Sleep advances : a journal of the Sleep Research Society最新文献

Idiopathic hypersomnia (IH) is a rare neurological sleep disorder, characterized by excessive daytime sleepiness despite normal sleep duration, that can significantly impact patient's lives. The burden of IH goes beyond excessive daytime sleepiness, pervading all aspects of everyday life. Characteristic and burdensome symptoms of IH include sleep inertia/drunkenness, long sleep duration, and daytime cognitive dysfunction. This systematic review assessed current knowledge regarding IH diagnostic challenges and burden of illness. Literature searches for original epidemiological, clinical, humanistic, or economic research relevant to IH published between 2012 and 2022 in MEDLINE, Embase, Cochrane, gray literature (diagnostic criteria and treatment guidelines), conferences (2019-2022), and clinical trial databases yielded 97 articles. Findings indicate that IH remains a poorly defined diagnosis of exclusion that is difficult to distinguish from narcolepsy type 2 because of symptom overlap and inadequacies of objective testing. Consequently, individuals with IH endure diagnostic delays of up to 9 years. The economic burden of IH has not been characterized to any appreciable extent. Pharmacological treatment options can improve symptoms and functional status, but rarely restores normal levels of functioning. These findings highlight the need to reclassify central disorders of hypersomnolence. Further collaboration is now required between research groups to identify and validate objective markers to help redefine diagnostic criteria for IH. This would move IH into a position that could benefit from future targeted therapeutic interventions. The study was funded by Takeda Development Center Americas, Inc.

Study objectives: The coronavirus disease 2019 (COVID-19) pandemic impact on infant sleep (IS) is understudied. The purpose of this study was to examine the relationships between family impact and distress from COVID-19 pandemic stressors, parental insomnia symptoms, infant temperamental negative affectivity, and parent-reported IS.

Methods: Parents from the Phoenix metropolitan area with a full-term healthy infant (<1 year) were recruited from February 27, 2021, to August 7, 2021. A sample of 70 parents (baby age 5.5 ± 3.5 months; parental age: 31.7 ± 5.0 years) completed the COVID-19 Exposure and Family Impact Survey (CEFIS) Impact and Distress scales, the Insomnia Severity Index (ISI), the Infant Behavioral Questionnaire-Revised Negative Affectivity subscale (IBQ-R-NA), and the Brief Infant Sleep Questionnaire-Revised (BISQ-R). Based on the transactional model of IS, path analyses were conducted to identify the direct effect of CEFIS scores and the indirect effects of parental ISI and infant IBQ-R-NA scores on BISQ-R scores.

Results: The parent sample was predominantly female (94.3%), white (72.9%), and married or in a domestic partnership (98.6%). Although COVID-19 pandemic impact and distress were not directly related to parent-reported IS, pandemic distress was negatively related to parent-reported IS indirectly through infant negative affectivity, including BISQ-R total score (β = -0.14, 95% CI [-0.32, -0.01]) and IS subscale score (β = -0.12, 95% CI [-0.27, -0.01]).

Conclusions: Heightened COVID-19 pandemic family distress was related to poorer parent-reported IS through greater parent-reported infant negative affectivity, suggesting the importance of addressing family stress and emotional regulation during crises.

Study objectives: Trauma-related nightmares (TRNs) are a hallmark symptom of PTSD and are highly correlated with PTSD severity and poor sleep quality. Given the salience and arousal associated with TRNs, they might be an effective target for imaginal exposures during Prolonged Exposure (PE) therapy. As a first step in this line of research, the current study compared participants' emotional reactivity during recollection of TRNs to their recollection of the index traumatic event.

Methods: Seventeen trauma-exposed participants with clinical or sub-clinical PTSD who reported frequent TRNs engaged in script-driven imagery using scripts depicting their index trauma and their most trauma-like TRN. Heart rate (HRR), skin conductance (SCR), corrugator EMG (EMGR) responses, and emotional ratings were recorded.

Results: HRR, SCR, and EMGR did not differ significantly between trauma-related and TRN scripts. Bayesian analyses confirmed support for the null hypothesis, indicating no differences. With the exception of "Sadness," for which TRNs elicited significantly lower ratings than trauma scripts, individual emotion ratings showed no significant differences, suggesting likely parity between the emotionality of trauma-related and TRN recollections.

