Poor sleep and malnutrition are prevalent issues among older adults, contributing to negative outcomes such as depression, sarcopenia, and reduced quality of life. A bidirectional relationship has been proposed between diet and sleep. This study aimed to examine the association between the Healthy Eating Index (HEI) and both sleep quality and duration in older adults. This cross-sectional analysis was conducted using baseline data from the Neyshabur Elderly Longitudinal Study (NeLSA, 2016-2022), including 2,026 adults aged ≥ 60. Dietary data were collected via a validated food frequency questionnaire, and HEI-2015 scores were calculated. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), with a score > 5 indicating poor sleep quality. Sleep duration was self-reported and categorized as adequate (≥ 7 h) or insufficient (< 7 h). Multivariable logistic regression was used to assess associations between HEI quartiles and sleep outcomes, adjusting for demographics, BMI, smoking, education, and chronic diseases. Participants had a mean age of 69.1 ± 7.6 years; 55.5% were women. Women reported poorer sleep quality and shorter sleep duration than men (P < 0.001). There was no statistically significant association between HEI and sleep quality or duration in the overall population or by gender (P > 0.05). However, a borderline non-significant inverse association was observed between HEI and insufficient sleep duration in older women. (Q4 vs. Q1, OR: 0.709; 95% CI: 0.502-1.003; P = 0.052). Higher HEI scores were not independently associated with sleep quality or duration among older adults. Although higher diet quality showed a non-significant inverse association between better sleep in women, the relationship may be influenced by other health-related factors. Further longitudinal and interventional studies are recommended.
The aim of this study was to describe the sleep patterns of intensive care unit (ICU) patients using portable polysomnography (PSG) and the Richards-Campbell Sleep Questionnaire (RCSQ), evaluate the correlation between these objective and subjective measures, and explore factors influencing sleep patterns in the ICU. This exploratory observational study was conducted as a substudy within the prospective SYNC (Sleep and circadian rhYthm in iNtensive Care unit) cohort study in a 42-bed surgical ICU of a university hospital. Patients with an anticipated ICU stay exceeding 12 h and requiring at least one overnight sleep were included. PSG was recorded during the first 3 ICU nights, and the RCSQ was administered on the following mornings. We collected and analysed 110 valid PSG recordings from 56 patients, along with 145 valid RCSQ responses from 69 patients. Total sleep time (TST) ranged from 3.98 to 4.52 h per night. Patients had frequent nocturnal awakenings, ranging from an average of 12.84-15.48 times per night. Non-rapid eye movement stage 3 sleep was significantly reduced (1.50%-6.20%). Rapid eye movement (REM) sleep was nearly absent (0-0.9%). The TST and wake after sleep onset showed moderate correlations with RCSQ score (ρ = 0.599, p < 0.01, ρ = -0.586, p < 0.01). In time-adjusted univariable generalised estimating equation analyses, a longer TST was associated with younger age, higher Acute Physiology and Chronic Health Evaluation II scores, mechanical ventilation, receipt of sedatives/analgesics, physical restraints, and more frequent night-time nursing interruptions (all p < 0.05). REM sleep occurrence was more likely in younger and female patients and those with fewer comorbidities and less likely in patients with higher Acute Physiology and Chronic Health Evaluation II scores, mechanical ventilation, sedatives/analgesics use, physical restraints, and more frequent night-time nursing interruptions (all p < 0.05). ICU patients had poor sleep quality during the initial ICU days, with insufficient TST, frequent awakenings, markedly reduced nonrapid eye movement stage 3 and near-absent REM sleep. Sleep disturbance was associated with both patient illness and medical treatments. Nurses should pay attention to patients' sleep time and quality and target modifiable factors, such as minimising nonurgent nighttime care during ICU stay. The study protocol was registered on ClinicalTrials.gov (NCT06346613).
