Sleep最新文献

{"title":"Rates of sufficient sleep among university students in the United States from 2000 to 2023.","authors":"Michael K Scullin, Blake K Barley, Allison E Nickel, Jason R Carter","doi":"10.1093/sleep/zsag128","DOIUrl":"10.1093/sleep/zsag128","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147857292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of major adverse cardiovascular events with the apnea-hypopnea index, desaturation severity parameters, and cardiac troponins in participants of the Akershus Sleep APnea cohort.","authors":"Xin Feng, Fjola Sigurdardottir, Erna Sif Arnardottir, Toril Dammen, Gunnar Einvik, Henri Korkalainen, Ole Klungsøyr, Timo Leppänen, Inger Hilde Nordhus, Sami Nikkonen, Juha Töyräs, Thea Thorshov, Tonje Caroline Øverby, Torbjørn Omland, Harald Hrubos-Strøm","doi":"10.1093/sleep/zsag013","DOIUrl":"10.1093/sleep/zsag013","url":null,"abstract":"<p><strong>Study objectives: </strong>To examine the prognostic value of the apnea-hypopnea index (AHI), desaturation severity parameters, and cardiac troponins alone and combined for major cardiovascular events (MACEs).</p><p><strong>Methods: </strong>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 Automatic Blood Oxygen Saturation Analysis software. Cox regression models estimated hazard ratios (HRs) for MACE. Predictive properties of combining troponins and obstructive sleep apnea 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.</p><p><strong>Results: </strong>High AHI, DesDur, DesSev, cTnI, and cTnT were 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.</p><p><strong>Conclusion: </strong>In this 15-year follow-up, cTnI was independently associated with risk of MACE, 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 obstructive sleep apnea populations, the measurement of cTnI may be considered for cardiovascular risk stratification.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146030374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perspective: sleep regularity-where do we go from here?","authors":"Andrew J K Phillips, Dorothee Steven","doi":"10.1093/sleep/zsag114","DOIUrl":"10.1093/sleep/zsag114","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147781665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and content validity of the Functional Impacts of Narcolepsy Instrument: a novel patient-reported outcome measure for narcolepsy type 1 and type 2.","authors":"Yulia Savva, Heather Romero, Stephen Crawford, Amy Howerter, Peter McPherson, Helen Doll, Tara Symonds, Todd Swick, Yves Dauvilliers","doi":"10.1093/sleep/zsag127","DOIUrl":"10.1093/sleep/zsag127","url":null,"abstract":"<p><strong>Study objectives: </strong>Most patient-reported outcome measures for narcolepsy focus on excessive daytime sleepiness or do not focus on specific disease impacts (e.g. cataplexy, cognitive difficulties, fatigue, daily function). The Functional Impacts of Narcolepsy Instrument (FINI) was developed to measure key functional impacts in people with narcolepsy type 1 and 2 (NT1/NT2).</p><p><strong>Methods: </strong>The instrument was developed separately in NT1/NT2 populations with input from patients, clinical experts experienced in narcolepsy management, and clinical outcome scientists. Development included: patient experience interview studies informing item development; item development including de novo items, and modified/original items from the Patient-Reported Outcomes Measurement Information System (PROMIS) library; two waves of patient-debriefing interviews testing initial/modified item drafts; determination of scale structure using exploratory factor and Rasch analyses, and confirmatory factor analyses for NT2; consensus meetings between clinical sleep experts/clinical outcome experts to finalize the FINI draft items and structure with a 7-day recall period.</p><p><strong>Results: </strong>The final FINI for NT1 had 28 items within six independent domains: Tiredness, Cognitive Functioning, Cataplexy, Social Activities, Everyday Activities, and Everyday Responsibilities. The final NT2 version (FINI-NT2) included the same items excluding the Cataplexy domain (23 items). Final FINI and FINI-NT2 items demonstrated good content validity and covered the main impacts of NT1 and NT2, respectively, as confirmed by patient interviews, exploratory/confirmatory factor analyses, and Rasch analysis.