Conclusions: Together, TRN content elicited psychophysiological reactivity similar to that of the index trauma in this pilot study. Upon replication, studies testing TRNs as potential targets for imaginal exposures during PE may be warranted.

Study objectives: The association of shift work (SW) and disrupted circadian rhythm with markers of large artery atherosclerosis and cerebral small vessel disease is uncertain. We aimed to study the separate association of current and former SW with these markers.

Methods: We included participants from the population-based Hamburg City Health Study. SW was defined by monthly working hours between 06:00 pm and 07:00 am containing night shifts for at least 12 months. Cross-sectional data were obtained from structured questionnaires, laboratory analyses, physical examinations, brain magnetic resonance imaging, and carotid ultrasound. We performed multivariable regression analysis with carotid intima-media thickness (CIMT), and peak-width skeletonized mean diffusivity (PSMD) as dependent variables.

Results: Three hundred and forty-four current, 238 former, and 7162 never-shift workers were included. The median age was 60 years for both current and former shift workers, and total duration of SW was comparable for the two groups. Current shift workers were less frequently female (27.3% vs. 44.5%; p < .001), had more frequent hyperlipidemia (31.5% vs. 22.3%; p = .024), and diabetes (16.2% vs. 3.2%; p < .001). After adjustment for age and sex, reduced quality of sleep (β = 1.61, p = .001) and low education (β = 2.63, p < .001) were associated with current but not former SW. Adjusted for age and sex, the current SW was associated with higher CIMT (β = 0.02, p = .001) and PSMD (β = 9.06e-06, p = .006), whereas former SW was not. Adjusted for risk factors, current SW remained associated with PSMD (β = 9.91e-06, p = .006) but not with CIMT.

Conclusions: Current SW was associated with CIMT and with PSMD, with the latter association remaining after adjustment for risk factors. Former SW showed no associations with CIMT or PSMD. This may indicate that current SW is linked with increased neurovascular risk through disrupted circadian rhythms.

Trial registration information: The trial was submitted at http://www.clinicaltrials.gov, under NCT03934957 on January 4, 2019. The first participant was enrolled in February 2016.

Study objectives: Stroke can result in or exacerbate various sleep disorders. The presence of behaviors such as daytime sleepiness poststroke can indicate underlying sleep disorders which can significantly impact functional recovery and thus require prompt detection and monitoring for improved care. Actigraphy, a quantitative measurement technology, has been primarily validated for nighttime sleep in healthy adults; however, its validity for daytime sleep monitoring is currently unknown. Therefore this study aims to identify the best-performing actigraphy sensor and algorithm for detecting daytime sleep in poststroke individuals.

Methods: Participants wore Actiwatch Spectrum and ActiGraph wGT3X-BT on their less-affected wrist, while trained observers recorded daytime sleep occurrences and activity levels (active, sedentary, and asleep) during non-therapy times. Algorithms, Actiwatch (Autoscore AMRI) and ActiGraph (Cole-Kripke, Sadeh), were compared with on-site observations and assessed using F2 scores, emphasizing sensitivity to detect daytime sleep.

Results: Twenty-seven participants from an inpatient stroke rehabilitation unit contributed 173.5 hours of data. The ActiGraph Cole-Kripke algorithm (minute sleep time = 15 minutes, bedtime = 10 minutes, and wake time = 10 minutes) achieved the highest F2 score (0.59). Notably, when participants were in bed, the ActiGraph Cole-Kripke algorithm continued to outperform Sadeh and Actiwatch AMRI, with an F2 score of 0.69.

Conclusions: The study demonstrates both Actiwatch and ActiGraph's ability to detect daytime sleep, particularly during bed rest. ActiGraph (Cole-Kripke) algorithm exhibited a more balanced sleep detection profile and higher F2 scores compared to Actiwatch, offering valuable insights for optimizing daytime sleep monitoring with actigraphy in stroke patients.

Objective: To explore markers that reflect sleep-disordered breathing (SDB) severity and investigate their associations with cardiometabolic risk factors in adolescents and young adults.