The Stroop test is a well‑validated measure of selective attention and inhibitory control. Although increased electronic device use has been consistently associated with shorter sleep duration and delayed bedtime, whether everyday variability in screen time and sleep relates to Stroop performance in medical trainees remains uncertain, and existing findings on executive function are mixed. This study aimed to examine associations between average daily screen time, self‑reported sleep duration (past week and past month), and Stroop performance measured using the EncephalApp (congruent reaction time, incongruent reaction time, and Stroop interference) in first-year osteopathic medical students. In this cross‑sectional study conducted between March and July 2025, 69 first‑year osteopathic medical students were recruited, of whom 49 (10 male, 39 female) provided complete datasets. Participants completed the EncephalApp Stroop test on their smartphone and an anonymous survey reporting demographic characteristics, average daily screen time over the past week, and sleep duration over the past week and past month. Simple linear regression analyses were used to examine associations between Stroop interference and screen time, Stroop interference and sleep duration, and between screen time and sleep duration. Participants (n = 49; 10 male, 39 female) had a mean age of 25.61 ± 3.58 years. The mean congruent reaction time (OffTime) was 54.06 ± 10.06 seconds, the incongruent reaction time (OnTime) was 60.94 ± 13.59 seconds, and the mean Stroop interference score was 6.87 ± 7.38 seconds. The average daily screen time over the past week was 6.10 ± 3.12 hours, while the average sleep duration was 6.93 ± 1.26 hours over the past week and 7.04 ± 1.16 hours over the past month. Stroop interference was not significantly associated with screen time (R² = 0.0023; p = 0.746) or sleep duration (past week: R² = 0.0287; p = 0.250; past month: R² = 0.0303; p = 0.237). However, screen time was inversely associated with sleep duration over the past week (R² = 0.14; β = -0.152 hours of sleep per additional hour of screen time; p = 0.0088). Among first-year osteopathic medical students, typical variation in screen time and sleep duration was not associated with Stroop‑indexed selective attention. Higher screen time was, however, moderately associated with shorter sleep duration. These findings are consistent with prior evidence linking electronic media use to reduced sleep and suggest that modest between‑person differences in sleep and screen exposure may not translate into measurable differences in Stroop performance in this population.
Patients often experience sleep disruption in hospital, which may prolong recovery and healing. Previous studies focusing on behavior change have ignored specific context implementation factors, resulting in limited improvements in patient sleep. The aim of this study was to improve patient sleep through the implementation of a standardized patient self-report sleep assessment scale, together with a comprehensive evidence-based nocturnal sleep guideline for patients. This study was conducted in two acute care wards in a 500-bed public tertiary referral hospital in Sydney, Australia. The study used the seven-phase JBI Evidence Implementation Framework, which is grounded in an audit and feedback process. Data were gathered through assessment of patients' self-reported sleep and semi-structured interviews with nurses and doctors. The resulting data and the Behaviour Change Wheel (BCW) informed the context-specific implementation strategy. A follow-up audit was then used to measure the effectiveness of the implementation strategy. Patients' self-reported quality of sleep remained unchanged; however, their perception of sound levels was lower post-implementation (median 49.0 [20.5] versus 23.0 [16.2-54.0]). Use of the sleep assessment scale was low. The main barrier was that nurses perceived documentation as a burden. Doctors reported that they were unaware of the sleep assessment scale and guideline post-implementation. Despite there being little uptake of the sleep assessment scale, there was evidence of some changes in practice relevant to sound reduction, which is key to improving sleep quality in hospitals. Documentation burden was a barrier for the uptake of the sleep assessment scale. http://links.lww.com/IJEBH/A581.
Primary headache disorders, particularly migraine, are closely linked to sleep disturbances. However, the relationship between headache phenotypes, sleep quality, and chronotype in large populations remains to be fully elucidated. This study aimed to investigate sleep quality and chronotype across different primary headache types compared to headache-free individuals. This nationwide, cross-sectional study included 5,311 Polish adults recruited via an online research panel. Headaches were classified using the HARDSHIP questionnaire according to ICHD-3 criteria. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and chronotype using the Morningness-Eveningness Questionnaire (MEQ). Sleep-related variables were then compared between specific headache types and individuals without headache. Participants with migraine (n = 1,523) reported the poorest sleep quality (median PSQI: 7 vs. 5 in controls) and the highest prevalence of poor sleep (64.1% vs. 38.7% in controls; p < 0.001). After adjustment, migraine (β = 2.09), unclassified headache (β = 1.57), and tension-type headache (TTH; β = 0.59) remained significantly associated with higher PSQI scores. Regarding chronotype, the migraine group showed a significant shift toward eveningness (adjusted β=-1.38; p < 0.001) and a lower representation of morning types (24.9% vs. 39.1% in controls). In the migraine subgroup, poorer sleep quality was moderately correlated with lower quality of life (r=-0.45) and higher perceived stress (r = 0.34), whereas MEQ scores showed only weak correlations with clinical outcomes. Poor sleep quality and an evening chronotype are prominent features of primary headache disorders, especially migraine. Future prospective studies are needed to determine the causality of these associations. Meanwhile, sleep quality assessment and interventions aiming to improve sleep patterns should be considered in migraine patients.
