Sleeping through a pandemic: impact of COVID-19-related restrictions on narcolepsy and idiopathic hypersomnia.

Seasonality of excessive daytime sleepiness has been proposed, yet no research has specifically investigated its impact on daytime sleepiness and cataplexy in central disorders of hypersomnolence. This study examined seasonal variations in daytime sleepiness and cataplexy in narcolepsy type 1, narcolepsy type 2 and idiopathic hypersomnia. Patients included in the study were on stable pharmacological treatment, and participated in sleep medicine interviews to assess diurnal sleepiness and daytime napping and completed the Epworth Sleepiness Scale to assess excessive daytime sleepiness (Epworth Sleepiness Scale ≥ 10). Patients with narcolepsy type 1 also maintained a cataplexy diary. Evaluations were conducted in autumn, winter, spring and summer. The study included 29 patients with narcolepsy type 1, 16 patients with narcolepsy type 2 and 10 patients with idiopathic hypersomnia. Patients with narcolepsy type 1 and narcolepsy type 2 showed higher Epworth Sleepiness Scale scores in summer compared with other seasons, while patients with idiopathic hypersomnia showed no changes in excessive daytime sleepiness across the four seasons. Epworth Sleepiness Scale scores were higher in idiopathic hypersomnia patients compared to narcolepsy type 1 and narcolepsy type 2 patients in spring, autumn, and winter; conversely, in summer there were no differences in Epworth Sleepiness Scale scores among the three groups. No significant differences in Epworth Sleepiness Scale scores were noted between patients with narcolepsy type 1 and narcolepsy type 2 throughout the year. Furthermore, no seasonal effect on cataplexy frequency was found in patients with narcolepsy type 1. This study demonstrates that seasonality may influence daytime sleepiness in patients with narcolepsy type 1 and narcolepsy type 2 but not in patients with idiopathic hypersomnia, while cataplexy symptoms remain unaffected by seasonal changes. The underlying mechanisms linking excessive daytime sleepiness to seasonality have yet to be explored, though social factors and vacation time may contribute to increased excessive daytime sleepiness in narcolepsy.

Introduction Central Disorders of Hypersomnolence (CDH) are classified primarily by polysomnography-multiple sleep latency test (PSG-MSLT). Lack of biomarkers and variable MSLT results in disorders other than narcolepsy type 1 (NT1) contribute to under- and mis-diagnosis. Limited studies explore PSG characteristics that may differentiate CDH subtypes using large datasets. Methods This retrospective cohort included 1,330 patients who underwent PSG-MSLT for hypersomnolence (January 2003-August 2024) at Cleveland Clinic. Cases were classified as NT1, narcolepsy type 2 (NT2), idiopathic hypersomnia (IH) and undifferentiated hypersomnia (UH; not meeting CDH criteria) based on physician clinical diagnosis. 557 patients with disorders associated with hypersomnia (i.e. OSA) were excluded. Demographic and PSG characteristics were compared with ANOVA, Kruskal-Wallis, and Pearson chi-square tests. Results Of 773 patients (33.7±14.0 yr, 79.4% female), 72(9.3%) had NT1,121(15.7%) NT2, 296(38.3%) IH, and 284(36.7%) UH. While groups did not differ in age or gender, more Caucasians had IH and UH than NT1(78.6, 80.8 vs. 62.5%, p=0.001). Epworth Sleepiness Scale scores were lower in UH than CDH groups (12.6±5.0 vs NT1-15.9±5.6,NT2-16.1±5.1,IH-14.2±5.2, p< 0.001). Self-reported sleep time was longer for UH than NT2 without other group differences (UH-9.1±2.1,NT2-8.4±1.7,NT1-8.6±2.1,IH-8.8±1.9 hours, p=0.003). PSG sleep onset REM periods (SOREMPs) were more common in NT1 and NT2 than IH and UH (NT1-27.8%,NT2-9.1%,IH-1.01%,UH-1.06%, p< 0.001). NT1 and NT2 had shorter REM latency than IH and UH(NT1-73.5[7.0,123.0],NT2-74.0[53.0,112.0],IH-103.0[71.0,161.5],UH-105.0[74.5,183.0] min, p< 0.001). NT1 and UH showed more wakefulness after sleep onset than NT2 and IH (NT1-43.5[26.0,97.0],UH-47.5[25.5, 85.0],NT2-32.5[17.3,61.5],IH-30.5[17.5, 62.5] min, p< 0.001). Sleep latency was shorter in CDH than UH (NT1-10.8[4.5,26.0],NT2-14.0[6.0,24.5],IH-17.5[7.8,30.5],UH-24.5[12.5,39.0] min, p< 0.001), and sleep efficiency higher in NT2 and IH than UH (NT2-87.4±7.3,IH-86.3±8.8,UH-82.0±10.0, p< 0.001). NT1 had greater, though non-significant, arousal index, stage shifts, and N1 percentage, along with lower sleep efficiency than NT2 and IH. No significant differences were observed between NT2 and IH in sleep latency, sleep efficiency, arousal index, WASO, stage shifts, or stage percentages. Conclusion We found significant differences in PSG variables between CDH that confirm and extend prior observations. Minimal differences between NT2 and IH support a common pathophysiology. Recognizing the larger group of UH with distinct PSG features from CDH is important in clinical practice. Support (if any)