</p><p><strong>Conclusions: </strong>The novel FINI assesses key functional impacts of narcolepsy in people with NT1/NT2 for use across clinical settings, and adds to the number of existing clinical outcome assessments for central disorders of hypersomnolence. Statement of Significance People with narcolepsy type 1 (NT1) or narcolepsy type 2 (NT2) often experience impacts on their daily life, such as cognitive difficulties, fatigue, and impaired work/school responsibilities, leading to decreased quality of life. Despite these recognized challenges, there remains a need for an additional tool that measures functional outcomes and complements existing narcolepsy symptom, severity, and impacts assessments. The Functional Impacts of Narcolepsy Instrument (FINI) was developed to evaluate functional impacts of narcolepsy that are important and meaningful to people living with NT1 (FINI) and NT2 (FINI-NT2). The instrument offers a patient-centered outcome measure for assessing narcolepsy impacts and treatment benefits related to changes in functional outcomes that can be used in both the clinical trial setting and clinical practice.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147933807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Context-dependent arousal via wake-promoting pontine neurons in the Drosophila melanogaster fan-shaped body.","authors":"Abigail Aleman, Jeffrey M Donlea","doi":"10.1093/sleep/zsag153","DOIUrl":"10.1093/sleep/zsag153","url":null,"abstract":"<p><p>Neurons projecting into the Drosophila dorsal fan-shaped body (dFB) respond electrically during rising sleep pressure to implement sleep. While the molecular and circuit mechanisms that track sleep pressure have been an area of intense focus, less attention has been placed on the downstream neurons targeted by dFB cells to change behavioral state. To identify relevant circuitry, we first used an anterograde transsynaptic labeling tool, trans-Tango, to identify postsynaptic partners of dFB. We found that neurons downstream of dFB resemble hΔF cells and through thermogenetic stimulation identify their activity to be wake promoting. We validated these results using independent genetic lines, including highly specific split-Gal4 drivers. Next, we found that hΔF neurons express the glutamate transporter VGLUT and the acetylcholine biosynthetic enzyme, Choline acetyltransferase (ChAT). Consistent with their wake promoting role, RNAi-mediated knock down of VGlut and ChAT in hΔF increases baseline sleep by sustaining sleep episodes. Furthermore, RNAi for VGlut but not ChAT in h∆F cells reduced night-time sleep loss when flies were exposed to night-time light, indicating that these cells promote arousal in response to specific sensory cues. In contrast, VGlut and ChAT knock-down in h∆F neurons resulted in enhanced sleep loss while flies were deprived of food overnight. These results suggest that hΔF cells may selectively release glutamate and acetylcholine to fine tune arousal responses to changing environmental inputs.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148164289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Subjective sleep traits and cognition across mid- to late-adulthood: a cross-sectional study of gene-environment interplay.","authors":"Tina T Vo-Eckerle, Nathan A Gillespie, Kaare Christensen, Deborah Finkel, William S Kremen, Marianne Nygaard, Perminder S Sachdev, Anbupalam Thalamuthu, Chandra A Reynolds","doi":"10.1093/sleep/zsag119","DOIUrl":"10.1093/sleep/zsag119","url":null,"abstract":"<p><p>Genetic susceptibility to Alzheimer's disease (AD) may influence the extent to which environmental factors shape cognition, with individuals at higher genetic risk potentially exhibiting greater sensitivity to environmental exposures. Sleep, an important factor for both cognitive function and AD risk, may further moderate genetic influences (A), including both measured (AP) and latent (AL) components, as well as shared (C) and non-shared environmental (E) contributions to cognition. This study leveraged data from the Interplay of Genes and Environment across Multiple Studies consortium (N = 3894; 1947 complete twin pairs, 842 monozygotic (MZ) pairs and 1105 dizygotic (DZ); Average age = 62.36 years, 38.75% female). Across six cognitive abilities, we examined whether an AD polygenic score (AD-PGS) moderated environmental influences on cognitive performance. We also examined whether sleep moderated genetic and