Characteristics associated with hypersomnia and excessive daytime sleepiness identified by extended polysomnography recording

Daytime sleepiness and BMI exhibit gender and age differences in patients with central disorders of hypersomnolence

The aim of the present study was to examine gender and age-specific effects on subjective daytime sleepiness (as measured by the Epworth Sleepiness Scale), body weight and eating behaviour in patients with central disorders of hypersomnolence. Based on the European Narcolepsy Network database, we compared 1035 patients with narcolepsy type I and 505 patients with other central disorders of hypersomnolence ("narcoleptic borderland"), including narcolepsy type II (N = 308) and idiopathic hypersomnia (N = 174), using logistic regression and general linear models. In the entire study population, the Epworth Sleepiness Scale was higher in women (N = 735, mean age = 30 years, mean Epworth Sleepiness Scale = 16.6 ± SD 3.9) than in men (N = 805, mean age = 32 years, mean Epworth Sleepiness Scale = 15.8 ± SD 4.4). In women with narcolepsy type I (N = 475), both Epworth Sleepiness Scale and body mass index increased in parallel with age. In women of the narcoleptic borderland (N = 260), the Epworth Sleepiness Scale markedly peaked in their early 30s, while body mass index only started to rise at that age. This rise in body mass index following the Epworth Sleepiness Scale peak cannot be explained by sleepiness-induced uncontrolled eating, as self-reported uncontrolled eating was negatively associated with the Epworth Sleepiness Scale in this group. We propose that the narcoleptic borderland harbours a unique cluster of women in their fertile years with an unexplored aetiology requiring further investigation towards tailored interventions.

Actigraphy against 32-hour polysomnography in patients with suspected idiopathic hypersomnia

Actigraphy, a tool known for investigating sleep-wake patterns at home, lacks scientific validation in hypersomnolent subjects. We aim to validate an actigraphy-based sleep-wake prediction algorithm against 32-h continuous polysomnography in patients with suspected idiopathic hypersomnia, and to compare its performance to predict sleep-wake parameters assessed by polysomnography with those of a commercially available algorithm. Two hundred and six hypersomnolent subjects were included prospectively in a Reference Centre for Hypersomnias, and underwent a 32-h bedrest protocol, wearing wrist-actigraphy, to diagnose idiopathic hypersomnia. Among them, 126 patients (91 females, 30.6 ± 15.5 years, 101 idiopathic hypersomnia, 25 non-specified hypersomnia) with synchronised actigraphy and polysomnography were analysed. Age, sex, and Epworth Sleepiness Scale scores were collected. We trained various supervised algorithms and selected a recurrent neural network (S2S sequence-to-sequence long short-term memory network) for comparison with Actiwatch Software (AS) on sleep-wake variables and prediction errors during daytime and nighttime. S2S outperformed AS across all relevant metrics, and Bland-Altman analysis showed disagreement between the two algorithms. S2S had a lower absolute error than AS. AS mainly overestimated sleep, an overestimation that was substantially reduced with S2S, overall as well as during day and night. Performance was not correlated with age, sex, or subjective sleepiness, but objective sleepiness and longer sleep time on the bedrest were associated with sleep underestimation. Our S2S algorithm using deep learning performed better to predict sleep-wake parameters than AS and other commonly used algorithms. The next objective is to leverage this algorithm to study sleep-wake patterns in patients with hypersomnolence at home.

Novel biomarkers derived from the Maintenance of Wakefulness Test as predictors of sleepiness and response to treatment

The Maintenance of Wakefulness Test (MWT) is a widely accepted objective test used to evaluate daytime somnolence and is commonly used in clinical studies evaluating novel therapeutics for excessive daytime sleepiness. In the latter, sleep onset latency (SOL) is typically the sole MWT endpoint. Here, we explored microsleeps, sleep probability measures derived from automated sleep scoring, and quantitative electroencephalography (qEEG) features as additional MWT biomarkers of daytime sleepiness, using data from a phase 1B trial of the selective orexin receptor 2 agonist danavorexton (TAK-925) in people with narcolepsy type 1 (NT1) or type 2 (NT2). Danavorexton treatment reduced the rate and duration of microsleeps during the MWT in NT1 (days 1 and 7; p ≤ .005) and microsleep rate in NT2 (days 1 and 7; p < .0001). The use of an EEG-sleep-staging - derived measure to determine the probability of wakefulness for each minute revealed a novel metric to track changes in daytime sleepiness, which were consistent with the θ/α ratio, a known biomarker of drowsiness. The slopes of line-fits to both the log-transformed sleepiness score or log-transformed θ/α ratio correlated well to (inverse) MWT SOL for NT1 (R = 0.93 and R = 0.83, respectively) and NT2 (R = 0.97 and R = 0.84, respectively), suggesting that individuals with narcolepsy have increased sleepiness immediately after lights-off. These analyses demonstrate that novel EEG-based biomarkers can augment SOL as predictors of sleepiness and its response to treatment and provide a novel framework for the analysis of wake EEG in hypersomnia disorders.

