Sleep Medicine

Major international sporting events frequently impose exogenous demands that challenge adult circadian rhythms, often leading to the misalignment of sleep-wake cycles and social schedules. This cross-sectional study investigated the impact of the FIFA 2022 World Cup on adult sleep patterns to assess the prevalence and determinants of tournament-associated circadian disruption. Through an online survey, we captured data on sleep duration, timing, and subjective quality from a diverse adult population using Pittsburgh Sleep Quality Index (PSQI) score. The results indicate that 81.3% had high problematic sleep according to PSQI scores, while only 9% perceived that their sleep pattern was impacted by watching matches during the tournament. While 83.7% of the participants had low or mild anxiety according to GAD-7 scores, we found that GAD-7 scores correlated significantly with PSQI scores. Married participants had significantly lower PSQI scores (RR 0.856, p = .005), while those who reported that their sleep hours had changed during the tournament had significantly higher PSQI scores (1.180, P-value <0.001). Males reported a significantly high impact of the tournament on their sleep (OR 2.622, P-value <0.001). In conclusion, our data demonstrate a discrepancy between self-perception of sleep quality and self-rated assessment by PSQI scores, as well as the substantial impact of major international sporting events on adult sleep hygiene. The results provide data-driven insights helpful in evaluating potential circadian risks and informing public health strategies for major sporting events such as the FIFA world cup.

ObjectiveTo examine whether hypoxic burden is distinctly associated with key drivers of glymphatic activity, independent of sleep fragmentation. BackgroundOSA is a robust risk factor for multiple neurodegenerative conditions, including Alzheimers disease, with glymphatic impairment representing a potential mechanistic pathway. However, it remains unknown whether distinct pathological features of OSA, including hypoxic burden and sleep fragmentation, are differentially associated with the two key physiological drivers of glymphatic activity: (1) coordination between brain pulsations and CSF flow and (2) brain pulsation strength. MethodTwenty-eight individuals with newly identified OSA and eight healthy individuals without OSA completed either in-lab polysomnography or WatchPAT, providing estimates of hypoxic burden, quantified as time spent below 90% oxygen saturation (T90), and sleep fragmentation, quantified as non-hypoxic respiratory effort-related arousals (RERAs). Participants also completed 7T resting-state fMRI to quantify the coordination between brain pulsations and CSF flow using gBOLD-CSF coupling (i.e., cross-correlation between gray matter blood oxygen level dependent signal pulsations and CSF inflow) and brain pulsation strength using gBOLD amplitude. Hierarchical regression and Pearson correlations were used to examine associations between sleep measures and fMRI-derived metrics. ResultsGreater T90 was associated with weaker gBOLD-CSF coupling, independent of age, sex, race, and RERAs (Table 2; {beta}=0.07, p=0.008). T90 also significantly improved model-explained variance in gBOLD-CSF coupling (Table 2; {Delta}R2=0.20, p=0.008). Contrary to expectations, greater T90 was associated with higher gBOLD amplitude across the temporal lobe and multiple frontal and parietal regions. Within regions showing T90-linked elevations in gBOLD amplitude, higher gBOLD amplitude was not associated with stronger region-specific gBOLD-CSF coupling. This contrasted with regions not associated with T90, where higher gBOLD amplitude was associated with stronger gBOLD-CSF coupling (difference in {beta}=0.0006, p<0.001). RERAs were not associated with gBOLD-CSF coupling and gBOLD amplitude throughout the cerebral cortex. O_TBL View this table: org.highwire.dtl.DTLVardef@107050eorg.highwire.dtl.DTLVardef@1dcf868org.highwire.dtl.DTLVardef@3899baorg.highwire.dtl.DTLVardef@1f4a867org.highwire.dtl.DTLVardef@15c281f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONAssociation of T90 with the coupling strength between gray matter pulsations and CSF flow derived from a nested, hierarchical modeling approach Acronyms. RERA=respiratory effort-related arousal index; T90=time of sleep spent under 90% oxygen saturation C_TABLECAPTION C_TBL ConclusionsIn OSA, hypoxic burden, rather than respiratory effort-related sleep fragmentation, may be the primary pathological feature associated with impaired brain pulsation and CSF dynamics, both of which are key drivers of glymphatic activity. These alterations may be most prominent in the temporal lobe, potentially reflecting its elevated metabolic demand and vulnerability to hypoxemia.

