Search Results (16)

Hypersomnia may be classified as primary or secondary, with secondary hypersomnia arising from a variety of underlying causes. Thus, according to ICSD3-TR classification, the diagnosis of idiopathic hypersomnia (IH) is established based on (1) excessive daytime sleepiness (EDS); (2) electrophysiological findings including either a mean sleep latency of less than 8 min on the Multiple Sleep Latency Test (MSLT) or increased total sleep (≥11 h) on 24 h polysomnography; and (3) systematic elimination of other potential etiologies, including sleep deprivation, substances, and medical, psychiatric (notably mood disorders), or sleep disorders. Nevertheless, the clinical heterogeneity observed in IH fuels an ongoing debate, reflecting the limited understanding of its underlying pathophysiological mechanisms. This report describes the case of a patient presenting with a clinical and polysomnographic phenotype of IH (MSLT < 8 min). A comprehensive psychopathological evaluation was performed to explore the possibility of secondary hypersomnia, which revealed features consistent with complex post-traumatic stress disorder (c-PTSD). Psychotherapy focused on c-PTSD was administered with positive and objective results in hypersomnolence/EDS. This clinical improvement suggests a potential relationship between psychological trauma and hypersomnia, a connection that is rarely described in the literature and warrants further investigation. This case highlights the need for a comprehensive assessment of secondary factors, particularly complex trauma, even in the presence of a clinical and polysomnographic phenotype consistent with IH. Full article

Background/Objectives: There is limited data on well-documented comorbidities with polysomnography (PSG)/multiple sleep latency test (MSLT) findings in idiopathic hypersomnia (IH). We aimed to characterize the clinical, PSG/MSLT characteristics of IH patients in our health network. Methods: We reviewed charts of all IH cases between 2000 and 2023, extracting clinical features, comorbidities, and PSG/MSLT findings. Results: One hundred forty-two patients (83.80% female) with IH were included. Compared to those without mood disorders, both major depressive disorder (MDD) and anxiety patients were older at onset (27.10 ± 8.32 and 26.76 ± 8.40 versus 23.23 ± 6.94 and 24.05 ± 7.31 years; p = 0.003 and p = 0.042) and had lower ESS (15 versus 19; 15.67 versus 17.75; p < 0.0001), more disrupted sleep (28 (36.36%) versus 8 (12.31%); p = 0.001; 24 (35.82%) versus 12 (16%); p = 0.007), and less sleep inertia (30 (38.96%) versus 38 (58.46%); p = 0.021; 26 (38.81%) versus 42 (56%); p = 0.04). Fifteen patients with dysautonomia disorders presented at an earlier age (21.80 ± 6.60 versus 25.75 ± 8, p = 0.0682). On MSLT, MDD, anxiety, and dysautonomia patients had longer sleep latencies than the non-affected counterparts (6.40 (5.40–7.60) minutes versus 3.60 (2.60–5.40) min., <0.0001; 6.20 (5.20–7.40) versus 4 (2.60–6.40) minutes; p < 0.0001; 7.40 (6–7.80) versus 5.40 (3–7); p = 0.008). MDD and anxiety cases had fewer sleep onset REM periods (7 (9.09%) versus 16 (24.62%), p = 0.0124 and 6 (8.96%) versus 17 (22.67%), p = 0.0388) compared to those not affected by these disorders. Conclusions: Our study highlights the importance of recognizing mood disorders and dysautonomia in patients diagnosed with IH. Further research may elucidate management strategies for these patients. Full article

Background/Objectives: This study aimed to investigate the effect of age at symptom onset on rapid eye movement (REM) sleep latency and sleep-onset REM period (SOREMP) distribution in multiple sleep latency tests (MSLTs) in patients with narcolepsy. Methods: This was a retrospective multicenter chart review of 135 newly diagnosed drug-naïve patients with narcolepsy who underwent MSLT and fulfilled the diagnostic criteria for narcolepsy. The age at onset was defined as the first occurrence of excessive daytime sleepiness or cataplexy. We investigated sleep onset latency, REM sleep latency, and the presence of SORMEP in each nap trial of the MSLT. The clinical, polysomnography, and MSLT findings were compared between the early- and late-onset groups. Correlation and linear regression analyses were used to assess the effect of age at onset as a continuous variable, and survival analyses confirmed its impact on the MSLT parameters. Results: The mean age at onset was 18.3 ± 8.8 years. Patients with early onset had a higher rate of SOREMPs than late-onset patients in the first MSLT nap (81.9% vs. 63.3%, p = 0.031). However, the severity of the narcolepsy symptoms did not differ between the groups. In linear regression analysis, age at onset was significantly associated with MSLT REM sleep latency (β = 0.049, p = 0.033) after adjusting for confounders. Survival analysis confirmed that an early onset of narcolepsy was associated with a higher probability of SOREMPs in the first MSLT nap (hazard ratio 0.955, p = 0.001). Conclusions: A younger age at narcolepsy onset was associated with shorter REM sleep latency and higher SOREMP probability in MSLT. These findings indicate that the early onset of narcolepsy may be linked to greater disease severity in terms of REM sleep dysregulation. Full article

