OBJECTIVE: We investigated the therapeutic effects of exercise in patients with obstructive sleep apnea (OSA), aiming to identify the subgroups that benefit the most and determine the optimal exercise protocol.
METHODS: Major databases were searched for randomized controlled trials involving patients with OSA performing aerobic exercise and/or resistance training. The investigated outcomes included apnea-hypopnea index (AHI), Epworth Sleepiness Scale (ESS), body mass index (BMI), and peak oxygen consumption during exercise (VO2peak). The pre- and postintervention unstandardized mean difference (USMD) of these parameters was compared between the exercise and control groups.
RESULTS: Twelve studies involving 526 patients were included. Exercise training significantly reduced AHI (USMD = -7.08 events/hour, 95% confidence interval [CI]: -9.98 to -4.17, p < 0.00001), ESS (USMD = -2.37, CI: -3.21 to -1.54, p < 0.00001), and BMI (USMD = -0.72 kg/m2, CI: -1.22 to -0.22, p = 0.005) and enhanced VO2peak (USMD = 3.46 mL/kg/min, CI: 1.20 to 5.71, p = 0.003). Subgroup analyses revealed that in continuous positive airway pressure (CPAP)-adherent patients, exercise significantly improved VO2peak but did not reduce AHI and ESS. A trend was observed that combining resistance training with aerobic exercise resulted in greater AHI reduction and VO2peak enhancement. Notably, exercise improved AHI, ESS, BMI, and VO2peak regardless of the baseline AHI or BMI.
CONCLUSIONS: Exercise, including resistance and aerobic training, should be part of treatment for patients with OSA of all severities, regardless of obesity status, and even for those who are already under CPAP.
BACKGROUND: The study protocol was registered with the PROSPERO database (#CRD42023423527).

Bus driver sleepiness is commonplace but often goes unreported within the industry. Whilst past research has begun to shed a light on the prevalence, potential causes, and consequences of bus driver sleepiness, this is often done using self-report methods. This is the first study to investigate sleepiness amongst city bus drivers on-road using a live bus route with drivers\' regular schedules. A total of 16 participants completed two drives of their regular bus route once during an early morning shift and once during a daytime shift whilst physiological and self-report measures of sleep and stress were taken. Prior to these drives, drivers recorded their sleep in a diary and wore an actigraph to obtain objective sleep measures. Results showed that most drivers did not obtain sufficient sleep prior to early morning shifts, and often did not obtain as much sleep as they would need in order to feel rested before work. Sleepiness and stress were observed in both shifts. During early morning shifts sleepiness was likely a result of working during circadian lows and not obtaining enough sleep prior to the shift. In contrast, sleepiness during the daytime shift was likely a result of completing a highly demanding task in complex traffic which not only contributed to fatigue, but also led to increased levels of stress. As well as demonstrating the prevalence of sleepiness amongst bus drivers, these findings show that the causes of sleepiness can be multifaceted and often come about due to a combination of work and personal factors. In addition, the experience of sleepiness is not the same for all drivers, with individual differences in the experience of sleepiness playing a large role. These differences highlight the need for individualised interventions which should be considered by policymakers alongside the combination of causal factors within a larger systems approach.

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.

OBJECTIVE: Shiftwork is associated with cognitive impairment and reduced sleep time and quality, largely due to circadian misalignment. This study tested if circadian-informed lighting could improve cognitive performance and sleep during simulated night shifts versus dim control lighting.
METHODS: Nineteen healthy participants (Mean±SD 29±10 years, 12 males, 7 females) were recruited to a laboratory study consisting of two counterbalanced 8-day lighting conditions (order randomized) 1-month apart: 1) control lighting condition- dim, blue-depleted and 2) circadian-informed lighting condition- blue-enriched and blue-depleted where appropriate. Participants underwent an adaptation night (22:00h - 07:00h), then four nights of simulated nightwork (cognitive testing battery of nine tasks, 00:00h - 08:00h) and sleep during the day (10:00h - 19:00h). Psychomotor vigilance task (PVT) lapses, Karolinska Sleepiness Scale (KSS) scores, and polysomnography-derived sleep outcomes were compared between conditions and across days using mixed models.
RESULTS: Significant condition-by-day-by-time of task interaction effects were found for PVT lapses, median reaction time, and reaction speed, with ~50% fewer lapses by the end of simulated shiftwork with circadian-informed lighting versus control (mean±SD 7.4±5.0 vs. 15.6±6.1). KSS was lower around the nightshift midpoints on days 6 and 7 with circadian versus control lighting. Participants slept 52 minutes longer [95% CIs: 27.5, 76.5 mins] by Day 7 with circadian-informed versus control lighting, p<0.001. Effects were inconsistent on other performance tasks.
CONCLUSIONS: Circadian-informed lighting improved sleep, sleepiness, and vigilance compared to control lighting. These findings support the potential for lighting interventions to improve sleep and vigilance in night shift workers chronically exposed to dim lighting.