Methods: Participants were recruited from our SDB epidemiological cohort. They underwent overnight polysomnography and ambulatory blood pressure (BP) monitoring. Complete blood count, ferritin, high-sensitivity C-reactive protein (hs-CRP), fasting blood glucose, and lipid profile were measured. Multiple linear regression was used to examine the association between red cell indices (RCIs), ferritin, and obstructive apnea-hypopnea index (OAHI). Subgroup analyses on participants with SDB were performed for the association of RCIs and ferritin with lipid profile, hs-CRP, and BP.

Results: There were 88 participants with SDB and 155 healthy controls aged 16-25 years. Hemoglobin (Hb; p < .001), hematocrit (HCT; p < .001), and ferritin (p < .001) were elevated with increasing SDB severity and were independently associated with OAHI (β=1.06, p < .001; β=40.2, p < .001; β=4.89 × 10^-3, p = .024, respectively). In participants with SDB, after adjusting for age, sex, and BMI, significant associations were found between ferritin with low-density lipoprotein (LDL; β=0.936 × 10^-3, p = .008) and triglyceride (TG; β =1.08 × 10^-3, p < .001), as well as between Hb (β=1.40, p = .007), HCT (β=51.5, p = .010) and mean arterial pressure (MAP). Ferritin (β=0.091, p = .002), Hb (β=0.975, p = .005), and HCT (β=38.8, p = .004) were associated with hs-CRP independent of age, sex, BMI, plasma LDL, and MAP. OAHI was not associated with LDL and TG in the multivariable models.

Conclusions: Serum ferritin, but not OAHI, was associated with LDL and TG in participants with SDB, suggesting it is a potential marker of cardiometabolic risk in patients with SDB.

People with narcolepsy type 1 (NT1), narcolepsy type 2 (NT2), and idiopathic hypersomnia (IH) often report cognitive impairment which can be quite burdensome but is rarely evaluated in routine clinical practice. In this systematic review and meta-analysis, we assessed the nature and magnitude of cognitive impairment in NT1, NT2, and IH in studies conducted from January 2000 to October 2022. We classified cognitive tests assessing memory, executive function, and attention by cognitive domain. Between-group differences were analyzed as standardized mean differences (Cohen's d), and Cohen's d for individual tests were integrated according to cognitive domain and clinical disease group. Eighty-seven studies were screened for inclusion; 39 satisfied inclusion criteria, yielding 73 comparisons (k): NT1, k = 60; NT2, k = 8; IH, k = 5. Attention showed large impairment in people with NT1 (d = -0.90) and IH (d = -0.97), and moderate impairment in NT2 (d = -0.60). Executive function was moderately impaired in NT1 (d = -0.30) and NT2 (d = -0.38), and memory showed small impairments in NT1 (d = -0.33). A secondary meta-analysis identified sustained attention as the most impaired domain in NT1, NT2, and IH (d ≈ -0.5 to -1). These meta-analyses confirm that cognitive impairments are present in NT1, NT2, and IH, and provide quantitative confirmation of reports of cognitive difficulties made by patients and clinicians. These findings provide a basis for the future design of studies to determine whether cognitive impairments can improve with pharmacologic and nonpharmacologic treatments for narcolepsy and IH.

Study objectives: Sleep deprivation is highly prevalent and caused by conditions such as night shift work or illnesses like obstructive sleep apnea. Compromised sleep affects cardiovascular-, immune-, and neuronal systems. Recently, we published human serum proteome changes after a simulated night shift. This pilot proteomic study aimed to further explore changes in human blood serum after 6 hours of sleep deprivation at night.

Methods: Human blood serum samples from eight self-declared healthy females were analyzed using Orbitrap Eclipse mass spectrometry (MS-MS) and high-pressure liquid chromatography. We used a within-participant design, in which the samples were taken after 6 hours of sleep at night and after 6 hours of sleep deprivation the following night. Systems biological databases and bioinformatic software were used to analyze the data and comparative analysis were done with other published sleep-related proteomic datasets.