BackgroundMedical students face demanding academic schedules and elevated stress levels, predisposing them to poor sleep quality. Sleep hygiene -- a set of behavioural and environmental practices aimed at optimising sleep -- has been identified as a modifiable determinant of sleep quality, yet its role among medical students in Sudan remains unstudied. ObjectivesTo assess current sleep hygiene practices among medical students at UMST and determine their association with sleep quality outcomes. MethodsA facility-based cross-sectional study was conducted at UMST among 240 medical students from three academic batches (3rd, 4th, and 5th year), selected via stratified random sampling. Data were collected using two validated self-administered instruments: the Pittsburgh Sleep Quality Index (PSQI) and the Sleep Hygiene Index (SHI). Descriptive statistics, independent sample t-tests, one-way ANOVA, chi-square tests, Pearson correlation, and binary logistic regression were performed using SPSS version 23. ResultsPoor sleep quality (PSQI >5) was prevalent in 72.1% of participants (mean PSQI 7.25 {+/-} 2.66), and poor sleep hygiene (SHI >16) in 92.5% (mean SHI 27.1 {+/-} 7.9). SHI score (continuous) was the only significant independent predictor of sleep quality on logistic regression (OR = 1.13 per unit increase; 95% CI: 1.08-1.19; p < 0.001), equivalent to a 3.4-fold increase in odds per 10-unit rise in SHI score. Female sex was additionally identified as a significant predictor (OR = 1.88; 95% CI: 1.00-3.53; p = 0.049). A significant positive correlation was observed between PSQI and SHI scores (r = 0.359, p < 0.001). ConclusionPoor sleep hygiene is highly prevalent among UMST medical students and is the most significant modifiable predictor of poor sleep quality, with each unit increase in SHI score increasing the odds of poor sleep quality by 13%. These findings highlight a gap in sleep health education within Sudanese medical institutions and support the integration of targeted sleep hygiene interventions into the medical curriculum.

Introduction: Actigraphy sleep-wake classification methods increasingly seek to leverage raw acceleration data and machine-learning-based classification, but performance evaluation in pediatrics is limited. We trained machine-learning models using pediatric data and compared their sleep-wake classification performance with existing algorithms for children. Methods: Sixty-five children (46% female, ages 5.3 to 17.7 years) completed in-lab overnight polysomnography and wore a GENEActiv device on their non-dominant wrist. The acceleration data were converted into 30-second epochs and aligned with physician-scored sleep-wake data from electroencephalography. Seven machine-learning models were trained using leave-one-subject-out cross-validation. Epoch-by-epoch analyses generated performance metrics (e.g., balanced accuracy [BA]) and discrepancy analyses provided overall sleep duration bias estimates. The combination of highest performance and least bias was used to rank using Euclidean distance scores - where a lower score represents closer to perfect performance and zero bias. For benchmarking, we included GGIR sleep scoring algorithms and an adult trained random forest classifier. Results: Overall, 560.1 hours of polysomnography and actigraphy data were collected (74.4% of epochs were scored as sleep). The pediatric-trained local-global long-short term memory (LSTM) classifier had the most optimal epoch-by-epoch performance (e.g., BA=0.85, sensitivity=0.88, specificity=0.83, ROC-AUC=0.95, and Cohen kappa=0.67). These metrics exceeded that of an adult-trained random forest classifier and GGIR-based algorithms. Discrepancy analyses revealed that overall sleep duration was underestimated by an average of 25 minutes using the LSTM classifier with no proportional bias. Conclusion: We trained seven pediatric sleep-wake classifiers that had strong ability to detect sleep and wake, with the LSTM classifier being most optimal.

Rationale: Conventional measures of obstructive sleep apnea severity, particularly the apnea-hypopnea index, do not adequately capture event-level neurophysiologic responses to respiratory events. Whether post-apnea/hypopnea arousal dynamics provide prognostic information beyond established metrics remains unknown. Objectives: To determine whether post-apnea/hypopnea arousal dynamics are associated with all-cause and cardiovascular mortality. Methods: We conducted a retrospective analysis of in-home polysomnography data from 8,053 adults across four community-based cohorts. Peak time (PT; latency to maximal arousal probability), peak height (PH; maximal arousal probability), and area under the curve (AUC; cumulative arousal probability) were derived from peri-stimulus time histograms aligned to event termination. Associations with mortality were examined using multivariable Cox models and random-effects meta-analysis. Measurements and Main Results: PT, but not PH or AUC, was associated with mortality. In pooled analyses, each 1-second delay in PT was associated with higher all-cause mortality in males (hazard ratio [HR], 1.04; 95% confidence interval [CI], 1.02-1.06) and females (HR, 1.03; 95% CI, 1.00-1.06). For cardiovascular mortality, each 1-second delay in PT was associated with higher risk in males (HR, 1.05; 95% CI, 1.02-1.08) but not females (HR, 1.04; 95% CI, 0.99-1.10). Associations were driven primarily by non-rapid eye movement sleep and remained materially unchanged after additional adjustment for apnea-hypopnea index, arousal index, and hypoxic burden. Conclusions: Delayed arousal timing after apnea/hypopnea termination was associated with increased mortality risk independent of conventional measures of obstructive sleep apnea severity. Event-level arousal timing may provide prognostic information beyond count-based and hypoxemia-based metrics.