environmental contributions on cognitive performance. Although the AD-PGS accounted for a negligible proportion of genetic variance as a main effect (B's = -0.004 to 0.02), we observed environment-by-PGS interactions. Increasing genetic risk for AD was associated with lower contributions from environmental experiences unique to each individual, on episodic memory, working memory, and verbal ability (B's = -0.03 to -0.05). These interaction effects, albeit small, were primarily observed with the AD-PGS including the APOE region. Hence, the role of person-specific environments on cognitive functioning was boosted for those at lower genetic risk for AD but reduced at greater genetic risk for AD. Although sleep moderation was minimal, results suggest that poorer sleep influences genetic influences on cognitive functioning. Statement of Significance This study provides novel insights into how genetic risk for Alzheimer's disease (AD-PGS), and sleep (duration and disturbances) moderate genetic and environmental contributions to cognitive performance. Although the AD-PGS accounts for minimal genetic variance, significant but small environment-by-PGS interactions emerged. Individuals with higher AD-PGS exhibited heightened responsiveness to nonshared environmental influences on episodic memory, working memory, and verbal ability, primarily driven by the APOE ε4 region. Poorer sleep may be associated with subtle variations in genetic contributions to cognition, though moderation effects were minimal. This work offers insight into the genetic mechanisms underlying sleep, AD risk, and cognition, underscoring the need to consider both genetic susceptibility and environmental influences when examining factors that contribute to individual differences in cognition.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147780900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to Li and Ni \"Positive Airway Pressure Therapy for Cognitive Enhancement in Parkinson's Disease: From Statistical Signals to Clinical Practice\".","authors":"Annie C Lajoie, R John Kimoff, Andrea Benedetti, Anne-Louise Lafontaine, Ann R Robinson, Marie Létourneau, Joelle Crane, Amanda Scanga, Francine Noel, Marta Kaminska","doi":"10.1093/sleep/zsag148","DOIUrl":"10.1093/sleep/zsag148","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148035291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facility-measured sleep electroencephalographic microstructures in long COVID.","authors":"Haoqi Sun, Rammy Dang, Peng Li, Wenzhong Xiao, Jennifer Scott-Sutherland, Kenneth C Sassower, M Brandon Westover, Donna Felsenstein, Robert J Thomas, Monika Haack, Janet M Mullington","doi":"10.1093/sleep/zsag090","DOIUrl":"10.1093/sleep/zsag090","url":null,"abstract":"<p><strong>Study objectives: </strong>Sleep electroencephalographic (EEG) microstructures are related to brain functions, providing a window into the unrefreshing, non-restorative sleep and daytime fatigue symptoms in long COVID (LC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We aim to characterize sleep EEG microstructural differences in individuals with LC and age-sex-matched healthy controls (HC), and also ME/CFS, using overnight in-lab facility-measured polysomnography (PSG).</p><p><strong>Methods: </strong>28 LC and 28 HC participants came from a single-center research study. 19 ME/CFS participants came from a single clinical center. Sleep EEG was processed to extract spectral band powers, spindles, slow oscillations (SO, 0.5-1 Hz), spindle-SO coupling, brain age index (BAI), alpha-delta patterns, and infraslow oscillation relative band power (ISO, 0.005-0.03 Hz).</p><p><strong>Results: </strong>Compared to HC, LC had higher SO power during wake before sleep and REM sleep. In N2 and N3, LC showed a faster within-spindle frequency drop (chirp) and shorter SO peak duration in the frontal region. LC showed widespread, early spindle-SO coupling phase at SO trough for both fast and slow spindles, with early fast spindle-SO coupling associated with worse sleep quality. ME/CFS shared some differences with LC but had higher SO-uncoupled slow spindle densities in frontal and central regions, more alpha-delta patterns in the first half of the night, and widespread elevated ISO power in the slow sigma band (11-13 Hz).</p><p><strong>Conclusions: </strong>These findings suggest that LC and ME/CFS are associated with plausibly pathological sleep EEG microstructure changes, illuminating the pathobiology of post-infectious processes on brain activity.