Results: Out of 494 proteins, 66 were found to be differentially expressed proteins (DEPs) after 6 hours of sleep deprivation. Functional enrichment analysis revealed the associations of these DEPs with several biological functions related to the altered regulation of cellular processes such as platelet degranulation and blood coagulation, as well as associations with different curated gene sets.

Conclusions: This study presents serum proteomic changes after 6 hours of sleep deprivation, supports previous findings showing that short sleep deprivation affects several biological processes, and reveals a molecular signature of proteins related to pathological conditions such as altered coagulation and platelet function, impaired lipid and immune function, and cell proliferation. Data are available via ProteomeXchange with identifier PXD045729. This paper is part of the Genetic and other molecular underpinnings of sleep, sleep disorders, and circadian rhythms including translational approaches Collection.

Study objectives: We examined whether sleep (i.e. quality, regularity, and duration) mediated associations between child maltreatment (CM) and depressive symptoms among emerging adults undergoing the major life transition of starting college.

Methods: Students (N = 1400; 44% male; 48% non-Hispanic white, 20% non-Hispanic Asian, 15% Hispanic all races, 7% non-Hispanic black, and 10% non-Hispanic other races) completed daily sleep diaries for 9 weeks, followed by the Childhood Trauma Questionnaire-Short Form, Pittsburgh Sleep Quality Index, and the Center for Epidemiologic Studies Depression Scale (CES-D). DSD data were used to compute participants' Sleep Regularity Index and average 24-hour total sleep time. We used a nonparametric structural equation modeling bootstrap approach and full information maximum likelihood to account for missing data. In model 1, we controlled for sex and race and ethnicity. In model 2, we further adjusted for baseline CES-D scores.

Results: The prevalence of self-reported moderate-to-severe CM was 22%. Small but significant indirect effects of CM on greater depressive symptoms through worse sleep quality (β = 0.06, 95% CI = 0.04, 0.09) and lower sleep regularity (β = 0.02, 95% CI = 0.005, 0.03) were observed in model 1. In model 2, only the indirect effect of sleep quality remained significant (β = 0.03, 95% CI = 0.01, 0.06).

Conclusions: Poorer sleep quality may partially account for associations between CM and depressive symptoms during the first semester of college. Including sleep as a target in student health interventions on college campuses may not only help buffer against poor mental health outcomes for students with CM, but also poor academic and socioeconomic outcomes long-term.

Background: Opioids are effective for acute pain management following surgery among adolescents, yet are associated with significant negative consequences, including respiratory depression and opioid misuse. Sleep deficiency is common following surgery and extant research indicates strong cross-sectional associations between sleep deficiency and increased problematic opioid use.

Objective: This study examined longitudinal associations between postsurgical sleep deficiency and opioid use among adolescents undergoing outpatient surgery. We also examined daily pain and mood as mechanisms linking previous night's sleep deficiency and next day prescription opioid use.

Methods: This prospective, observational study enrolled 106 adolescents (11-19 years) who underwent orthopedic outpatient surgery and collected pre-surgery and longitudinal measurements. Participants were 52% female, African-American (7%), American Indian/Alaska Native (7%), Hispanic (9%), Native Hawaiian or Other Pacific Islander (4%), or white, non-Hispanic (66%). Using ecological momentary assessment methods, participants reported sleep, pain, and mood in real time over the first 14 days following surgery. Postsurgical opioid use was measured using an electronic medication cap monitoring device, eCAP^TM. Associations between variables were measured using multilevel structural equation modeling.

Results: Using multi-level mediation models, pain, but not mood-mediated associations between postsurgical sleep deficiency (sleep quality, total sleep time, sleep onset latency, and wake after sleep onset) and opioid use, at both the within-person and between-person levels. Results highlight that greater previous night's sleep deficiency (both generally and greater than a person's mean level) was associated with higher next day pain (both generally and greater than a person's mean level), which, in turn, was associated with higher opioid use. Furthermore, between-person total effect models provide support for sleep deficiency predicting higher opioid use.

Conclusions: Our findings should be considered preliminary yet underscore the need for a comprehensive and personalized approach to postsurgical pain management and opioid use, potentially implementing interventions targeting sleep quality and quantity to reduce pain and opioid use.