Background/Objectives: Poor sleep quality is a prevalent health concern among older adults, impacting cognitive and physical functions. This study aimed to determine the association between sleep quality and self-reported health status among middle-aged and older adults in northern Taiwan. Methods: This cross-sectional study, conducted from April to October 2017, assessed participants using the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) with a cut-off of 5; scores above 5 indicated poor sleep quality. The self-reported health status was evaluated using a questionnaire. Statistical analyses included the chi-squared test, one-way ANOVA, Cochran–Armitage trend test, and multiple logistic regression models. Results: This study included 850 adults (243 males and 607 females). The participants were grouped according to their self-reported health status as follows: good (n = 278), fair (n = 499), and poor (n = 73). Poor health status was associated with worse sleep quality components, including sleep latency, efficiency, disturbances, medication use, and daytime dysfunction (p for trend < 0.001). The multiple logistic regression analysis showed higher dissatisfaction with health status among the participants with a CPSQI score of >5 (odds ratio, 4.12; 95% CI 2.26–7.50; p < 0.001). A poor health status was reported by 19.51% of the participants sleeping < 5 h, compared to 6.97% of the participants sleeping 5–6 h, 6.60% of the participants sleeping 6–7 h, and 6.34% of the participants sleeping > 7 h, showing a trend toward a shorter sleep duration (p for trend = 0.002). Conclusions: Our study findings indicate that a poor sleep quality and short sleep duration were independent risk factors for poor self-reported health status in middle-aged and older adults in Taiwan. Addressing sleep quality is crucial for implementing preventive health measures in this demographic group. Full article

Background/Objectives: Narcolepsy was first described in the late 19th century, and in the current decade, narcolepsy patients are reaching their senior years. Little is known about the evolution of clinical features, the management of narcolepsy medications, and the development of comorbid conditions. We aimed to present the clinical characteristics, comorbidities, and therapeutic choices of seniors with narcolepsy. Methods: We extracted 21 charts of patients older than 65 with a diagnosis of narcolepsy according to the International Classification of Sleep Disorders Third Edition. We reviewed and analyzed all clinical and available polysomnographic data. Results: A total of 21 patients (median age 69 years. 67.0–71.0 interquartile range IQR; 71% female) were included. Three (14.3%) had type I and 18 (85.7%) had type II narcolepsy. The average age at symptom onset was 23 years (IQR 19.5–27.5). Diagnosis was made at an average age of 41 years (IQR 33–45), between 1990 and 2002. Median time from onset to diagnosis was 13.7 years (IQR 9.5–19). The most prevalent cardiovascular/metabolic comorbidity was hypertension (57.1%). All patients were historically using narcolepsy medications. Fewer patients were currently on wake-promoting agents (85.7%), with over half on modafinil (55.6%). None currently reported the need to nap during the daytime. Conclusions: Narcolepsy is a lifelong, but not progressive disorder, that has yet to be well-characterized in the senior population. A few seniors appear to outgrow the disorder and to no longer need wake-promoting agents. It is important to consider cardiometabolic comorbidities in the management of narcolepsy in this population. Geriatricians should be educated on narcolepsy with specific programs for these seniors. Full article

Sleep–wake disturbances are common in post-COVID-19 syndrome but lack extensive objective characterization. This study evaluated sleep–wake patterns in 31 patients with post-COVID-19 syndrome referred for fatigue and excessive daytime sleepiness (EDS). Assessments included questionnaires (the fatigue severity scale, the Epworth sleepiness scale, and the Beck Depression Index-II), video polysomnography (V-PSG), the multiple sleep latency test (MSLT, n = 15), and actigraphy (n = 29). Patients (70% female, mean age 45 years) had mostly mild acute SARS-CoV-2 infections and were assessed a median of 31 weeks post-infection. Fatigue (fatigue severity scale, median 6.33), sleepiness (the Epworth sleepiness scale, median 15), and depression (Beck depression inventory-II, median 20) scores were elevated. V-PSG showed moderate sleep apnea in 35.5%, increased arousal index in 77.4%, and median sleep stage percentages of NREM1 (12%), NREM2 (37%), NREM3 (19%), and REM (15.8%). MSLT revealed only 13.3% with sleep latencies under 8 min and no sleep-onset REM periods. Actigraphy indicated increased inactivity index in 96.6%, with high variability in time in bed. These findings highlight a polysomnographic and actigraphic profile of increased arousal and clinophilia, alongside moderate sleep apnea and limited objective sleepiness on MSLT. Addressing these multifactorial sleep disturbances is crucial in managing post-COVID-19 syndrome. Full article

