OBJECTIVE: The Karolinska Sleepiness Scale (KSS) is widely used for assessing current level of sleepiness, but it has not been validated in South Korea. This study aimed to validate the KSS using the Stanford Sleepiness Scale (SSS), polysomnography (PSG), and electroencephalography (EEG).
METHODS: The sample consisted of 27 adult participants in this study aged 40.5±7.7 years (mean±standard deviation) and included 22 males. They completed questionnaires and underwent EEG recording and overnight PSG. The KSS was completed from 18:00 to 24:00 every 2 hours and following PSG (at 07:00). KSS scores changed over time and in particular increased with the time since waking, with the score peaking at 24:00.
RESULTS: Convergent validity of the KSS was verified by performing a Spearman correlation analysis between the KSS and SSS (r=0.742, p<0.01). Concurrent validity of the KSS was verified by performing a Spearman correlation analysis between the KSS administered before sleep and the sleep onset latency measured using PSG (r=-0.456, p<0.05). Alpha waves were measured 5 minutes before administering the KSS, and the KSS scores were compared with these alpha waves. There were no significant correlations observed between the KSS scores and alpha waves measured in the left occipital area (O1), left frontal area (F3), or left central area (C3). In addition, Spearman correlation analyses of the difference between KSS scores and alpha waves measured at O1, F3, and C3 produced no significant results.
CONCLUSIONS: This study verified the convergent validity and concurrent validity of the KSS, and confirmed the capabilities of this scale in assessing sleepiness changes over time.

UNASSIGNED: Resilience can mitigate the negative impact produced by the COVID-19 pandemic. Medical students endure significant academic stress, so adjusting to sudden changes can present greater mental health challenges. The aim is to identify the level and prevalence of resilience and to know what are the educational variables and is sleep quality associated with resilience.
UNASSIGNED: A cross-sectional study was conducted using an online questionnaire. The survey was elaborated in Google Forms and shared through social networks. The outcome was resilience, measured with the Connor Davidson Resilience Scale. Its association was assessed with sleep quality (measured with the Pittsburgh Sleep Quality Index), daytime sleepiness (measured with the Epworth Sleepiness Scale), and selected academic/sociodemographic variables. Generalized linear models were used to identify the association between the variables.
UNASSIGNED: Of 1277 participants, 35.7% experienced high resilience. Poor sleep quality and sleepiness were present in 88.4% and 36.0% of students, respectively. High resilience was associated with good sleep quality (PR:1.56; 95%CI: 1.34 - 1.83; p-value<0.001), absent sleepiness (PR:1.59; 95%CI: 1.32-1.91; p-value<0.001), male sex (PR: 1.21; 95%CI: 1.05-1.39; p-value 0.006), working (PR:1.14), having family responsibilities (PR: 1.36; 95%CI: 1.09-1.70; p-value 0.005) and spending more than 6 hours studying (PR: 1.35; 95%CI: 1.17-1.54; p-value<0.001).
UNASSIGNED: 4 out of 10 students presented high levels of resilience. The development of resilience depended on multiple individual and sociodemographic factors. These findings are important to support universities in developing resilience-building measures and strategies that can be implemented to mitigate the adverse pandemic event.

UNASSIGNED: To assess the daily relationship between prior-night total sleep time (TST) and next-day, afternoon sleep propensity among firefighters operating from two popular fire department shift schedules.
UNASSIGNED: Dataset included 22 firefighters (24/48 shift schedule) and 20 firefighters (48/96 shift schedule). Daily TST was assessed using actigraphy and daily sleep propensity was assessed using the Epworth Sleepiness Scale (ESS), completed every afternoon.
UNASSIGNED: Separate one-way repeated measures ANOVA indicated statistically significant differences among daily sleep propensity within each shift schedule. Separate Pearson product moment correlations indicated moderate relationships between prior-night TST and next-day, afternoon sleep propensity.
UNASSIGNED: When firefighters slept less, sleep propensity the following day increased. Least TSTs occurred on nights prior to commuting suggesting firefighters likely begin shifts without sufficient sleep and drive home without sufficient sleep, then experience greatest sleep propensity.