Association between idiopathic hypersomnia and a genetic variant in the PER3 gene

We aim to identify genetic markers associated with idiopathic hypersomnia, a disabling orphan central nervous system disorder of hypersomnolence that is still poorly understood. In our study, DNA was extracted from 79 unrelated patients diagnosed with idiopathic hypersomnia with long sleep time at the National Reference Center for Narcolepsy-France according to very stringent diagnostic criteria. Whole exome sequencing on the first 30 patients with idiopathic hypersomnia (25 females and 5 males) allowed the single nucleotide variants to be compared with a control population of 574 healthy subjects from the French Exome project database. We focused on the identification of genetic variants among 182 genes related to the regulation of sleep and circadian rhythm. Candidate variants obtained by exome sequencing analysis were then validated in a second sample of 49 patients with idiopathic hypersomnia (37 females and 12 males). Our study characterised seven variants from six genes significantly associated with idiopathic hypersomnia compared with controls. A targeted sequencing analysis of these seven variants on 49 other patients with idiopathic hypersomnia confirmed the relative over-representation of the A➔C variant of rs2859390, located in a potential splicing-site of PER3 gene. Our findings support a genetic predisposition and identify pathways involved in the pathogeny of idiopathic hypersomnia. A variant of the PER3 gene may predispose to idiopathic hypersomnia with long sleep time.

Sleep architecture in idiopathic hypersomnia: the influence of age, sex, and body mass index

This study aimed to progress the understanding of idiopathic hypersomnia (IH) by assessing the moderating influence of individual characteristics, such as age, sex, and body mass index (BMI) on sleep architecture. In this retrospective study, 76 IH participants (38.1 ± 11.3 years; 40 women) underwent a clinical interview, an in-laboratory polysomnography with a maximal 9-h time in bed and a multiple sleep latency test (MSLT). They were compared to 106 healthy controls (38.1 ± 14.1 years; 60 women). Multiple regressions were used to assess moderating influence of age, sex, and BMI on sleep variables. We used correlations to assess whether sleep variables were associated with Epworth Sleepiness Scale scores and mean sleep onset latency on the MSLT in IH participants. Compared to controls, IH participants had shorter sleep latency (p = 0.002), longer total sleep time (p < 0.001), more time spent in N2 sleep (p = 0.008), and showed trends for a higher sleep efficiency (p = 0.023) and more time spent in rapid eye movement (REM) sleep (p = 0.022). No significant moderating influence of age, sex, or BMI was found. More severe self-reported sleepiness in IH patients was correlated with shorter REM sleep latency and less N1 sleep in terms of proportion and duration (ps < 0.01). This study shows that, when compared to healthy controls, patients with IH had no anomalies in their sleep architecture that can explain their excessive daytime sleepiness. Moreover, there is no moderating influence of age, sex, and BMI, suggesting that the absence of major group differences is relatively robust.

Long sleep time and excessive need for sleep: State of the art and perspectives

The mechanisms underlying the individual need for sleep are unclear. Sleep duration is indeed influenced by multiple factors, such as genetic background, circadian and homeostatic processes, environmental factors, and sometimes transient disturbances such as infections. In some cases, the need for sleep dramatically and chronically increases, inducing a daily-life disability. This "excessive need for sleep" (ENS) was recently proposed and defined in a European Position Paper as a dimension of the hypersomnolence spectrum, "hypersomnia" being the objectified complaint of ENS. The most severe form of ENS has been described in Idiopathic Hypersomnia, a rare neurological disorder, but this disabling symptom can be also found in other hypersomnolence conditions. Because ENS has been defined recently, it remains a symptom poorly investigated and understood. However, protocols of long-term polysomnography recordings have been reported by expert centers in the last decades and open the way to a better understanding of ENS through a neurophysiological approach. In this narrative review, we will 1) present data related to the physiological and pathological variability of sleep duration and their mechanisms, 2) describe the published long-term polysomnography recording protocols, and 3) describe current neurophysiological tools to study sleep microstructure and discuss perspectives for a better understanding of ENS.