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.

BACKGROUND: While sleep disorders are implicated in atrial fibrillation (AF), the interplay of physiologic alterations and symptoms remains unclear. Sleep-based phenotypes can account for this complexity and translate to actionable approaches to identify at-risk patients and therapeutic interventions.
OBJECTIVE: This study hypothesized discrete phenotypes of symptoms and polysomnography (PSG)-based data differ in relation to incident AF.
METHODS: Data from the STARLIT (sleep Signals, Testing, And Reports LInked to patient Traits) registry on Cleveland Clinic patients (≥18 years of age) who underwent PSG from November 27, 2004, to December 30,2015, were retrospectively examined. Phenotypes were identified using latent class analysis of symptoms and PSG-based measures of sleep-disordered breathing and sleep architecture. Phenotypes were included as the primary predictor in a multivariable-adjusted Cox proportional hazard models for incident AF.
RESULTS: In our cohort (N = 43,433, age 51.8 ± 14.5 years, 51.9% male, 74.9% White), 7.3% (n = 3,166) had baseline AF. Over a 7.6- ± 3.4-year follow-up period, 8.9% (n = 3,595) developed incident AF. Five phenotypes were identified. The hypoxia subtype (n = 3,245) had 48% increased incident AF (HR: 1.48; 95% CI: 1.34-1.64), the apneas + arousals subtype (n = 4,592) had 22% increased incident AF (HR: 1.22; 95% CI: 1.10-1.35), and the short sleep + nonrapid eye movement subtype (n = 6,126) had 11% increased incident AF (HR: 1.11; 95% CI: 1.01-1.22) compared with long sleep + rapid eye movement (n = 26,809), the reference group. The hypopneas subtype (n = 2,661) did not differ from reference (HR: 0.89; 95% CI: 0.77-1.03).
CONCLUSIONS: Consistent with prior evidence supporting hypoxia as an AF driver and cardiac risk of the sleepy phenotype, this constellation of symptoms and physiologic alterations illustrates vulnerability for AF development, providing potential value in enhancing our understanding of integrated sleep-specific symptoms and physiologic risk of atrial arrhythmogenesis.

Insomnia, the most prevalent sleep disorder, is commonly associated with other mental and somatic disorders, making it a significant health concern. It is characterized by nighttime symptoms and daytime dysfunction, with sleepiness being a potential criterion for the latter. Sleepiness is a normal physiological state that is typically experienced near usual bedtime, in normal circumstances. In insomnia, it seems somewhat logical the idea that there is significant daytime sleepiness. However, the topic has been the subject of various discussions in sleep medicine, with studies yielding contradictory and inconsistent results. In this article, we aim to critically examine daytime sleepiness in individuals with insomnia disorder and propose an alternative approach to addressing it, both in clinical practice and research settings. It is crucial to further investigate the role of daytime sleepiness in insomnia, particularly by focusing on sleepiness perception as a more relevant dimension to explore in majority of patients. It is plausible that certain insomnia phenotypes are objectively sleepy during the day, but more studies are necessary, particularly with well-defined clinical samples. The implications of assessing sleepiness perception in insomnia for clinical practice are discussed, and new avenues for research are suggested.

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.

Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected and correlate most strongly with drowsiness. This study examines the variations and importance of various facial areas and proposes an approach for detecting driver drowsiness. Twenty participants underwent tests in a driving simulator, and temperature changes in various facial regions were measured. The random forest method was employed to evaluate the importance of each facial region. The results revealed that temperature changes in the nasal area exhibited the highest value, while the eyes had the most correlated changes with drowsiness. Furthermore, drowsiness was classified with an accuracy of 88 % utilizing thermal variations in the facial region identified as the most important regions by the random forest feature importance model. These findings provide a comprehensive overview of facial thermal imaging for detecting driver drowsiness and introduce eye temperature as a novel and effective measure for investigating cognitive activities.