BACKGROUND: This study aimed to investigate the relationship between obstructive sleep apnea (OSA), circadian rhythms, and individual sleep-wake preferences, as measured by chronotype, and to assess the association between circadian clock gene expression and subjective sleep-related variables.
METHODS: A total of 184 individuals were recruited, underwent polysomnography (PSG), and completed questionnaires including a chronotype questionnaire (CQ), insomnia severity index (ISI), and Epworth sleepiness scale (ESS). Blood samples were collected in the evening before and morning after PSG. Gene expression analysis included BMAL1, CLOCK, PER1, CRY1, NPAS2, and NR1D1.
RESULTS: In the OSA group, the subjective amplitude (AM score of CQ) positively correlated with all circadian clock genes in the morning (R ≥ 0.230 and p < 0.05 for each one), while the morningness-eveningness (ME score of CQ) was only associated with the evening BMAL1 level (R = 0.192; p = 0.044). In healthy controls, insomnia severity correlated with evening expression of BMAL1, PER1, and CRY1.
CONCLUSIONS: The findings highlight the complex interplay between OSA, circadian rhythms, and sleep-related variables, suggesting potential determinants of morning chronotype in OSA and implicating disrupted circadian clock function in subjective feelings of energy throughout the day. Further research is warranted to elucidate underlying mechanisms and guide personalized management strategies.

OBJECTIVE: We investigated the difference in sleep inertia between shift workers (SWs) and non-shift workers (NSWs) and the effects of depressive symptoms, sleepiness, insomnia, and chronotype on sleep inertia in SWs and NSWs.
METHODS: Altogether, 4,561 SWs (2,142 men and 2,419 women, aged 36.99±9.84 years) and 2,093 NSWs (999 men and 1,094 women, aged 37.80±9.73 years) participated in the current study. All participants completed the Sleep Inertia Questionnaire (SIQ), Epidemiological Studies Depression Scale (CESD), Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), and Morningness-Eveningness Questionnaire (MEQ) through an online survey.
RESULTS: SWs reported higher SIQ scores than NSWs after controlling for CESD, ESS, ISI, or MEQ. The CESD, ESS, ISI, and MEQ predicted SIQ in both SWs and NSWs. The effects of CESD and MEQ on SIQ were stronger in SWs and NSWs, respectively. The indirect effects of CESD and MEQ on SIQ via ESS were significantly moderated by work schedules.
CONCLUSIONS: SWs showed higher sleep inertia than NSWs. The effect of chronotypes on sleep inertia was more prominent in NSWs than in SWs. However, the effect of depressive symptoms on sleep inertia was more prominent in SWs than in NSWs. Moreover, the effect of depressive symptoms or chronotypes on sleep inertia was mediated by sleepiness, and such indirect effects were significantly different among the participants stratified by work schedules.

UNASSIGNED: In this study we aimed to investigate the effects of incorporating Swedish-style fika (coffee) breaks into the didactic schedule of emergency medicine residents on their sleepiness levels during didactic sessions. Fika is a Swedish tradition that involves a deliberate decision to take a break during the workday and usually involves pastries and coffee. We used the Karolinska Sleepiness Scale to assess changes in sleepiness levels before and after the implementation of fika breaks.
UNASSIGNED: The study design involved a randomized crossover trial approach, with data collected from emergency medicine residents over a specific period. This approach was done to minimize confounding and to be statistically efficient.
UNASSIGNED: Results revealed the average sleepiness scale was 4.6 and 5.5 on fika and control days, respectively (P = 0.004).
UNASSIGNED: Integration of fika breaks positively influenced sleepiness levels, thus potentially enhancing the educational experience during residency didactics.

Obesity is a global health concern that has been increasing over the years, and it is associated with several pathophysiological changes affecting the respiratory system, including alveolar hypoventilation. Obesity hypoventilation syndrome (OHS) is one of the six subtypes of sleep-hypoventilation disorders. It is defined as the presence of obesity, chronic alveolar hypoventilation leading to daytime hypercapnia and hypoxia, and sleep-disordered breathing. The existence of a sleep disorder is one of the characteristics that patients with OHS present. Among them, 90% of patients have obstructive sleep apnea (OSA), and the remaining 10% of patients with OHS have non-obstructive sleep hypoventilation without OSA or with mild OSA. This review aims to provide a comprehensive understanding of the epidemiological and pathophysiological impact of OHS and to highlight its clinical features, prognosis, and severity, as well as the available treatment options.