PurposeMyotonic dystrophy type 1 (DM1) is often characterized by excessive daytime sleepiness (EDS) and sleep-onset rapid eye movement periods caused by muscleblind-like protein 2. The EDS tends to persist even after treatment of sleep apnea. We measured the cerebrospinal fluid (CSF) orexin levels in DM1 patients with EDS and compared the clinical characteristics with narcolepsy type 1 and idiopathic hypersomnia (IHS) patients.Patients and methodsWe measured the CSF orexin levels in 17 DM1 patients with EDS and evaluated subjective sleepiness using the Epworth Sleepiness Scale (ESS), objective sleepiness using mean sleep latency (MSL), and sleep apnea using apnea-hypopnea index (AHI). We compared the ESS scores and MSL between decreased (≤200 pg/mL) and normal (>200 pg/mL) CSF orexin group in DM1 patients. Furthermore, we compared the CSF orexin levels, ESS scores, MSL, and AHI among patients with DM1, narcolepsy type 1 (n=46), and IHS (n=30).ResultsSeven DM1 patients showed decreased CSF orexin levels. There were significant differences in the ESS scores and MSL between decreased and normal CSF orexin groups in DM1 patients. The ESS scores showed no significant difference among patients with DM1, narcolepsy type 1, and IHS. The MSL in DM1 and IHS patients were significantly higher than narcolepsy type 1 patients (p=0.01, p<0.001). The AHI in DM1 patients was significantly higher than narcolepsy type 1 patients (p=0.042) and was insignificantly different from IHS patients. The CSF orexin levels in DM1 patients were significantly lower than IHS patients and higher than narcolepsy type 1 patients (p<0.001, p<0.001).ConclusionThe CSF orexin levels of DM1 patients moderately decreased compared to those of IHS patients as the control group. However, the EDS of DM1 patients may not be explained by only orexin deficiency.