</p><p><strong>Clinical trial information: </strong>Trial 1: Sleep and Inflammatory Resolution Pathway, https://clinicaltrials.gov/study/NCT03377543, NCT03377543.Trial 2: Pain in Long COVID-19: the Role of Sleep, https://clinicaltrials.gov/study/NCT05606211, NCT05606211. Statement of Significance People with long COVID (LC) frequently experience sleep disturbances, non-restorative sleep, and fatigue. Sleep electroencephalographic (EEG) microstructures may offer objective markers of subjective sleep quality in LC. Here, we present an in-lab facility-measured sleep study. LC participants exhibited abnormally early spindle-slow oscillation (SO) coupling phase at the trough of the SO, and a faster drop in within-spindle frequency. The abnormally early spindle-SO coupling phase in LC was correlated with worse subjective sleep quality. Similar differences in EEG microstructural patterns were found in people with myalgic encephalomyelitis/chronic fatigue syndrome as well. The results demonstrate candidate electrophysiological abnormalities associated with the fatigue and non-restorative sleep experienced in LC.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147781707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The paradox of right dorsolateral prefrontal cortex targeting: why did low-frequency repetitive transcranial magnetic stimulation modulate default mode network but not frontoparietal network BOLD-CSF coupling in chronic insomnia?","authors":"Luna Liu, Fang Zhang, Peng Zhou","doi":"10.1093/sleep/zsag056","DOIUrl":"10.1093/sleep/zsag056","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147318183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pediatric SleepNet: a deep learning network for reliable pediatric sleep staging across developmental stages.","authors":"Ayush Tripathi, Arnav Gupta, Wolfgang Ganglberger, Samuel Waters, Haoqi Sun, Samaneh Nasiri, Ayan Mitra, Katie L Stone, Emmanuel Mignot, Dennis Hwang, Matthew A Reyna, Lynn Marie Trotti, Gari D Clifford, Kiran Maski, Umakanth Katwa, Robert J Thomas, M Brandon Westover","doi":"10.1093/sleep/zsag064","DOIUrl":"10.1093/sleep/zsag064","url":null,"abstract":"<p><strong>Study objectives: </strong>Manual sleep staging in pediatric populations is challenging due to developmental variability and limited scoring consistency, especially in infants and toddlers. We developed a multimodal deep learning model for pediatric sleep staging and evaluated its performance across a broad age range and diverse clinical subgroups.</p><p><strong>Methods: </strong>We trained a U-Net-inspired encoder-decoder model (pediatric SleepNet) using 9-channel input signals: electroencephalography (EEG), electrooculography (EOG), and chin electromyography (EMG) using 35-epoch segments from clinical pediatric polysomnograms (PSGs). Models were trained separately on three age groups (<6 months, 6-12 months, >1 year) using 9150 PSGs, with 2455 PSGs reserved for validation. Evaluation was conducted on 3804 held-out test recordings. Performance was compared with U-Sleep and the Complete Artificial Intelligence Sleep Report (CAISR), and stratified analyses were performed across ages, sexes, and seven ICD-10-based disease categories. External validation was conducted on two independent datasets, CHAT and PATS.</p><p><strong>Results: </strong>pediatric SleepNet achieved robust performance across all age groups, with mean Cohen's Kappa increasing from 0.49 (0-6 months) to 0.72 (>12 years). It significantly outperformed U-Sleep and CAISR across early developmental stages. Three-class staging yielded mean Cohen's Kappa increasing from 0.66 (0-6 months) to 0.79 (>12 years). Sex-based differences were negligible. However, significant reductions in performance were observed in children with epilepsy, Down syndrome, hydrocephalus, and other neurodevelopmental conditions. External validation yielded Kappa values >0.69 comparable to the internal test set.</p><p><strong>Conclusions: </strong>pediatric SleepNet demonstrates reliable sleep staging across pediatric development. Its robust performance across age, disease, and external datasets supports its potential for clinical and research use in pediatric sleep medicine.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147391089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}