Obstructive sleep apnoea (OSA) is a disorder marked by repeated episodes of airway collapse during sleep, leading to hypoxaemia and sympathoexcitation. Its impact on brain fluid transport remains unclear. We investigated MRI-visible perivascular spaces (PVS) in healthy controls (n=20; 5 females, mean{+/-}SD age = 52.1{+/-}9.9 years) and OSA patients (n=20; 3 females, mean{+/-}SD age = 54.6{+/-}9.6 years) before and after continuous positive airway pressure (CPAP) therapy in a longitudinal case-control study. MRI-PVS were automatically quantified using a deep learning model called the nnU-Net. At baseline, OSA patients had significantly greater whole-brain PVS volumes and cluster counts than controls (volume: exp({beta})=1.65, 95%CI [1.07, 2.51], p=0.01; cluster counts: exp({beta})=1.51, 95%CI [1.1, 2.04], p=0.01). However, after 12 months of CPAP, these differences were no longer significant (volume: exp({beta})=1.56, 95%CI [1.03, 2.39], p=0.054; cluster counts: exp({beta})=1.39, 95%CI [0.97, 1.92], p=0.072). Similarly, PVS metrics were significantly greater in OSA patients than controls at baseline in the frontal (volume: exp({beta})=1.66, 95%CI [1.02, 2.64], p=0.04; cluster counts: exp({beta})=1.46, 95%CI [1.02, 2.08], p=0.04) and temporal lobe (volume: exp({beta})=1.92, 95%CI [1.2, 3.03], p=0.01; cluster counts: exp({beta})=1.68, 95%CI [1.1, 2.55], p=0.02). After 12 months of CPAP, PVS metrics remained significantly higher in the OSA patients compared to controls in the frontal (volume: exp({beta})=1.68, 95%CI [0.94, 2.87], p=0.085; cluster counts: exp({beta})=1.4, 95%CI [0.92, 2.05], p=0.12) and temporal lobes (volume: exp({beta})=1.54, 95%CI [0.94, 2.38], p=0.085; cluster counts: exp({beta})=1.44, 95%CI [0.95, 2.12], p=0.089). These findings suggest that OSA is associated with PVS enlargement, which may be regionally reversible with CPAP treatment.

ObjectivesChronic insomnia (INS) is particularly prevalent in older adults and females. Sex-and age-related differences in neurophysiological markers of sleep quality (sleep spindles and slow-wave activity [SWA]) may underlie differential vulnerability to INS. This study investigated the effects of sex and insomnia on spindle and SWA beyond aging, to better understand the mechanistic differences contributing to the higher prevalence of INS in females. MethodsAfter a habituation night, one night of sleep assessed with polysomnography was analyzed in 222 adults (aged 18-82) including 119 INS (71% female) and 103 healthy sleepers (HS; 61% female). Spindle density, slow oscillation (SO) density, relative sigma power and SWA were derived during NREM sleep. Age, group, sex, and group-by-sex interactions were examined, with age as a covariate. ResultsAge, insomnia, and sex each contributed uniquely to NREM oscillatory activity. INS primarily reduced spindle and SO density, while sex accounted for differences in SWA. While SWA was higher in females overall, sex differences were not significant within the INS or HS groups. Female INS reported highest rates of insomnia severity as well as lower sigma power than males in the INS group. Spindle and SO density deficits were also present in female INS relative to female HS, as well as male INS relative to male HS. ConclusionsThe combination of reduced sigma power in females with insomnia relative to their male counterparts, as well as less spindle and SO density compared to female healthy sleepers may contribute to greater insomnia severity in females. Statement of SignificanceInsomnia is a growing public health concern that is more commonly reported in females, yet the neural mechanisms underlying this sex difference remain poorly understood. Our findings suggest that specific markers of sleep quality are disproportionately disrupted in females with insomnia, potentially contributing to greater vulnerability and symptom severity. These results provide new insight into how sex influences the neurophysiology of insomnia disorder and identify oscillatory markers that could serve as targets for personalized interventions. Future research should investigate whether these alterations represent persistent dysfunction or reversible changes, which could advance understanding of the biological basis of insomnia and inform strategies to improve sleep health in at-risk populations.