Narcolepsy type 2 (NT2) is an understudied central disorder of hypersomnolence sharing some similarities with narcolepsy type 1 and idiopathic hypersomnia (IH). We aimed: (1) to assess systematically the symptoms in patients with NT2, with self-reported questionnaires: Epworth Sleepiness Scale (ESS), Narcolepsy Severity Scale (NSS), IH Severity Scale (IHSS), and (2) to evaluate the responsiveness of these scales to treatment. One hundred and nine patients with NT2 (31.4 ± 12.2 years old, 47 untreated) diagnosed according to ICSD-3 were selected in a Reference Center for Narcolepsy. They all completed the ESS, subgroups completed the modified NSS (NSS-2, without cataplexy items) (n = 95) and IHSS (n = 76). Some patients completed the scales twice (before/during treatment): 42 ESS, 26 NSS-2, and 30 IHSS. Based on NSS-2, all untreated patients had sleepiness, 58% disrupted nocturnal sleep, 40% hallucinations, and 28% sleep paralysis. On IHSS, 76% reported a prolonged nocturnal sleep, and 83% sleep inertia. In the independent sample, ESS and NSS-2 scores were lower in treated patients, with same trend for IHSS scores. After treatment, ESS, NSS-2, and IHSS total scores were lower, with a mean difference of 3.7 ± 4.1, 5.3 ± 6.7, and 4.1 ± 6.2, respectively. The minimum clinically important difference between untreated and treated patients were 2.1 for ESS, 3.3 for NSS-2, and 3.1 for IHSS. After treatment, 61.9% of patients decreased their ESS > 2 points, 61.5% their NSS-2 > 3 points, and 53.3% their IHSS > 3 points. NSS-2 and IHSS correctly quantified symptoms' severity and consequences in NT2, with good performances to objectify response to medications. These tools are useful for monitoring and optimizing NT2 management, and for use in clinical trials.

Idiopathic hypersomnia (IH) is a rare central disorder of hypersomnolence characterized by excessive daytime sleepiness, prolonged nighttime sleep, and sleep inertia. Low-sodium oxybate is the sole Food and Drug Administration-approved treatment for IH. Objective measures of nighttime sleep and daytime sleepiness are lacking with oxybates in IH. We aimed to evaluate efficacy and safety of sodium oxybate (SXB) in IH. This phase 3, double-blind, parallel-group, placebo-controlled trial was conducted at the National Reference Center for Hypersomnia in Montpellier-France. Eligible participants aged 18-60 years with IH with an Epworth Sleepiness Scale (ESS) score ≥14 were randomly assigned to receive SXB or placebo (1:1). After a 2-week screening without any drugs and without exposure to oxybate, patients started a 6-week individual twice-nightly up-titration scheme from 4.5 g to a maximum of 9 g. Treatment was administered at stable dose for 2 weeks, followed by a 2-week taper period. The primary endpoint was the between-group difference in ESS scores at week 8, identified by a covariance analysis, including baseline ESS scores. The same methodology was applied for secondary endpoints including Idiopathic Hypersomnia Severity Scale (IHSS) score and sleep latency on the Maintenance of Wakefulness Test (MWT). Safety was examined as a secondary endpoint. Among the 48 patients screened, 45 were randomized (36 women, 29.0 ± 7.5 years, 22 assigned to SXB, 23 to placebo) and 40 (19 receiving SXB, 21 placebo) completed the study. In the intention-to-treat analysis, the mean ESS score was significantly reduced in the SXB group compared with placebo, after adjusting for the baseline score (least squared [LS] mean difference: -6.86, 95% CI [-9.73 to -4.00]), p < 0.0001). Significant differences between SXB and placebo groups at week 8 were observed for the IHSS score (LS mean difference: -11.61; 95% CI [-16.63 to -6.59], p < 0.0001) and MWT latency (14.75; 95% CI [9.98-19.52], p < 0.0001). Treatment-emergent adverse events (nausea, headache, and dizziness) were reported in 81.8% patients with SXB and 26.1% with placebo. SXB resulted in a clinically meaningful improvement in adults with IH, reducing excessive sleepiness on ESS, improving wakefulness on MWT, and decreasing IH severity on IHSS after 8 weeks. The safety profile was consistent with previous reports on SXB. ClinicalTrials.gov NCT03597555, EudraCT number 2017-004122-15. This article provides Class I evidence that sodium oxybate at a dose of 4.5-9 g per night compared with placebo reduces excessive sleepiness, improves wakefulness, and decreases disease severity with expected side effects in patients with idiopathic hypersomnia.