Estimation bias and agreement limits between two common self-report methods of habitual sleep duration in epidemiological surveys

Accurate measurement of habitual sleep duration (HSD) is crucial for understanding the relationship between sleep and health. This study aimed to assess the bias and agreement limits between two commonly used short HSD self-report methods, considering sleep quality (SQ) and social jetlag (SJL) as potential predictors of bias. Data from 10,268 participants in the International COVID Sleep Study-II (ICOSS-II) were used. Method-Self and Method-MCTQ were compared. Method-Self involved a single question about average nightly sleep duration (HSDself), while Method-MCTQ estimated HSD from reported sleep times on workdays (HSDMCTQwork) and free days (HSDMCTQfree). Sleep quality was evaluated using a Likert scale and the Insomnia Severity Index (ISI) to explore its influence on estimation bias. HSDself was on average 42.41 ± 67.42 min lower than HSDMCTQweek, with an agreement range within ± 133 min. The bias and agreement range between methods increased with poorer SQ. HSDMCTQwork showed less bias and better agreement with HSDself compared to HSDMCTQfree. Sleep duration irregularity was - 43.35 ± 78.26 min on average. Subjective sleep quality predicted a significant proportion of variance in HSDself and estimation bias. The two methods showed very poor agreement and a significant systematic bias, both worsening with poorer SQ. Method-MCTQ considered sleep intervals without adjusting for SQ issues such as wakefulness after sleep onset but accounted for sleep irregularity and sleeping in on free days, while Method-Self reflected respondents' interpretation of their sleep, focusing on their sleep on workdays. Including an SQ-related question in surveys may help bidirectionally adjust the possible bias and enhance the accuracy of sleep-health studies.

Habitual short sleepers with pre-existing medical conditions are at higher risk of Long COVID

STUDY OBJECTIVES

Preliminary evidence suggests that the risk of Long COVID is higher among people with pre-existing medical conditions. Based on its proven adjuvant role in immunity, habitual sleep duration may alter the risk of developing Long COVID. The objective of this study was to determine whether the odds of Long COVID are higher among those with pre-existing medical conditions, and whether the strength of this association varies by habitual sleep duration.

METHODS

Using data from 13,461 respondents from 16 countries who participated in the 2021 survey-based International COVID Sleep Study II (ICOSS II), we studied the associations between habitual sleep duration, pre-existing medical conditions, and Long COVID.

RESULTS

Of 2,508 individuals who had COVID-19, 61% reported at least 1 Long COVID symptom. Multivariable logistic regression analysis showed that the risk of having Long COVID was 1.8-fold higher for average-length sleepers (6-9 h/night) with pre-existing medical conditions compared with those without pre-existing medical conditions (adjusted odds ratio [aOR] 1.84 [1.18-2.90]; P = .008). The risk of Long COVID was 3-fold higher for short sleepers with pre-existing medical conditions (aOR 2.95 [1.04-8.4]; P = .043) and not significantly higher for long sleepers with pre-existing conditions (aOR 2.11 [0.93-4.77]; P = .073) compared with average-length sleepers without pre-existing conditions.

CONCLUSIONS

Habitual short nighttime sleep duration exacerbated the risk of Long COVID in individuals with pre-existing conditions. Restoring nighttime sleep to average duration represents a potentially modifiable behavioral factor to lower the odds of Long COVID for at-risk patients.

CITATION

Berezin L, Waseem R, Merikanto I, et al. Habitual short sleepers with pre-existing medical conditions are at higher risk of long COVID. J Clin Sleep Med. 2024;20(1):111-119.