Since its publication in 1989, the Pittsburgh sleep quality index (PSQI) has become one of the most widely used self-report instruments in sleep medicine. Despite its enduring popularity, its extensive adoption has been accompanied by conceptual and methodological concerns regarding its psychometric foundations and the construct it purports to measure. This review offers a critical appraisal of the PSQI nearly four decades after its introduction and outlines directions for its contemporary use. Five interrelated issues are examined: (i) the absence of a clearly specified construct model of "sleep quality"; (ii) the frequent use of the PSQI as a proxy for insomnia or sleep disturbance; (iii) the interpretive fragility of the conventional global score cutoff (>5); (iv) heterogeneity in component scoring logic and instability of factorial structure; and (v) the redundancy and recall vulnerability of retrospective sleep continuity estimates. Drawing on the shift from "sleep quality" toward multidimensional sleep health, we propose reframing PSQI outputs within a theoretically grounded sleep health perspective. Accordingly, alternative strategies for scoring, reporting, and interpretation are discussed to preserve the value of this legacy instrument while improving its conceptual alignment with contemporary models of sleep assessment.
Sleep disturbances are common after-effects of cancer. While the effectiveness of interventions in managing sleep disturbances in cancer have been evaluated, the effectiveness of interventions on reducing clinically relevant sleep disturbances remains unknown. This systematic review and meta-analysis aimed to appraise the effectiveness of up-to-date interventions managing clinical sleep disturbances in cancer patients or survivors. Data from randomized controlled trials were analysed following PRISMA guidelines. Five English databases were searched from January 2012 to June 2025. Outcomes were measured using Hedge's g with random-effects models. The methodological quality of the trials was assessed by Cochrane Risk of Bias Tool 2.0 and the certainty of evidence was determined using GRADE. 42 trials with 3,844 participants were identified, with sample sizes ranging from 22 to 255. A moderate and large effect was found for cognitive behavioural therapy for insomnia (CBT-I) on improving sleep quality (g = 0.57; 95% CI = 0.20 - 0.93, p < 0.01) and insomnia severity (g = 0.91; 95% CI = 0.49 - 1.34, p < 0.01) respectively. Complementary and alternative medicine (CAM) showed a large effect size for improving sleep quality (g = 1.11; 95% CI = 0.43 - 1.78, p < 0.01) but indicated presence of publication bias. Other interventions, including mindfulness, exercise-based interventions, herbal medicine, relaxation and brief behavioural therapy for insomnia (BBT-I), showed less convincing evidence compared to CBT-I. Only one study scored low in overall risk of bias. The existing evidence base needs to be expanded to adequately evaluate the effectiveness of other interventions for clinical sleep disturbances. CBT-I is currently the most empirically supported treatment for cancer patients and survivors with clinically relevant sleep disturbances.