Comparative polysomnography parameters between narcolepsy type 1/type 2 and idiopathic hypersomnia: A systematic review and meta-analysis

Idiopathic hypersomnia (IH) and narcolepsy type 2 (NT2) are rare hypersomnolence disorders with unknown pathophysiology. Recent evidence suggests they may belong to the same spectrum. This study compared objective sleep duration and REM sleep features, including sleep-onset REM periods (SOREMPs), during a 32-h continuous polysomnography (PSG) in patients with confirmed NT2 or IH. Consecutive drug-free patients with sleepiness complaints underwent baseline PSG and multiple sleep latency test (MSLT) and were included if their mean sleep latency was ≤8min, with a clear NT2 or IH diagnosis. They were classified into three groups based on baseline SOREMPs (0, 1, or ≥2). During a second visit, they underwent a 32-h bedrest protocol with continuous PSG under controlled conditions. Of 84 patients (mean age 28.6 ± 8.9years, 70.2% female), 22 had ≥2 SOREMPs (NT2), 16 had 1 (IH), and 46 had none (IH) at baseline PSG/MLST. Surprisingly, total sleep duration during the 32-h bedrest and SOREMP count did not differ between the three groups. However, the ≥2 SOREMPs group had longer REM sleep duration, more REM sleep bouts, and more REM/Wake transitions during bedrest. Patients with 1 or ≥2 SOREMPs also showed a higher REM sleep proportion at baseline than those without SOREMPs. Total sleep time and number of SOREMPs during prolonged PSG did not differ between IH and NT2. NT2 patients, however, exhibited more REM sleep and REM/Wake transitions. Overall, our data on sleep time and SOREMPs frequency support IH and NT2 as a single disease entity. Statement of Significance Idiopathic hypersomnia (IH) and narcolepsy type 2 (NT2) are rare central hypersomnolence disorders with unknown pathophysiology, with recent evidence suggesting they may belong to the same spectrum. We found that patients with objective EDS (MSLT ≤8min), without cataplexy, with ≥2 SOREMPs on the MSLT (NT2), compared to the others (IH; 0 or 1 SOREMPs), had similar total sleep duration during the 32-h bedrest protocol with continuous PSG. The number of SOREMPs was not higher in patients with NT2 during this continuous recording, although they exhibited longer REM sleep duration, more REM sleep bouts, and more REM/Wake transitions. Overall, these data on sleep time and number of SOREMPs support IH and NT2 as a single disease entity.

Given that intelligence quotient (IQ) has not previously been assessed in idiopathic hypersomnia (IH) and only rarely in adults with narcolepsy type 1 (NT1), this study examined IQ in adults with IH and NT1. The Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV), comprising the Full Scale IQ, four indices and 10 subtests, was administered to 29 participants with IH (22 women; age: 34.1±11.3y [mean±SD]; Epworth Sleepiness Scale [ESS] score: 12.4±4.7), 30 with NT1 (19 women; age: 30.1±10.6y; ESS: 15.5±5), and 30 healthy controls (21 women, age: 30.7±8.7y; ESS: 5.0±3.6). Full-Scale IQ scores differed across groups (IH: 114.6±13.4; NT1: 104.1±14.3; and controls: 108.4±17.0; p=0.03, medium effect size). Both IH and NT1 groups showed IQ comparable to controls, although IH participants tended to outperform those with NT1. Group differences emerged in the perceptual reasoning and working memory domains, although none of pairwise comparisons reached significance. The only cognitive area showing group differences was visuospatial reasoning. Global cognitive abilities, including Full-scale IQ, General Ability Index, Verbal Comprehension Index and Working Memory Index showed moderate correlation with years of education, though not with disease duration, daytime sleepiness or treatment status. Pre-test fatigue, though not daytime sleepiness, was associated with poorer working memory performances. Adults with IH and NT1 exhibit normal-range IQs despite chronic hypersomnolence and cognitive complaints. Emphasizing preserved intellectual functioning may contribute to enhanced self-esteem and support professional development in these populations.

