CPAP also increased FFM, raised acylated ghrelin and insulin-like growth factor 1, and reduced cortisol and cognitive restraint. No changes were observed in macronutrient intake, FM, activity, insulin resistance, leptin, or neuropeptide Y. Per-protocol findings were similar.

Conclusions: CPAP-induced weight gain, probably primarily from FFM, occurred without measurable changes in REE, activity, or significant increases in caloric intake. Accompanying hormonal and behavioral changes suggest a subtle positive energy balance. This gain may not reflect adverse metabolic effects and supports evaluating CPAP's metabolic impact through body composition, not weight alone.

Clinical trial registration: Registry: ClinicalTrials.gov; Name: Validation of Sleep Healthcare System; URL: https://clinicaltrials.gov/study/NCT04252482; Identifier: NCT04252482. Statement of Significance The physiological basis and clinical relevance of weight gain following CPAP therapy remain insufficiently defined. This study found that CPAP-induced weight gain was probably primarily due to increases in FFM, without measurable changes in REE, physical activity, or significant increases in reported caloric intake. Given the potential underestimation in dietary reporting, the observed gain-together with hormonal and behavioral changes-suggests a subtle positive energy balance. These findings indicate that post-CPAP weight gain may not reflect adverse metabolic effects and highlight the value of assessing body composition, rather than weight alone, in clinical follow-up.

Study objectives: Teams that work together across location, time, and organization are known as "distributed teams." These teams often work in demanding environments that are stressful and fatiguing due to extended periods of wakefulness, intense work, and working during night hours. The aim of this study was to examine the impact of prolonged wakefulness on team performance and cohesion.

Methods: N = 22 healthy young individuals (M = 22.60, SD = 4.41 years, 11f) participated in a 5-day laboratory study with 62 h of wakefulness. Throughout the sleep deprivation period, four-person distributed teams completed the Capturing Objective Human Econometric Social Interactions in Organizations and Networks (COHESION) team task while physically isolated from one another. This task assessed cooperation, productivity, individual performance, team performance, and team dynamics. Fatigue and self-reported measures of team cohesion were also administered.

Results: There were statistically significant changes in team member cooperation and team dynamics across the sleep deprivation period (p < .05, ƞp2 > 0.14), with steep declines in cooperation and team dynamics after 21 h of prior wake. There were statistically significant productivity, team performance, and team cohesion over the sleep deprivation period (p < .05, ƞp2 > 0.14), with deficits after 36 h of wake.

Conclusions: Team members acted more selfishly than cooperatively after 21 h of total sleep deprivation, resulting in poorer team dynamics. Distributed team members were no longer able to engage effectively with their teams after 36 h of total sleep deprivation due to fatigue, which was associated with poorer distributed team performance and cohesion. These findings show impairments for distributed teams who operate with severe fatigue in safety-critical working environments.