Background. No device is yet available to effectively capture the attentional repercussions of hypersomnolence (HYP). The present study aimed to compare attentional performance of children with HYP, attention deficit hyperactivity disorder (ADHD), and controls using behavioral and electrophysiological (EEG) markers, and to assess their relationship with conventional sleepiness measurements. Methods. Children with HYP underwent a multiple sleep latency test (MSLT) and completed the adapted Epworth sleepiness scale (AESS). Along with age-matched children with ADHD, they were submitted to a resting EEG followed by the Bron–Lyon Attention Stability Test (BLAST). The control group only performed the BLAST. Multivariate models compared reaction time (RT), error percentage, BLAST-Intensity, BLAST-Stability, theta activity, and theta/beta ratio between groups. Correlations between these measures and conventional sleepiness measurements were conducted in children with HYP. Results. Children with HYP had lower RT and BLAST-Stability than controls but showed no significant difference in BLAST/EEG markers compared to children with ADHD. The AESS was positively correlated with the percentage of errors and negatively with BLAST-Intensity. Conclusions. Children with HYP showed impulsivity and attention fluctuations, without difference from children with ADHD for BLAST/EEG markers. The BLAST–EEG protocol could be relevant for the objective assessment of attentional fluctuations related to hypersomnolence. Full article

Individuals with internalizing conditions such as depression or anxiety are at risk of sleep difficulties. Social–ecological models of sleep health propose factors at the individual (e.g., mental health) and neighborhood (e.g., crime risk) levels that contribute to sleep difficulties. However, these relationships have been under-researched in terms of internalizing conditions. Therefore, the current study comprised participants diagnosed with major depression (n = 24) or social anxiety (n = 35). Sleep measures included actigraphic variables (i.e., total sleep time, waking after sleep onset, sleep onset latency) and subjective sleep quality. Geocoding was used to assess nationally-normed crime risk exposure at the person level (e.g., murder, assault) and property level (e.g., robbery, burglary). Analyses consisted of independent t-tests to evaluate potential differences between diagnostic groups. To examine relationships, multiple regressions were used with internalizing symptoms, crime risk, and age as independent variables and sleep measures as the dependent variable. The t-test results revealed that groups differed in symptoms and age but not sleep or neighborhood crime. Regression results revealed crime risk positively corresponded with sleep onset latency but no other sleep measures. Also, only depression positively corresponded with total sleep time. Preliminary findings suggest exposure to crime and depression relate differentially to facets of sleep in individuals with internalizing conditions. Full article

Two commercial multisport activity trackers (Garmin Forerunner 945 and Polar Ignite) and the accelerometer ActiGraph GT9X were evaluated in measuring vital data, sleep stages and sleep/wake patterns against polysomnography (PSG). Forty-nine adult patients with suspected sleep disorders (30 males/19 females) completed a one-night PSG sleep examination followed by a multiple sleep latency test (MSLT). Sleep parameters, time in bed (TIB), total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), awake time (WASO + SOL), sleep stages (light, deep, REM sleep) and the number of sleep cycles were compared. Both commercial trackers showed high accuracy in measuring vital data (HR, HRV, SpO₂, respiratory rate), r > 0.92. For TIB and TST, all three trackers showed medium to high correlation, r > 0.42. Garmin had significant overestimation of TST, with MAE of 84.63 min and MAPE of 25.32%. Polar also had an overestimation of TST, with MAE of 45.08 min and MAPE of 13.80%. ActiGraph GT9X results were inconspicuous. The trackers significantly underestimated awake times (WASO + SOL) with weak correlation, r = 0.11–0.57. The highest MAE was 50.35 min and the highest MAPE was 83.02% for WASO for Garmin and ActiGraph GT9X; Polar had the highest MAE of 21.17 min and the highest MAPE of 141.61% for SOL. Garmin showed significant deviations for sleep stages (p < 0.045), while Polar only showed significant deviations for sleep cycle (p = 0.000), r < 0.50. Garmin and Polar overestimated light sleep and underestimated deep sleep, Garmin significantly, with MAE up to 64.94 min and MAPE up to 116.50%. Both commercial trackers Garmin and Polar did not detect any daytime sleep at all during the MSLT test. The use of the multisport activity trackers for sleep analysis can only be recommended for general daily use and for research purposes. If precise data on sleep stages and parameters are required, their use is limited. The accuracy of the vital data measurement was adequate. Further studies are needed to evaluate their use for medical purposes, inside and outside of the sleep laboratory. The accelerometer ActiGraph GT9X showed overall suitable accuracy in detecting sleep/wake patterns. Full article