Face validation and pharmacologic analysis of Sik3Sleepy mutant mouse as a possible model of idiopathic hypersomnia

Idiopathic hypersomnia (IH) is a chronic neurologic disorder with unknown mechanisms that result in long night-time sleep, daytime sleepiness, long non-refreshing naps, and difficult awakening presenting as sleep drunkenness. IH patients are typically diagnosed by shorter sleep latency on multiple sleep latency test (MSLT) along with long sleep time. Only symptomatic drug treatments are currently available for IH and no animal model to study it. Sleepy mice carry a splicing mutation in the Sik3 gene, leading to increased sleep time and sleep need. Here we used a mouse version of MSLT and a decay analysis of wake EEG delta power to validate the Sleepy mutant mouse as an animal model for IH. Sleepy mice had shorter sleep latency in the dark (active) phase than wild-type mice. They also showed lower decay of EEG delta density during wakefulness, possibly reflecting increased sleep inertia. These data indicate that the Sleepy mouse may have partial face validity as a mouse model for idiopathic hypersomnia. We then investigated the effect of orexin-A and the orexin receptor 2-selective agonist YNT-185 on the sleepiness symptoms of the Sleepy mouse. Intracerebroventricular orexin-A promoted wakefulness for 3 h and decreased wake EEG delta density after injection in Sleepy mice and wild-type mice. Moreover, Sleepy mice but not wild-type mice showed a sleep rebound after the orexin-A-induced wakefulness. Intraperitoneal YNT-185 promoted wakefulness for 3 h after injection in Sleepy mice, indicating the potential of using orexin agonists to treat not only orexin deficiency but hypersomnolence of various etiologies.

Update on the treatment of idiopathic hypersomnia: Progress, challenges, and expert opinion

Idiopathic hypersomnia is a central hypersomnolence disorder of unknown origin characterized by excessive daytime sleepiness despite normal or long sleep time, and frequent severe sleep inertia. Management strategies have been largely derived from expert consensus, due to a lack of disease-specific assessments and reliance on case series and rare randomized controlled studies. Guidelines recommend treatment with off-label medications. Modafinil, which was approved for idiopathic hypersomnia until 2011 in Europe, is the most commonly used treatment and improved sleepiness in two recent randomized placebo-controlled trials. In 2021, low-sodium oxybate (LXB) was approved in the United States for idiopathic hypersomnia. In a placebo-controlled, double-blind, randomized withdrawal study, LXB reduced daytime sleepiness and sleep inertia, and improved daily functioning. Here, treatment options are reviewed considering the authors' professional experience, current guidelines, and the latest research developments. The choice of pharmacotherapy should be guided by symptom profile, age, comorbidities (eg, depressive symptoms, cardiovascular problems), and concomitant medications (eg, oral contraceptives). Nonpharmacologic approaches have a role in management. An instrument (idiopathic hypersomnia severity scale) has been validated in idiopathic hypersomnia specifically, opening a path to better assessment of symptoms, impact, and response to treatment. Continued research on idiopathic hypersomnia is needed to support treatment algorithms.

Clinical considerations for the diagnosis of idiopathic hypersomnia

Idiopathic hypersomnia is a sleep disorder of neurologic origin characterized by excessive daytime sleepiness, with sleep inertia, long, unrefreshing naps, and prolonged nighttime sleep being key symptoms in many patients. Idiopathic hypersomnia is described in the International Classification of Sleep Disorders, 3rd Edition as a central disorder of hypersomnolence with distinct clinical features and diagnostic criteria; however, confirming the diagnosis of idiopathic hypersomnia is often challenging. Diagnosis of idiopathic hypersomnia is based on objective sleep testing and the presence of associated clinical features but may be difficult for clinicians to recognize and correctly diagnose because of its low prevalence, clinical heterogeneity, and symptoms, which are similar to those of other sleep disorders. The testing required for diagnosis of idiopathic hypersomnia also presents logistical barriers, and reliability of objective sleep measures is suboptimal. The pathophysiology of idiopathic hypersomnia remains unknown. In this review, clinical considerations related to the pathogenesis, diagnosis, and management of idiopathic hypersomnia will be discussed, including perspectives from the European Union and United States.

Data-Driven Phenotyping of Central Disorders of Hypersomnolence With Unsupervised Clustering

BACKGROUND AND OBJECTIVES

Recent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers.

METHODS

We used agglomerative hierarchical clustering, an unsupervised machine learning algorithm, to identify distinct hypersomnolence clusters in the large-scale European Narcolepsy Network database. We included 97 variables, covering all aspects of central hypersomnolence disorders such as symptoms, demographics, objective and subjective sleep measures, and laboratory biomarkers. We specifically focused on subgrouping of patients without cataplexy. The number of clusters was chosen to be the minimal number for which patients without cataplexy were put in distinct groups.