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be \'objective\' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

OBJECTIVE: Menopause is associated with nighttime sleep fragmentation, declining estradiol, and impaired cognition. In a model of pharmacologically induced estradiol suppression mimicking menopause, we examined the impact of menopause-pattern sleep fragmentation on daytime neurobehavioral performance and sleepiness in premenopausal women.
METHODS: Twenty premenopausal women completed two five-night inpatient studies in the mid-to-late follicular phase (estrogenized) and after pharmacological estradiol suppression (hypo-estrogenized). During each study, participants had an uninterrupted 8-hour sleep opportunity for two nights, followed by three nights where sleep was experimentally fragmented to mimic menopause-pattern sleep disturbance, and during which the sleep opportunity was extended to prevent shortening of the sleep duration. Neurobehavioral performance and subjective sleepiness were measured using the Psychomotor Vigilance Task and Karolinska Sleepiness Scale (KSS).
RESULTS: Compared to unfragmented sleep, sleep fragmentation increased attentional lapses (+ 0.6 lapses, p < .05), slowed reaction time (+ 9.4 milliseconds, p < .01), and increased daytime sleepiness (+ 0.5 KSS score, p < .001). Estradiol suppression increased attentional lapses (+ 0.8; p < .001) and reaction time (+ 12.3, p < .01) but did not significantly affect daytime sleepiness. The effect of sleep fragmentation on neurobehavioral performance differed by estradiol state, such that the adverse effects of sleep fragmentation on attentional lapses (+ 0.9, trend p = .06) and reaction time (+ 15, p < .05) were observed only when estrogenized.
CONCLUSIONS: Menopause-pattern sleep fragmentation and estradiol suppression worsened neurobehavioral performance and daytime sleepiness, even while sleep duration was not reduced. The adverse effects of sleep fragmentation in the context of an adequate sleep duration highlight the importance of sleep continuity as a vital aspect of good sleep health.

OBJECTIVE: Persisting neurological symptoms after COVID-19 affect up to 10% of patients and can manifest in fatigue and cognitive complaints. Based on recent evidence, we evaluated whether cerebral hemodynamic changes contribute to post-COVID syndrome (PCS).
METHODS: Using resting-state functional magnetic resonance imaging, we investigated brain perfusion and oxygen level estimates in 47 patients (44.4 ± 11.6 years; F:M = 38:9) and 47 individually matched healthy control participants. Group differences were calculated using two-sample t-tests. Multivariable linear regression was used for associations of each regional perfusion and oxygen level measure with cognition and sleepiness measures. Exploratory hazard ratios were calculated for each brain metric with clinical measures.
RESULTS: Patients presented with high levels of fatigue (79%) and daytime sleepiness (45%). We found widespread decreased brain oxygen levels, most evident in the white matter (false discovery rate adjusted-p-value (p-FDR) = 0.038) and cortical grey matter (p-FDR = 0.015). Brain perfusion did not differ between patients and healthy participants. However, delayed patient caudate nucleus perfusion was associated with better executive function (p-FDR = 0.008). Delayed perfusion in the cortical grey matter and hippocampus were associated with a reduced risk of daytime sleepiness (hazard ratio (HR) = 0.07, p = 0.037 and HR = 0.06, p = 0.034). Decreased putamen oxygen levels were associated with a reduced risk of poor cognitive outcome (HR = 0.22, p = 0.019). Meanwhile, lower thalamic oxygen levels were associated with a higher risk of cognitive fatigue (HR = 6.29, p = 0.017).
CONCLUSIONS: Our findings of lower regional brain blood oxygen levels suggest increased cerebral metabolism in PCS, which potentially holds a compensatory function. These hemodynamic changes were related to symptom severity, possibly representing metabolic adaptations.