Sleep spindles are rhythmic electroencephalographic signatures of non-rapid-eye-movement sleep. Their dysregulation has been implicated in several neuropsychiatric illnesses. Spindles have a characteristic waxing and waning shape, but the cellular and circuit mechanisms controlling their shape are not well understood. Recent but sparse research has implied that sleep spindle shape becomes abnormal in post-traumatic stress disorder (PTSD). PTSD patients have dysfunctional GABAA receptors in midline thalamic regions, areas involved in the orchestration of sleep spindles. We modelled this GABAA dysfunction within thalamocortical (TC) neurons using localized CRISPR-Cas9 technology to test the hypothesis that GABA dysfunction would dysregulate sleep spindle shape and cause symptoms of PTSD, in mouse model behavioral evaluations. We found sleep spindles were shorter and abnormally shaped, having lost their characteristic waxing and waning shape, in mice with GABAA receptor knock-down in TC neurons (TC-1KD). TC-1KD mice failed to recover from learned fearful reactions following an aversive stimulus. We tested this with a contextual fear conditioning paradigm using electric foot shocks. A control group with intact GABAA receptors successfully habituated to the fear conditioned location in subsequent visits to that context without foot shocks. In contrast, TC-1KD mice never habituated, suggesting abnormally extended fearful memories. The number of inhibitory post synaptic currents in TC neurons were significantly decreased in vitro, confirming an effective knock-down. Our results imply that abnormally shaped sleep spindles may serve as a biomarker of GABAA receptor dysfunction in TC neurons which may be involved in abnormal fear processing in PTSD. We postulate GABAA receptor dysfunction in TC neurons may be underlying pathophysiology of PTSD and our findings here may inspire the development of screens, diagnostics and objective characteristics of stress related disorders, including PTSD.

Objective: Several endotypes contribute to the development of Obstructive Sleep Apnea (OSA). However, efforts to measure these endotypes have been challenging. In this paper, we propose a new method that overcomes some of these challenges. Methods: To test the feasibility of this new method, data from the Sleep Heart Health Study (SHHS) were analyzed and two oxygen-based endotypes were identified and plotted on a graphical model: the steady-state SpO2 and the SpO2 arousal threshold. The first is the oxygen saturation that would occur during sleep if there were no arousals, and it is a measure of upper airway collapsibility (a more collapsible airway produces a lower SpO2). The latter is the oxygen saturation that triggers arousals. These endotypes were validated by assessing their ability to detect positional and state-related changes in airway collapsibility and arousal threshold. Results: The study showed that it was feasible to measure oxygen-based endotypes in 95% of SHHS participants. As expected, steady-state SpO2 was lower during supine vs. non-supine sleep, as well as during REM vs. NREM sleep. Also, the SpO2 arousal threshold was similar between supine and non-supine sleep. However, SpO2 arousal threshold was not lower in REM sleep vs. NREM sleep. Therefore, in 3 of the 4 conditions, the oxygen-based endotypes moved in the expected direction due to positional or sleep state changes. Conclusion: Although further validation experiments are required, this study indicates that OSA endotyping using the pulse oximetry signal is feasible. The oxygen-based endotypes could be used to aid therapeutic decision making.

Background Postoperative sleep disorder, a frequently observed complication, is associated with heightened pain sensitivity, exacerbated inflammatory reactions, and compromised tissue repair. Sufentanil, a highly selective -opioid receptor agonist, is widely used in patient-controlled intravenous analgesia (PCIA) and has been associated with reduced sleep efficiency. Oxycodone, as a /{kappa} dual receptor agonist, has shown a lower incidence of adverse effects in clinical practice. Despite these pharmacological differences, the comparative effects of oxycodone- versus sufentanil-based PCIA on postoperative sleep remain poorly characterized. Recent advances in wearable devices demonstrate strong agreement with polysomnography (PSG) in intergroup comparisons of sleep efficiency and total sleep time, enabling continuous, non-invasive, multi-night sleep monitoring and offering a viable alternative for clinical postoperative sleep research. Hence, we design this clinical trial to compare postoperative sleep efficiency between patients receiving oxycodone-based versus sufentanil-based PCIA under wearable sleep monitoring. Methods This study is a randomized, double-blind, placebo-controlled trial that was conducted at a single center. A sample size of 68 patients was determined through calculation, and these patients will be randomly assigned to either the oxycodone group or the sufentanil group. Sleep monitoring was initiated using a wristband device one day before surgery after recruitment. The sleep quality data at different setting time will be monitored. All patients will be followed up by blinded evaluators at baseline and 1, 2, and 30 days after the intervention. The follow-up included pain scores, postoperative complications and adverse events, etc. Discussion By integrating a modern photoelectric device with first-line analgesics, we hope the result of the study will inform perioperative sleep management, guide clinical analgesic selection, and improve patient recovery quality.