Sleep duration and physical activity (PA) may play a pivotal role in gastrointestinal functions. It remains unclear how they function in constipation. This study aims to assess the independent and combined associations of sleep duration and PA with the risk of constipation, using data from the National Health and Nutrition Examination Survey (NHANES) 2007-2010. A total of 5590 (unweighted data) participants were included in the analysis. Sleep duration was categorised as insufficient (<7 hours/d), sufficient (7-8h/d), and excessive (>8 hours/d). Physical activity was converted to metabolic equivalent (MET) minutes of moderate to vigorous PA per week, classified as inactive (<600 MET-minutes/week) and active (≥600 MET-minutes/week). Constipation was defined based on stool consistency using the Bristol Stool Form Scale. Multivariable logistic regression models were used to estimate the odds ratios (ORs) for constipation. In multivariable-adjusted models, sufficient sleep duration and active PA was associated with reduced ORs of constipation. Subgroup analysis found this association was more pronounced in male population older than or equal to 60 (sufficient sleep (OR = 0.14; 95% CI = 0.02-0.75, P = 0.047) and active PA (OR = 0.27; 95% CI = 0.08-0.93, P = 0.050)), but not younger adults and female participants. Furthermore, active PA was always associated with a lower risk of constipation, no matter how long the sleep duration was (insufficient sleep (OR = 0.13; 95% CI = 0.03-0.57, P = 0.030), sufficient sleep (OR = 0.04; 95% CI = 0.01-0.21, P = 0.006), and excessive sleep (OR = 0.02; 95% CI = 0.00-0.42, P = 0.038)). Sufficient sleep as well as active PA were associated with lower risk of constipation, independently or jointly. This finding was more pronounced in male population older than or equal to 60, but not younger adults and female participants.
Dysregulation in circadian rhythms, including sleep abnormalities, is a central feature in bipolar disorder during all illness phases. This exploratory post hoc study investigated the association between variation in sleep and instability in mood based on day-to-day patient-reported smartphone-based data in patients with bipolar disorder. Data from patients with bipolar disorder from two prior studies (A-Bipolar and SMART-Bipolar) were included for exploratory analyses. Patients provided daily smartphone-based evaluations of sleep and mood. A total of 370 patients with bipolar disorder each providing data for six months were included in the analyses. We analysed how various summaries of sleep variation were associated with mood instability, using linear mixed effect regression models. There was a positive association between variation in sleep for both the prior three days (1.22, 95%CI: (1.19; 1.24), p < 0.0001) as well as the prior week (1.40,95% CI: (1.36, 1.44), p < 0.0001)) and mood instability. Interestingly, increasing sleep up to a certain point around eight hours was associated with decreased mood instability. Increasing sleep after this point was associated with increased mood instability. The estimated inflection point for this choice of knots was 8.05 h (95% CI: 7.20,8.90) for the A-bipolar study and 8.24 h (95% CI: 6.24,10.24) for SMART-Bipolar study. Analyses were exploratory and post hoc. Sleep and mood were patient-reported. Findings should be interpreted with caution. Temporal ordering of the associations cannot be concluded. In this exploratory study of patients with bipolar disorder, short-term fluctuations in sleep were significantly associated with increased mood instability, highlighting the dynamic interplay between circadian regulation and affective variability.
To objectively characterize inpatient sleep patterns following orthopaedic trauma and evaluate their association with opioid medication utilization while hospitalized. This was a retrospective analysis of a prospective randomized clinical trial (NCT04154384). An Urban, Level 1 Trauma Center. Adult patients with isolated orthopaedic injuries treated surgically were eligible to participate in the original trial if they could consent, comprehend English, were not pregnant or incarcerated, and had a cell phone. Participants were enrolled within 12 hours of surgery and provided with wrist worn actigraphy devices, which are non-invasive devices that measure activity and rest, for the duration of hospitalization thereafter. Participants who wore the actigraphy device for ≥70% of their hospitalization were included in the analysis; those who did not meet this threshold were excluded. Total sleep time while participants were admitted to the hospital recorded by actigraphy devices. Linear mixed-effects models examined associations between inpatient sleep and inpatient opioid use, measured in morphine milligram equivalents daily. The final sample of N=99 participants was predominantly Black (71.7%) and female (55.6%) with a mean age of 48 (range 18-89). Patients had an average total sleep time of 6 hr 36 min (±4 hr 17 min) per 24 hours. Sleep was fragmented, averaging 9.1 awakenings totaling 26.6 minutes. Median opioid use was 45.1 morphine milligram equivalents daily (MED). Each additional MED during the hospitalization period was associated with shorter inpatient sleep duration, specifically an average of 2.7 minutes less of sleep (p=0.004). This study demonstrated that participants needing surgery for isolated orthopaedic injuries experienced short, fragmented sleep while hospitalized. This study's findings also indicate that higher inpatient opioid utilization is associated with worse sleep quality. Level 2.