RESULTS

We included 1,078 unmedicated adolescents and adults. Seven clusters were identified, of which 4 clusters included predominantly individuals with cataplexy. The 2 most distinct clusters consisted of 158 and 157 patients, were dominated by those without cataplexy, and among other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening, and weekend-week sleep length difference. Patients formally diagnosed as having narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these 2 clusters.

DISCUSSION

Using a data-driven approach in the largest study on central disorders of hypersomnolence to date, our study identified distinct patient subgroups within the central disorders of hypersomnolence population. Our results contest inclusion of sleep-onset REM periods in diagnostic criteria for people without cataplexy and provide promising new variables for reliable diagnostic categories that better resemble different patient phenotypes. Cluster-guided classification will result in a more solid hypersomnolence classification system that is less vulnerable to instability of single features.

Multidimensional assessment and cluster analysis for OSA phenotyping

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is a heterogeneous disease with varying phenotype. A cluster analysis based on multidimensional disease characteristics, including symptom, anthropometry, polysomnography (PSG), and craniofacial morphology, in combination with auto-continuous positive airway pressure (CPAP) titration response and comorbidity profiles was performed within a well-characterized cohort of patients with OSA, with the aim to refine current phenotypic expressions of OSA with clinical implications.

METHODS

Two hundred and ninety-one subjects with a new diagnosis of moderate to severe OSA, referred for auto-CPAP titration to the sleep center were included for analysis. In-laboratory PSG and craniofacial computed tomography (CT) scanning was performed, followed by an auto-CPAP titration. The symptom of excessive daytime sleepiness (EDS) was assessed by Epworth sleepiness scale (ESS).

RESULTS

Three patient phenotypes, corresponding to the "normal weight, non-sleepy and moderate OSA", the "obese, non-sleepy and severe OSA" and "obese, sleepy, very severe OSA with craniofacial limitation" were identified. Among the PSG parameters, only N3% and mean pulse oxygen saturation (SPO₂) were found to be associated with ESS, and they only explain small fraction of the variation (R²=0.136). Neck circumference and craniofacial limitation were associated the more severe phenotype, which had higher prevalence of hypertension, metabolic syndrome, greater diurnal blood gas abnormalities and worse PAP titration response.

CONCLUSIONS

Three OSA phenotypes were identified according to multiple aspect of clinical features in patients with moderate to severe OSA, which differed in prevalence of hypertension, metabolic syndrome, diurnal blood gas parameters and CPAP titration response. Self-reported EDS was not related with the severity of sleep breathing disturbance, and craniofacial limitation was associated the more severe phenotype. These findings highlight the necessity of integrate multiple disease characters into phenotyping to achieve better understanding of the clinical pictures of OSA.

Idiopathic Hypersomnia Severity Scale to better quantify symptoms severity and their consequences in idiopathic hypersomnia

STUDY OBJECTIVES

To assess the responsiveness of the Idiopathic Hypersomnia Severity Scale (IHSS) to medications and estimate the minimum clinically important difference, to report clinically relevant score ranges, and to confirm its psychometric properties and whether items need to be weighted in drug-free and treated patients with idiopathic hypersomnia (IH).

METHODS

Two-hundred twenty-six (166 drug-free and 60 treated) patients with IH (cross-sectional sample) completed the 14-item IHSS to quantify the severity of the 3 major IH symptoms (excessive daytime sleepiness, prolonged nighttime sleep, and sleep inertia) and consequences; 77 untreated patients were evaluated again after treatment (longitudinal sample). Patients filled in the Epworth Sleepiness Scale, Beck Depression Inventory II, and European Quality of Life questionnaires.

RESULTS

The IHSS confirmed adequate psychometric properties with a factor analysis indicating a 3-component solution. IHSS total score was lower in treated than untreated patients, with a mean difference of 4-5 points in the cross-sectional and longitudinal samples. Distribution-based methods were used to estimate that 4 points represented the minimum clinically important difference. Four severity levels were defined with between-group differences related to treatment. The probability of having severe sleepiness, depressive symptoms, and low quality of life increased with the severity level. Our results showed that IHSS item-weighting was not necessary.