Abstract Background Prediction of long-term neurodevelopmental outcomes remains challenging after perinatal asphyxia. Here, we studied whether computational metrics of brain function derived from neonatal EEG are associated with long-term neurodevelopment in infants with perinatal asphyxia. Methods Total of 36 term-born infants with perinatal asphyxia with or without hypoxic-ischemic encephalopathy were studied with neonatal multichannel electroencephalography (EEG). We computed local EEG amplitudes and phase-amplitude coupling (PAC), as well as large-scale functional cortical networks estimated using amplitude-amplitude correlations (AAC) and phase-phase correlations (PPC). These EEG-derived markers were tested for associations with neurodevelopmental outcomes at two years, assessed using the Griffiths Scales of Child Development, 3rd edition (GMDS-III). Results EEG amplitudes showed positive associations with GMDS-III Foundations of Learning and General Development scores across most electrodes during quiet sleep, with the strongest effects observed at frontal and central regions (r = 0.44-0.66). PAC showed negative associations with the same scores mainly over parietal and temporal regions (r = -0.45 to -0.55). Cortical AAC networks demonstrated the most robust and widespread negative associations in all frequency bands during quiet sleep (r = -0.47 to -0.54), with 70-72% of connections significant in high delta frequency. In turn, PPC networks showed frequency-selective and more spatially constrained negative associations during quiet sleep (r = -0.48 to -0.53), involving 5-12% of the network. Conclusions Both local and network-based metrics in the newborn brain show significant association with neurodevelopmental outcome at 2 years after perinatal asphyxia.

The transition from wake to stable sleep is characterized by multiple neural, physiological, and behavioral changes. How these changes may differ in individuals with difficulties falling asleep such as children with neurodevelopmental conditions is poorly understood. Here, we studied sleep initiation in >2000 nights recorded from 186 children who participated in the Simons Sleep Project (SSP). Data included simultaneous, synchronized recordings of actigraphy, electroencephalography (EEG), photoplethysmography (PPG), and skin temperature. We extracted multiple neural, physiological, and behavioral measures that are known to increase/decrease during the sleep initiation period including EEG delta (1-4Hz) power, movement counts, heart rate (HR), and skin temperature. Transitions from 20 minutes before sleep onset to 40 minutes after sleep onset were modeled with a sigmoid function enabling the quantification of transition timing, speed, and magnitude per measure. Individuals with longer sleep onset latencies (SOL) exhibited smaller increases in EEG delta power and skin temperature as well as smaller decreases in HR and activity counts. These findings indicate that difficulties falling asleep are associated with multiple forms of cortical, physiological, and behavioral hyperarousal that can be measured at home with wearable devices. Importantly, transition magnitudes were key to explaining differences in SOL across participants (26% explained variance) in contrast to transition speed or timing within the sleep initiation period (<13% explained variance). Longer SOL and weaker transitions were particularly prominent in children diagnosed with autism and/or attention deficit hyperactivity disorder (ADHD).