Postoperative sleep disturbance (PSD) is a common complication after general anesthesia and is associated with delayed recovery and other adverse postoperative outcomes. Perioperative esketamine may improve postoperative sleep, but current evidence remains inconclusive. This systematic review and meta-analysis assessed the efficacy and safety of perioperative esketamine for preventing PSD in adults undergoing surgery under general anesthesia. PubMed, Embase, the Cochrane Library, and CNKI were searched from inception to 10 March 2026, for randomized controlled trials comparing perioperative esketamine with placebo or non-esketamine controls. The primary outcomes were the incidence of Postoperative sleep disturbance on postoperative day 1, 2, 3, and 7. Secondary outcomes included common perioperative adverse events. Risk ratios (RRs) with 95% confidence intervals were pooled using a random-effects model. Risk of bias, certainty of evidence, and robustness of key findings were assessed using the Cochrane Risk of Bias tool, GRADE, trial sequential analysis, and leave-one-out sensitivity analyses. Twenty-two randomized controlled trials were included. Esketamine significantly reduced PSD incidence on POD1 (RR = 0.58, 95% CI: 0.51-0.66; I2 = 0%), POD2 (RR = 0.40, 95% CI: 0.28-0.58; I2 = 0%), and POD3 (RR = 0.55, 95% CI: 0.45-0.68; I2 = 9%), but not on POD7 (RR = 0.77, 95% CI: 0.55-1.08). Although statistical heterogeneity was low, clinical heterogeneity should be considered because of differences in surgical populations, patient characteristics, esketamine regimens, and sleep assessment methods. Subgroup analyses generally supported the early postoperative benefit, whereas POD3 findings stratified by preoperative sleep status should be interpreted cautiously. No statistically significant differences were observed in the analyzed adverse events, but safety evidence remains limited. Sensitivity analyses and trial sequential analysis supported the robustness of POD1 and POD3 findings. The certainty of evidence for early PSD outcomes was moderate. Perioperative esketamine may reduce early PSD incidence, particularly from POD1 to POD3. However, evidence mainly reflects subjective binary PSD outcomes, while effects on objective sleep parameters and longer-term sleep recovery remain uncertain. Further high-quality, multicenter trials using standardized and objective sleep assessments are needed. PROSPERO (CRD420261364623).
Wakefulness produces sleep-promoting substances and the cerebrospinal fluid contains substances that reflect homeostatic sleep pressure. However, identities of such molecules, and the neural mechanisms for producing and sensing them, remain mysterious. Here we show that cerebrospinal fluid levels of tryptamine (TrpA) track homeostatic sleep pressure in nocturnal mice and diurnal pigs, reflecting physical activity history independently of light-dark cycles. We developed a ratiometric fluorescent sensor for TrpA and showed that TrpA is produced by wake-active monoaminergic nuclei in the diencephalon and brainstem and is secreted in an activity-dependent manner. We showed that released TrpA binds to G-protein-coupled receptor 139 (GPR139) and enhances neuronal excitability in the hypothalamic preoptic area to promote sleep. TrpA-GPR139 signaling was necessary for homeostatic sleep rebound and small-molecule GPR139 agonists promoted sleep duration and quality. Together, our study reveals TrpA as a signal related to sleep homeostasis and GPR139 as a druggable target against its disruption.