CONCLUSIONS

The IHSS is a valid and reliable tool to quantify IH symptoms, with 4 severity score levels of clinical importance. The IHSS has adequate psychometric properties and can detect symptom changes after treatment. These findings should stimulate its use in clinical settings and in research studies.

CITATION

Rassu AL, Evangelista E, Barateau L, et al. Idiopathic Hypersomnia Severity Scale to better quantify symptoms severity and their consequences in idiopathic hypersomnia. J Clin Sleep Med. 2022;18(2):617-629.

Efficacy and Safety of Lower-Sodium Oxybate in an Open-Label Titration Period of a Phase 3 Clinical Study in Adults with Idiopathic Hypersomnia

PURPOSE

To report the efficacy and safety of lower-sodium oxybate (LXB; Xywav^®) during the open-label titration and optimization period (OLT) and stable-dose period (SDP) in a clinical study for the treatment of idiopathic hypersomnia.

PATIENTS AND METHODS

Data were collected during treatment titration and optimization in a phase 3 randomized withdrawal trial in adults (18-75 years of age) with idiopathic hypersomnia who took LXB treatment (once, twice, or thrice nightly, administered orally) in the OLT (10-14 weeks), followed by the 2-week, open-label SDP. Endpoints included the Epworth Sleepiness Scale (ESS), Idiopathic Hypersomnia Severity Scale (IHSS), Patient Global Impression of Change, Clinical Global Impression of Change, Functional Outcomes of Sleep Questionnaire (FOSQ)-10, and Work Productivity and Activity Impairment Questionnaire: Specific Health Problem (WPAI:SHP).

RESULTS

The safety population included 154 participants; the modified intent-to-treat population comprised 115 participants. During open-label treatment, mean (SD) ESS scores improved (decreased) from 15.7 (3.8) at baseline to 6.1 (4.0) at end of SDP, and IHSS scores improved (decreased) from 31.6 (8.3) to 15.3 (8.5). Improvements were also observed during OLT in each individual IHSS item and in FOSQ-10 and WPAI:SHP scores. Thirty-five (22.7%) participants discontinued during OLT and SDP, 22 (14.3%) due to treatment-emergent adverse events (TEAEs) during OLT and SDP. The most frequent TEAEs in the first 4 weeks were nausea, headache, dizziness, and dry mouth; TEAE incidence decreased throughout OLT and SDP (weeks 1-4, n = 87 [56.5%]; weeks 13-16, n = 39 [31.7%]).

CONCLUSION

During open-label treatment with LXB, participants showed clinically meaningful improvements in idiopathic hypersomnia symptoms and in quality of life and functional measures. TEAE incidence declined over LXB titration and optimization.

Safety and efficacy of lower-sodium oxybate in adults with idiopathic hypersomnia: a phase 3, placebo-controlled, double-blind, randomised withdrawal study

BACKGROUND

Idiopathic hypersomnia is a central hypersomnolence disorder mainly characterised by excessive daytime sleepiness, with prolonged night-time sleep and pronounced sleep inertia. Until August, 2021, no medication had regulatory approval for the treatment of idiopathic hypersomnia. This study aimed to evaluate the safety and efficacy of lower-sodium oxybate in idiopathic hypersomnia.

METHODS

This was a phase 3, multicentre (50 specialist sleep centres; six EU countries and the USA), placebo-controlled, double-blind, randomised withdrawal study. Participants (aged 18-75 years) with idiopathic hypersomnia (meeting criteria from the International Classification of Sleep Disorders, 2nd or 3rd editions) began lower-sodium oxybate treatment (oral solution once or twice nightly) in an open-label titration and optimisation period (10-14 weeks), followed by a 2-week, open-label, stable-dose period. After these open-label periods, participants were randomised (1:1) by means of an interactive web recognition system, stratified by participants' baseline medication use, to either placebo or lower-sodium oxybate (individually optimised dose; range 2·5-9·0 g/night) during a 2-week, double-blind, randomised withdrawal period. To maintain masking of treatment assignment, placebo and lower-sodium oxybate oral solutions were matched in volume, appearance, and taste. During the double-blind, randomised withdrawal period, participants and investigators were unaware of treatment assignments. The primary efficacy endpoint was change in Epworth Sleepiness Scale (ESS) score from the end of the stable-dose period to the end of the double-blind, randomised withdrawal period, which was assessed in the modified intention-to-treat population (defined as all participants who were randomly assigned, took at least one dose of study medication during the double blind, randomised withdrawal period, and had at least one set of post-randomisation assessments for the primary or key secondary endpoints). Adverse events were assessed in the safety population (defined as all participants who took at least one dose of study medication). This study is registered at ClinicalTrials.gov, NCT03533114, and at EU Clinical Trials, 2018-001311-79, and is complete.