Light therapy is used to treat sleep and circadian rhythm disorders, yet there are limited studies on whether light therapy impacts electroencephalographic (EEG) activity during sleep. Therefore, we aimed to provide an overview of research studies that examined the effects of light therapy on sleep macro- and micro-architecture in populations with sleep and circadian rhythm disorders. We searched for randomized controlled trials that used light therapy and included EEG sleep measures using MEDLINE, PubMed, CINAHL, PsycINFO and Cochrane Central Register of Controlled Trials databases. Five articles met the inclusion criteria of patients with either insomnia or delayed sleep–wake phase disorder (DSWPD). These trials reported sleep macro-architecture outcomes using EEG or polysomnography. Three insomnia trials showed no effect of the timing or intensity of light therapy on total sleep time, wake after sleep onset, sleep efficiency and sleep stage duration compared to controls. Only one insomnia trial reported significantly higher sleep efficiency after evening light therapy (>4000 lx between 21:00–23:00 h) compared with afternoon light therapy (>4000 lx between 15:00–17:00 h). In the only DSWPD trial, six multiple sleep latency tests were conducted across the day (09:00 and 19:00 h) and bright light (2500 lx) significantly lengthened sleep latency in the morning (09:00 and 11:00 h) compared to control light (300 lx). None of the five trials reported any sleep micro-architecture measures. Overall, there was limited research about the effect of light therapy on EEG sleep measures, and studies were confined to patients with insomnia and DSWPD only. More research is needed to better understand whether lighting interventions in clinical populations affect sleep macro- and micro-architecture and objective sleep timing and quality. Full article

Married female nurses experience work–family conflict (WFC) as they manage excessive work and various working-hour types while rearing children and tending household chores, and as a result, they continuously constantly deliberate over quitting their job or moving to a different workplace. Married nurses were found to have shorter sleep duration and sleep latency compared to single nurses, and high job stress not only hinders their family life but also causes sleep problems. Depression is a classic negative emotion experienced by married working women who must manage both work and family. This study aims to examine WFC in married female nurses and investigate its predictors, namely depression and sleep quality. A total of 229 married female nurses completed a Google questionnaire link consisting of the Work–Family Conflict Scale, Sleep-Quality Scale, and the Center for Epidemiologic Studies Depression Scale (CES-D). Data were analyzed by descriptive statistics, t-test, ANOVA, LSD post hoc test, Pearson’s correlation coefficients, and multiple regression using the SPSS/WIN 26.0 program. The average WFC score was 4.84 ± 1.12 (range 1–7); WFC showed a statistical difference according to a stage of the lifecycle (F = 7.12, p = 0.001) and perceived health (F = 12.01, p < 0.001). WFC was low among those in the non-parenthood stage of the lifecycle (β = −0.26, p < 0.001), those with good (β = −0.18, p = 0.011) or moderate perceived health (β = −0.15, p = 0.023), and those without turnover intention (β = −0.13, p = 0.016). On the other hand, WFC was high among those who were extremely dissatisfied with their job (β = 0.16, p = 0.008) and those who had a high level of depression (β = 0.22, p = 0.002); these variables explained 20.2% of WFC (F = 7.663, p < 0.001). Based on these results, subsequent studies should develop and implement coping programs that help reduce WFC and improve depression and sleep quality in married female nurses. Full article

(1) Background—Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a multifaceted illness characterized by profound and persistent fatigue unrelieved by rest along with a range of other debilitating symptoms. Experiences of unrefreshing and disturbed sleep are frequently described by ME/CFS patients. This is the first systematic review assessing sleep characteristics in ME/CFS. The aim of this review is to determine whether there are clinical characteristics of sleep in ME/CFS patients compared to healthy controls using objective measures such as polysomnography and multiple sleep latency testing. (2) Methods—the following databases—Pubmed, Embase, Medline (EBSCO host) and Web of Science, were systematically searched for journal articles published between January 1994 to 19 February 2021. Articles that referred to polysomnography or multiple sleep latency testing and ME/CFS patients were selected, and further refined through use of specific inclusion and exclusion criteria. Quality and bias were measured using the Joanna Briggs Institute checklist. (3) Results—twenty observational studies were included in this review. The studies investigated objective measures of sleep quality in ME/CFS. Subjective measures including perceived sleep quality and other quality of life factors were also described. (4) Conclusions—Many of the parameters measured including slow- wave sleep, apnea- hypopnea index, spectral activity and multiple sleep latency testing were inconsistent across the studies. The available research on sleep quality in ME/CFS was also limited by recruitment decisions, confounding factors, small sample sizes and non-replicated findings. Future well-designed studies are required to understand sleep quality in ME/CFS patients. Full article