Sleep disorders are prevalent in end-stage renal failure (ESRF) patients on dialysis. Renal transplantation may enhance the quality of sleep but comparative data are limited. The aim of our study was to assess the prevalence and factors linked to self-reported obstructive sleep apnea (OSA) and excessive daytime sleepiness (EDS) in kidney transplant recipients compared with dialysis patients. This cross-sectional study analyzed 159 renal transplant recipients using the STOP-BANG questionnaire, Berlin Questionnaire, and Epworth Sleepiness Scale. These results were compared to those for a historical cohort of 227 dialysis patients. Multinomial logistic regression models adjusted for demographic and clinical confounders were used to explore associations. In the combined cohort, 27.5% reported EDS (44.1% in dialysis vs. 3.8% in transplant patients, P < 0.001) and 30.6% reported OSA risk (41.9% in dialysis vs. 14.5% in transplant patients, P < 0.001). After adjusting for age, sex, body mass index, neck size, smoking, coffee intake, and comorbidities, renal transplantation was significantly associated with lower adjusted odds of EDS (odds ratio (OR): 0.014), OSA (OR: 0.422), and co-occurrence (OR: 0.092). No polysomnography data were available. Renal transplant patients reported fewer symptoms of EDS and OSA risk compared with dialysis patients, indicating potential benefits of transplantation beyond renal function. اضطرابات النوم شائعة بين مرضى الفشل الكلوي في مراحله النهائية الذين يخضعون لغسيل الكلى. ورغم أن زراعة الكلى قد تُحسّن جودة النوم، إلا أن البيانات المقارنة محدودة. يهدف البحث إلى تقييم مدى انتشار انقطاع النفس الانسدادي النومي والنعاس المفرط أثناء النهار لدى متلقي زراعة الكلى مقارنةً بمرضى غسيل الكلى، والعوامل المرتبطة بهما. حللت هذه الدراسة المقطعية بيانات 159 متلقيًا لزراعة الكلى باستخدام مقياس ستوب-بانق، واستبيان برلين، ومقياس إيبوورث للنعاس. وقورنت هذه النتائج بمجموعة تاريخية تضم 227 مريضا يخضعون لغسيل الكلى. واستُخدمت نماذج الانحدار اللوجستي متعدد الحدود، مع ضبط المتغيرات الديموغرافية والسريرية المؤثرة، لاستكشاف الارتباطات. في المجموعة المُجمّعة، أبلغ 27.5% عن النعاس المفرط أثناء النهار (44.1% لدى مرضى غسيل الكلى مقابل 3.8% لدى مرضى زراعة الكلى)، وأبلغ 30.6% عن انقطاع النفس الانسدادي النومي (41.9% لدى مرضى غسيل الكلى مقابل 14.5% لدى مرضى زراعة الكلى). بعد ضبط النتائج وفقا للعمر، والجنس، ومؤشر كتلة الجسم، وحجم الرقبة، والتدخين، وتناول القهوة، والأمراض المصاحبة، ارتبطت زراعة الكلى بشكلٍ ملحوظ بانخفاض احتمالية الإصابة بالنعاس المفرط أثناء النهار (نسبة الأرجحية 0.014)، وانقطاع النفس الانسدادي النومي (نسبة الأرجحية 0.422)، وتزامنهما (نسبة الأرجحية 0.092). لم تتوفر بيانات تخطيط النوم. يُبلغ مرضى زراعة الكلى عن أعراض أقل للنعاس المفرط أثناء النهار واحتمالية أقل للإصابة بانقطاع النفس الانسدادي النومي مقارنة بمرضى غسيل الكلى، مما يُشير إلى فوائد محتملة لزراعة الكلى تتجاوز تحسين وظائف الكلى.
Hormonal contraceptives (HC) have been shown to influence cognitive performance, yet their effects under conditions of sleep deprivation remain poorly understood. Consistent with prior research demonstrating greater fatigue among individuals using HC, we hypothesized that vigilant attention would be impaired among females using HC compared with males and females not using HC. Forty-eight participants (18-30 years; 23 females) underwent 28 hours of total sleep deprivation (TSD) while completing serial stress tasks, psychomotor vigilance tasks (PVT), and providing salivary cortisol samples. Mixed-effects models were constructed with either PVT outcomes or cortisol reactivity as dependent variables, group (males, females not using HC, females using HC) time, and mood induction group as fixed effects, as well as a group-by-time interaction, and participant as a random effect. Females using HC demonstrated significantly more PVT lapses (F(1,45) = 3.75; p = .031) and a trend toward lower PVT speed (F(2,44) = 3.05; p = .057) than males and females not using HC during the second half of the sleep deprivation period. No significant group differences were observed for PVT reaction time or false starts. Neither self-reported sleepiness, cortisol reactivity, or amplitude differed by group. Use of HC was associated with greater attentional instability following TSD, reflected by increased lapses and reduced vigilance efficiency. These effects occurred independently of cortisol responses. Larger studies are needed to further characterize the cognitive effects of HC use under sleep loss and to elucidate underlying mechanisms.