We completed a video-based, four-night, in-home, level 3 sleep apnea study of healthy, low-risk pregnant participants and their bed partners in order to characterize sleep physiology in the third trimester of pregnancy. Demographic, anthropometric, and baseline sleep health characteristics were recorded, and the NightOwl home sleep apnea test device was used to measure sleep breathing, posture, and architecture parameters. Symptoms of restless legs syndrome were elicited in the exit interview. Forty-one pregnant participants and 36 bed partners completed the study. Bed partners had a significantly higher prevalence of sleep apnea than their pregnant co-sleepers (31% vs. 5.9%). Bed partners also had more severe sleep apnea than their pregnant co-sleepers, and this persisted on an adjusted analysis for baseline differences in factors known to increase risk of sleep apnea. In pregnant participants, increasing gestational age was found to be protective against mild respiratory events but not more severe events. While the correlation between STOP-Bang score and measures of sleep apnea severity was weak, an affirmative response to the "witnessed apneas" item on the STOP-Bang questionnaire was a strong predictor of more severe sleep apnea for all participants. Smoking history also increased sleep apnea risk. Pregnant participants had lower sleep efficiency and longer self-reported sleep onset latency. Restless legs syndrome was experienced by 39.5% of the pregnant participants but no bed partners. From a sleep breathing perspective, people with healthy, low-risk pregnancies have better sleep than their bed partners despite lower sleep efficiency and higher rates of restless legs syndrome. Clinical Study RegistrationSleep in Late Pregnancy - Artificial Intelligence Development for the Detection of Disturbances and Disorders (SLeeP AID4), https://clinicaltrials.gov/study/NCT05376475, registration ID NCT05376475. Statement of SignificancePregnancy negatively impacts sleep, and poor sleep in pregnancy negatively impacts maternal and fetal health. Pregnancy represents a unique challenge to sleep breathing physiology and, thus, an opportunity to test for sleep apnea. Sleep apnea however, while increased in pregnancy, is more common in males. This novel study tested healthy people with low-risk pregnancies and their bed partners for sleep apnea in the comfort of their home over four nights in late pregnancy. Sleep apnea was more common and worse in the bed partners. Advancing gestational age was protective against mild but not severe sleep apnea, and a critical remaining knowledge gap is this interplay in high-risk pregnancies. Future sleep in pregnancy research should make efforts to include high-risk pregnancies.

Objectives: Self-applied, low-density EEG offers opportunities to examine sleep in the home environment, yet its feasibility during behavioural sleep interventions remains unexplored. This pilot study aimed to evaluate the feasibility and acceptability of a self-applied, low-density EEG device during sleep restriction therapy (SRT) and explore effects on sleep and affect. Methods: Seventeen adults with insomnia and depressive symptoms completed a 2-week baseline and 4 weeks of SRT. The primary outcome was the proportion of expected EEG recordings completed and scoreable. Secondary outcomes included clinical measures, sleep continuity (sleep diary, actigraphy), sleep architecture (low-density EEG for 9 nights), power spectral density, and affect. Data were analysed with linear mixed models. Cohen's d and 95% confidence intervals were reported. Results: Feasibility was demonstrated (92% of expected EEG nights completed). SRT was associated with reductions in insomnia severity, depressive symptoms, negative affect, and increases in positive affect. Robust improvements were observed across treatment in sleep continuity (SOL, WASO, SE) from diary, which were paralleled by actigraphy. EEG revealed reduced TIB, TST, N1, N2, REM sleep, and REM latency during week one. Reductions in EEG-derived TIB and N1 sleep were maintained at night 28. There were no reliable differences for spectral or spindle measures. Conclusions: These findings suggest that self-applied, low-density EEG during SRT is feasible, acceptable, and may capture sleep changes during treatment. They highlight the potential for multi-night monitoring of sleep interventions at home and elucidating mechanisms underlying therapeutic change.

Smartphone use among medical students has become pervasive. While existing literature links excessive smartphone use to poor sleep quality, the specific behavioral pattern most strongly associated with sleep disruption remains insufficiently characterized. This study investigated whether the timing of smartphone cessation relative to sleep onset is more strongly associated with poor sleep quality than total daily screen time among medical students in Punjab, Pakistan, and examined the moderating role of exam period status. A cross-sectional anonymous online survey was conducted among medical students across Punjab, Pakistan (May 2026). Sleep quality was assessed using items informed by Pittsburgh Sleep Quality Index (PSQI) response formats. Descriptive statistics, chi-square tests, and binary logistic regression were applied to 369 eligible responses, reported in accordance with STROBE guidelines. Of 369 respondents (49.9% female, 48.2% male), 74.8% reported using smartphones 6 or more hours daily and 61.2% used their smartphone until falling asleep. Overall, 75.7% reported poor sleep quality. Students using smartphones until sleep onset had 95.1% poor sleep quality compared to 44.8% in those who ceased use before sleeping (p<0.001). In logistic regression with both variables entered simultaneously, bedtime use until sleep onset remained independently associated with poor sleep quality (OR 15.3, 95% CI 5.7-41.2, p<0.001), while total daily screen time lost significance (OR 1.8, 95% CI 0.7-4.7, p=0.228). Outside exam periods, 99.0% of students using smartphones until sleep onset reported poor sleep quality versus 24.2% of those who stopped before sleeping, a difference of 74.8 percentage points (p<0.001). During exam periods, no significant association was observed (p=0.075), suggesting exam-related stress may attenuate the bedtime behavior effect. Hostel-dwelling students showed the highest prevalence of bedtime smartphone use, with 79.0% using smartphones until sleep onset compared to 23.2% of family-living students (p<0.001). Bedtime smartphone use until sleep onset is more strongly associated with poor sleep quality than total daily screen time among Pakistani medical students. Medical institutions should consider integrating targeted digital wellness education specifically addressing bedtime cessation timing into student health programs, with particular attention to hostel-dwelling students.