High cognitive functioning could be a protective factor for school difficulties, behavioral and mood impairments in children with narcolepsy. To investigate this factor, we studied the intellectual abilities of 74 children with narcolepsy (43 boys, 11.7 years old at diagnosis, 91% of cataplexies, 64% obese, 100% HLA positive for DR-DQB1*06:02). All children underwent a one-night polysomnography followed by Multiple Sleep Latency Tests, an evaluation of intelligence quotient (IQ), and filled standardized questionnaires. Thirty-eight percent had high potentialities (HP defined by IQ > 130) and 48% had school difficulties. Using non-parametric tests, we found that HP children reported less difficulties at school and tended to have less impulsivity, conduct, and learning disorders than those without HP. They also tended to be less obese and had less desaturation. Using a multivariate regression analysis, we found an association between the REM sleep percentage and the IQ. REM sleep could be involved in the dynamic changes contributing to the equilibrium of intellectual functioning. This study highlights that despite their frequent school difficulties, narcolepsy per se is unlikely to be a cause of intellectual disability in children. Prompt diagnosis and management of comorbidities such as obesity and obstructive sleep apnea (OSA) could improve cognitive and school performances in these children. Full article

Within the Internet of Things (IoT) and blockchain research, there is a growing interest in decentralizing health monitoring systems, to provide improved privacy to patients, without relying on trusted third parties for handling patients’ sensitive health data. With public blockchain deployments being severely limited in their scalability, and inherently having latency in transaction processing, there is room for researching and developing new techniques to leverage the security features of blockchains within healthcare applications. This paper presents a solution for patients to share their biomedical data with their doctors without their data being handled by trusted third party entities. The solution is built on the Ethereum blockchain as a medium for negotiating and record-keeping, along with Tor for delivering data from patients to doctors. To highlight the applicability of the solution in various health monitoring scenarios, we have considered three use-cases, namely cardiac monitoring, sleep apnoea testing, and EEG following epileptic seizures. Following the discussion about the use cases, the paper outlines a security analysis performed on the proposed solution, based on multiple attack scenarios. Finally, the paper presents and discusses a performance evaluation in terms of data delivery time in comparison to existing centralized and decentralized solutions. Full article

Sleep quality has been directly linked to cognitive function, quality of life, and a variety of serious diseases across many clinical domains. Standard methods for assessing sleep involve overnight studies in hospital settings, which are uncomfortable, expensive, not representative of real sleep, and difficult to conduct on a large scale. Recently, numerous commercial digital devices have been developed that record physiological data, such as movement, heart rate, and respiratory rate, which can act as a proxy for sleep quality in lieu of standard electroencephalogram recording equipment. The sleep-related output metrics from these devices include sleep staging and total sleep duration and are derived via proprietary algorithms that utilize a variety of these physiological recordings. Each device company makes different claims of accuracy and measures different features of sleep quality, and it is still unknown how well these devices correlate with one another and perform in a research setting. In this pilot study of 21 participants, we investigated whether sleep metric outputs from self-reported sleep metrics (SRSMs) and four sensors, specifically Fitbit Surge (a smart watch), Withings Aura (a sensor pad that is placed under a mattress), Hexoskin (a smart shirt), and Oura Ring (a smart ring), were related to known cognitive and psychological metrics, including the n-back test and Pittsburgh Sleep Quality Index (PSQI). We analyzed correlation between multiple device-related sleep metrics. Furthermore, we investigated relationships between these sleep metrics and cognitive scores across different timepoints and SRSM through univariate linear regressions. We found that correlations for sleep metrics between the devices across the sleep cycle were almost uniformly low, but still significant (p < 0.05). For cognitive scores, we found the Withings latency was statistically significant for afternoon and evening timepoints at p = 0.016 and p = 0.013. We did not find any significant associations between SRSMs and PSQI or cognitive scores. Additionally, Oura Ring’s total sleep duration and efficiency in relation to the PSQI measure was statistically significant at p = 0.004 and p = 0.033, respectively. These findings can hopefully be used to guide future sensor-based sleep research. Full article