To assess the screening awareness of obstructive sleep apnea in children with Down syndrome among Primary Care and Pediatric Sub-Specialty Clinicians. A 15-question cross-sectional survey was conducted to determine the current awareness of OSA screening in DS children among primary care and pediatric subspecialty clinicians in the state of Kentucky. A Fisher's Exact test was performed to determine if the proportions of respondents differed significantly among different clinicians. A total of 97 responses were included. 73% of the clinicians specialized in pediatrics, 23% in family medicine, and 3% in ENT. Of the respondents, 50% were physician attendings, 27% were residents, and 23% were nurse practitioners or physician assistants. Although 94% of the respondents were aware that the prevalence of OSA in children with DS is higher than normally developing children, only 26% were aware of AAP guidelines and only 29.6% knew the age-specific threshold for screening regardless of symptoms. A significant difference existed between the type of clinicians who agreed that all DS children should undergo OSA screening regardless of symptoms: 85.4% of attending physicians, 57.7% of residents, and 81.8% of nurse practitioners (p < 0.03). In terms of specialty, 84% in pediatrics, 50% in medicine/pediatrics, and 59% in family medicine (p < 0.003). AAP screening guidelines for awareness of OSA in DS children vary among clinicians, their practice, and their specialty in Kentucky. Given the clinical implications of OSA, clinicians can utilize this study to identify knowledge gaps to address the barriers to screening guidelines education.
Associations between sleep duration and cognitive decline are inconsistent, and the value of longitudinal changes versus static measurements remains unclear. We identified longitudinal sleep patterns in 4780 older adults from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) using K-means clustering. Linear mixed-effects models and Cox models assessed cognitive decline and incident dementia risk over 10 years. The "Consistently Long" pattern showed the fastest cognitive decline (β = -0.027 standard deviation/year; p < 0.001) and highest cumulative dementia incidence. Conversely, patterns trending toward healthy duration slowed decline. However, adjusted Cox models found no significant association between sleep patterns and incident dementia risk. The trajectory of sleep duration, particularly the direction of change, is a powerful correlate of cognitive decline. Monitoring long-term dynamics outperforms static assessments for identifying high-risk older adults.
Working memory impairment has been reported in older adults with sleep disorders and MCI, with the frontoparietal network playing a central role in working memory. The key question is whether integrating Tai Chi with rTMS improves working memory, and whether such improvements result from the modulation of frontoparietal networks plasticity. Seventy-one participants with sleep disorders and MCI were assigned to the experimental group (Tai Chi + 1-Hz rTMS, n = 37) or sham group (Tai Chi + sham rTMS, n = 34). They completed 6 weeks of Tai Chi combined with neuronavigated rTMS targeted the right DLPFC and underwent fMRI scans. Outcomes included Numerical N-back task, digit span task，Pittsburgh Sleep Quality Index (PSQI), Montreal Cognitive Assessment (MoCA). Task fMRI measured N-back activation patterns, and seed-based resting-state functional connectivity (rsFC) was assessed. Correlations between the activation/rsFC and N-back task performance were explored. Seventy-one participants (mean age 67.6 ± 4.6 years; 30 male [42%], 41 female [58%]) were included. After 6 weeks, the experimental group showed significant improvements versus shams in PSQI, MoCA, 0-back and 2-back task accuracy, 0-back reaction time, and forward digit span (all p < 0.05). The 2-back accuracy was negatively correlated with right precuneus activation (r = -0.381, p = 0.034) and positively correlated with right precuneus connectivity to the left SMA (r = 0.367, p = 0.042). Adjunctive neuronavigated rTMS delivered in addition to Tai Chi training may enhance working memory rehabilitation in older adults with sleep disorders and MCI, with frontoparietal network modulation as a potential neural basis. Clinical trial registration no. ChiCTR 2200063274.