A systematic review and meta-analysis of sleep studies in schizoaffective disorder were conducted using published articles researched in major databases within the period from inception to December 1, 2025. The sleep parameters: total sleep time, sleep efficiency, sleep latency, wakefulness, REM time and percentage, REM latency, REM density, stage 1, 2, 3 and 4 sleep time and percentage, delta sleep time and percentage, of drug-free schizoaffective patients were analyzed and, where available, compared with case-control data of healthy controls, depressed unipolar patients and schizophrenic patients. Forty studies were identified in the systematic review. Nine case-control studies with 67 schizoaffective patients, 88 schizophrenic patients, 79 healthy controls and 131 depressed patients were included in the meta-analyses. The primary outcome was the standard mean difference. Data were fitted with a random-effects model. Publication bias assessment was checked by Egger's Regression and funnel plot asymmetry. Patients with schizoaffective disorder showed reduced total sleep time, increased sleep latency and wakefulness, along with reduced REM time and shortened REM latency, reduced stage 4 sleep time and percentage compared to healthy controls. Patients with schizoaffective disorder differed from depressed patients only for increased sleep latency, while they did not show any difference compared to patients with schizophrenia. SZA showed a non-significant trend (p=0.08) towards increased REM density compared to SCZ, suggesting the need to better clarify the role of REM density in mood and psychotic disorders.

Purpose: Obstructive sleep apnea (OSA) is a treatable chronic condition associated with significant health and societal consequences. Primary care providers (PCPs) often manage OSA with support from sleep specialists but face challenges navigating a complex system of care. By developing a Journey Map, we sought to identify factors influencing primary care OSA management and the associated PCPs' perspectives and emotions. Methods: Twenty-one Calgary-based PCPs were interviewed as part of a study evaluating a primary care management pathway for OSA. We used conventional content analysis, utilizing inductive coding to define journey phases and deductive coding via the Theoretical Domains Framework (TDF) to identify barriers and enablers. These were then mapped onto journey phases for OSA management to create a Journey Map. Results: The Journey Map included five phases of OSA care. PCPs described feeling neutral during the Learning phase and expressed neutral to positive emotions during the Patient Encounter and Diagnosing OSA phases. In contrast, the Initial Treatment and Ongoing Management phases were associated with neutral to negative emotional experiences. Barriers included limited OSA-related training and education, unclear roles among provider groups, and low patient engagement. Enablers included accessible knowledge resources, a shared key role in OSA screening, and availability of sleep testing. Opportunities to enhance primary care OSA management were identified at each step. Conclusion: This study identified several behavioural factors influencing PCP decision-making across the OSA care continuum. The Journey Map illustrates how high diagnostic confidence of PCPs shifts to escalating challenges and negative sentiment during treatment and long-term management of OSA. Keywords: obstructive sleep apnea; primary health care; health service delivery; process assessments; attitude of health personnel

BackgroundSleep-onset insomnia (SOI) is characterized by difficulty initiating sleep and is frequently associated with psycho-affective disorders. Despite its high prevalence and clinical impact, pathophysiological biomarkers and clear nosological frameworks remain lacking. Conventional polysomnographic (PSG) measures provide limited insight into the continuous dynamics of vigilance during the transition from wakefulness to sleep and across the night. MethodsWe retrospectively analyzed PSG recordings from 2 952 individuals using fine-grained EEG markers of vigilance, including theta/alpha ratio dynamics, micro-sleep episodes, and probability-of-wakefulness metrics. Individuals with and without SOI were compared, and SOI subgroups with and without depressive or anxiety symptoms were further examined. ResultsIndividuals with SOI exhibited a persistent state of elevated EEG-defined vigilance extending from wakefulness through the sleep onset period (SOP) and across all sleep stages, including N2, N3, and REM sleep. This hypervigilance was associated with vigilance instability during the SOP and a delayed accumulation of deep sleep over the night. Importantly, hypervigilance was more pronounced in isolated SOI than in SOI comorbid with psycho-affective symptoms, particularly depressive symptoms, and remained largely undetected by conventional PSG macrostructure measures. ConclusionsThese findings support a reconceptualization of SOI as a disorder of sustained vigilance dysregulation and reveal heterogeneity in hypervigilance across insomnia phenotypes. This dissociation from psycho-affective symptoms challenges current nosological frameworks at the interface of sleep and psychiatric disorders. By capturing microstructural alterations in vigilance invisible to standard scoring, continuous EEG-based markers provide mechanistic insight into insomnia heterogeneity and may enable biologically informed phenotyping across psychiatric conditions.