FINDINGS

Between Nov 27, 2018, and March 6, 2020, 154 participants were enrolled and comprised the safety population. ESS scores decreased from a mean of 15·7 (SD 3·8) at baseline to 6·1 (4·0) by the end of the stable-dose period. After the open-label periods, 115 participants were randomly assigned either placebo (n=59) or lower-sodium oxybate (n=56) and comprised the modified intention-to-treat population. During the double-blind, randomised withdrawal period, ESS scores increased (worsened) in participants randomly assigned to placebo but remained stable in those assigned to lower-sodium oxybate (least squares mean difference -6·5; 95% CI -8·0 to -5·0; p<0·0001). Treatment-emergent adverse events included nausea (34 [22%] of 154), headache (27 [18%] of 154), dizziness (19 [12%] of 154), anxiety (17 [11%] 154), and vomiting (17 [11%] 154). No deaths were reported during the study.

INTERPRETATION

Lower-sodium oxybate treatment resulted in a clinically meaningful improvement in idiopathic hypersomnia symptoms, with an overall safety profile consistent with that reported for narcolepsy. Lower-sodium oxybate was approved in August, 2021, by the US Food and Drug Administration for the treatment of idiopathic hypersomnia in adults.

FUNDING

Jazz Pharmaceuticals.

How to Design a Relevant Corpus for Sleepiness Detection Through Voice?

This article presents research on the detection of pathologies affecting speech through automatic analysis. Voice processing has indeed been used for evaluating several diseases such as Parkinson, Alzheimer, or depression. If some studies present results that seem sufficient for clinical applications, this is not the case for the detection of sleepiness. Even two international challenges and the recent advent of deep learning techniques have still not managed to change this situation. This article explores the hypothesis that the observed average performances of automatic processing find their cause in the design of the corpora. To this aim, we first discuss and refine the concept of sleepiness related to the ground-truth labels. Second, we present an in-depth study of four corpora, bringing to light the methodological choices that have been made and the underlying biases they may have induced. Finally, in light of this information, we propose guidelines for the design of new corpora.

Sleep inertia measurement with the psychomotor vigilance task in idiopathic hypersomnia

STUDY OBJECTIVES

Sleep inertia is a frequent and disabling symptom in idiopathic hypersomnia (IH), but poorly defined and without objective measures. The study objective was to determine whether the psychomotor vigilance task (PVT) can reliably measure sleep inertia in patients with IH or other sleep disorders (non-IH).

METHODS

Sixty-two (51 women, mean age: 27.7±9.2) patients with IH and 140 (71 women, age: 33.3±12.1) with non-IH (narcolepsy=29, non-specified hypersomnolence NSH=47, obstructive sleep apnea=39, insomnia=25) were included. Sleep inertia and sleep drunkenness in the last month (M-sleep inertia) and on PVT day (D-sleep inertia) were assessed with three items of the Idiopathic Hypersomnia Severity Scale (IHSS), in drug-free conditions. The PVT was performed four times (7:00 PM, and 7:00, 7:30 and 11:00 AM) and three metrics were used: lapses, mean 1/Reaction Time (RT), slowest 10% 1/RT.

RESULTS

Sleep inertia was more frequent in patients with IH than non-IH (56.5% and 43.6% with severe sleep inertia in the past month, including 24% and 12% with sleep drunkenness). Lapse number increase and slowest 10% 1/RT decrease, particularly at 7:00 and 7:30AM, were proportional with M-sleep inertia severity, but regardless of sleep drunkenness and sleep disorders. Similar results were obtained when PVT results were compared in patients with/without D-sleep inertia, with the largest increase of the lapse number at 7:00 and 7:30AM associated with severe sleep inertia and sleep drunkenness.

CONCLUSION

PVT is a reliable and objective measure of sleep inertia that might be useful for its characterization, management and follow-up in patients with IH.