To evaluate the feasibility, diagnostic yield, and downstream clinical linkage of a hepatologist-driven obstructive sleep apnea (OSA) screening pathway using a modified STOP-Bang questionnaire in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). From July 2025 to March 2026, 555 outpatients with MASLD were screened using the Screening for OSA in MASLD (SOMA) model. Home sleep apnea testing (HSAT) referral relied on the modified STOP-Bang questionnaire, Epworth Sleepiness Scale (ESS), and clinical judgment. Among 276 HSAT-evaluated patients, 258 with valid recordings were analyzed. Clinically significant OSA was defined as a respiratory event index (REI) ≥ 15 events/hour. Among HSAT-evaluated outpatients with MASLD, OSA (REI ≥ 5 events/hour) and clinically significant OSA occurred in 253 (98.1%) and 203 (78.7%), respectively. The modified STOP-Bang questionnaire outperformed the ESS (area under the curve: 0.616 vs. 0.485, p = 0.021). A modified STOP-Bang score ≥ 3 showed high sensitivity (93.6%) but low specificity (7.3%), whereas a score ≥ 5 showed more balanced sensitivity (59.1%) and specificity (54.5%). ESS score ≥ 11 showed poor sensitivity (10.8%). Among patients with REI ≥ 15 and ≥ 30 events/hour, full polysomnography was completed or scheduled in 64.0% and 73.0%, respectively. OSA severity was not significantly associated with Fibrosis-4 index, Mac-2 binding protein glycosylation isomer levels, or shear wave elastography findings. Clinically significant OSA was frequent among selected HSAT-evaluated MASLD outpatients. The SOMA model may represent a feasible hepatologist-driven screening/referral pathway integrating structured triage, clinical judgment, and HSAT. However, these findings should not be interpreted as prevalence estimates or evidence of long-term clinical benefit.
High-frequency oscillations (HFOs) and sleep spindles are key neural rhythms in non-rapid eye movement (NREM) sleep with significance for information processing and epilepsy research. This review summarizes the neurophysiological basis of HFOs and spindles, with emphasis on cross-frequency coupling and its pathological alterations in epilepsy. Cross-frequency coupling reflects spatiotemporal coordination within thalamocortical-hippocampal networks and may serve as an electrophysiological marker for distinguishing physiological from pathological activity and localizing epileptogenic zones. To bridge the gap between clinical observation and underlying mechanisms, we evaluate the potential of Neural Mass Models (NMMs) in elucidating the generation and abnormal coupling of these oscillations. Ultimately, the integration of multimodal electrophysiology and computational modeling offers a transformative pathway toward enhancing diagnostic precision and personalizing therapeutic interventions in epilepsy.
Obstructive sleep apnea (OSA) is common yet frequently underdiagnosed, partly because overnight polysomnography (PSG) is logistically burdensome and access to specialized testing is limited. We aimed to develop machine-learning models for OSA risk screening using multimodal digital phenotyping from consumer-grade wearable devices, smartphone-based assessments, and clinical scales. We enrolled 338 participants and collected data over four weeks. After preprocessing, 107 features were derived from wearable-derived physiological and activity measures, smartphone-based records, and questionnaire-based clinical risk profiles, and used to classify high- versus low-risk OSA groups defined by the Berlin Questionnaire. Across multiple model configurations, predictive performance was high, with the best-performing model achieving an AUC of up to 0.94 and an F1 score of 0.80 in the internal validation set. Consistently influential predictors included body mass index, Insomnia Severity Index score, Smartphone Overuse Screening Questionnaire score, resting heart rate, and heart rate recovery. These findings suggest that multimodal digital phenotyping from accessible consumer technologies may support scalable pre-screening for OSA risk in real-world settings. Further validation against PSG-confirmed OSA outcomes is needed.Trial Registration: Clinical Research Information Service (CRIS) KCT0009175 (Registration data: Feb-15-2024) (https://cris.nih.go.kr/cris/search/detailSearch.do?search_lang=E&focus=reset_12&search_page=M&pageSize=10&page=undefined&seq=26133&status=5&seq_group=26133).