Background Narcolepsy is a rare, lifelong neurological disorder that often begins in childhood or adolescence. Diagnosis is frequently delayed because current diagnostic testing relies on specialist in-patient sleep investigations: overnight polysomnography (PSG) followed by a multiple sleep latency test (MSLT), interpreted according to International Classification of Sleep Disorders criteria (ICSD-3-TR). These investigations are expensive, labour intensive, and available in a limited number of centres, contributing to delays and inequity of access. Automated analysis of sleep-stage probabilities (hypnodensity) using neural networks has shown promising diagnostic performance in research cohorts but still requires hospital-based PSG acquisition. The Dreem 3 headband (DH) is a comfortable, dry-montage EEG device designed for home use. Combined with its proprietary machine learning classification of sleep stages, it may offer accurate ambulatory sleep physiology assessments and support clinical decision making. Methods This was a single-centre, prospective, observational study recruiting 60 participants aged 10 to 35 years undergoing investigation for hypersomnolence within GSTT sleep services and scheduled for PSG and MSLT as part of routine care. Exclusion criteria included physician-diagnosed medical or psychiatric disorder that could independently account for excessive daytime sleepiness; and/ or regular use of prescribed or recreational medication known to affect sleep architecture. Participants first wore the DH at home for five weeknights, followed by a continuous 48-hour weekend recording using two devices in rotation. They then underwent routine in-patient PSG and MSLT. PSG and MSLT were interpreted according to ICSD-3 by an experienced sleep physician and a final diagnosis determined by a sleep physiology consultant. The primary outcome is accuracy of ambulatory DH-based assessment of sleep physiology and subsequent diagnosis of sleep disorders. We evaluate proprietary and in-house developed machine learning methods to detect SOREM epochs and predict narcolepsy diagnosis from PSG, PSG+MSLT and DH data. All algorithmic outcomes will be compared to clinical outcomes derived from current clinical standard of care. Discussion This study will provide proof-of-concept evidence for a home-based wearable EEG approach to narcolepsy diagnosis. Patient and public involvement work with young people with confirmed narcolepsy indicates high acceptability of the DH protocol: in a survey of ten young people, eight reported they would be willing to wear a sleep headband nightly at home for five days (two were unsure), and seven reported they would be willing to wear it continuously for 48 hours over a weekend (two were unsure; one said no). These findings informed the decision to restrict continuous wear to the weekend, reflecting feedback that daytime wear during school or work hours would be unacceptable. If validated, this approach could reduce delays to diagnosis, improve equity of access, and support development of a subsequent multicentre study. Trial registration IRAS Project ID: 321547. Registered October 2022. Recruitment was completed on 30 January 2026.

Motor memory retention is impaired in Parkinsons disease (PD), affecting long-term rehabilitation outcomes. It appears that NREM sleep could be beneficial for consolidation processes in PD, and could be leveraged with non-invasive sleep interventions. This study examined the effect of auditory targeted memory reactivation (TMR) during NREM sleep on the retention of a motor sequence learning finger tapping task in 20 PD and 20 healthy older adults (HOA). TMR was applied during a 2-hour nap and its effect on motor retention was post-nap, after 24-hours and with a dual-task. The impact of TMR on sleep electrophysiology was also evaluated. Results showed no effect of TMR on motor retention or dual-tasking, with no difference between the groups. However, the TMR intervention did increase slow-wave density and decreased spindle density in both groups, and slow-wave amplitude during the presentation of the auditory cues was positively associated with performance in HOA. In conclusion, TMR applied during a 2 hour nap did not enhance motor retention, but the changes in sleep physiological features could be linked to a possible underlying effect on memory processing that warrants further investigation.