Differential diagnosis of narcolepsy type 2 (NT2) from type 1 (NT1) and idiopathic hypersomnia (IH) is challenging due to overlapping symptoms. We developed an automated method using nocturnal polysomnography (nPSG) data to differentiate these conditions and clinical controls (CCs), and explored varying sleep phenotypes within NT1, NT2, IH, and CCs. We analyzed nPSG data from drug-free individuals with NT1, NT2, and IH, or CCs. Sleep features were derived at whole-night and per-quarter-night levels, including hypnogram, transition probability, hypnodensity, spindle, and quantitative electroencephalogram (qEEG) features. Random forest machine learning models were used for three classification tasks. Within-diagnosis clustering identified potential diagnosis subgroups. The sample included 350 individuals (52% females; median age 30years; 114 NT1, 90 NT2, 105 IH, and 41 CCs). Our models achieved area under the receiver operating characteristic curve values of 0.87, 0.79, and 0.82 for distinguishing NT2 from CCs, NT2 from IH, and IH from CCs, with corresponding F1 scores of 0.74, 0.71, and 0.69, respectively. qEEG features substantially contributed to model performance, distinguishing NT2 from IH. Cluster analysis revealed two NT1 subgroups (one showing more severe sleep disturbances), two NT2 subgroups (one trended toward NT1, the other toward IH), and two IH subgroups with differences in hypnodensity, qEEG, and spindle characteristics. Our exploratory findings demonstrate strong diagnosis classification performance from nPSG data alone, more easily distinguishing NT2 from CCs than from IH, and IH from CCs. The distinct NT2 subgroups suggest heterogeneity within NT2; further research is warranted to explore these patterns. Statement of Significance Accurate diagnoses of narcolepsy types 2 (NT2) and 1 and idiopathic hypersomnia (IH) remain challenging due to overlapping symptoms. We developed a machine learning model using drug-free nocturnal polysomnography data to automatically differentiate NT2 from clinical controls, NT2 from IH, and IH from clinical controls, with high accuracy. Our model leverages a rich set of sleep features, including spindle and quantitative electroencephalogram (qEEG) metrics. Furthermore, our analysis revealed distinct sleep phenotypes within each diagnosis, suggesting subtypes with varying levels of sleep disturbance and differences at qEEG and spindle levels. These findings provide a novel approach to classifying central disorders of hypersomnolence and suggest disease heterogeneity, which could lead to more accurate and timely diagnoses and personalized treatment strategies.

To explore the first coronavirus disease 2019 (COVID-19) lockdown effect on sleep symptoms in patients with narcolepsy, idiopathic hypersomnia (IH), and restless legs syndrome (RLS). Between March and May 2020, a sample of adult patients regularly followed up in a Reference Hospital Sleep Unit (299 with narcolepsy, 260 with IH, and 254 with RLS) was offered an online survey assessing their sleep-wake habits, daily activities, medication intake, and validated scales: International RLS Study Group questionnaire, Narcolepsy Severity Scale (NSS), IH Severity Scale (IHSS), Epworth Sleepiness Scale (ESS), Insomnia Severity Index, Beck Depression Inventory-II, and European Quality of Life (QoL) scale. The survey was proposed once, and the questions were answered for the prelockdown (recall of the month before the confinement) and the lockdown (time of study) periods. Overall, 331 patients completed the survey (response rate 40.7%): 102 with narcolepsy, 81 with IH, and 148 with RLS. All patients reported later bedtimes, with reduced differences for time in bed (TIB) and total sleep time (TST) over 24 hours between weekdays and weekends. Patients with narcolepsy spent more TIB and increased TST overnight, with more daytime napping. They had more awakenings, higher ESS scores, lower QoL, and no NSS changes. Patients with IH also increased their TIB, TST overnight and 24 hours on weekdays. Nocturnal sleep latency and the number of awakenings increased but with no change in ESS, QoL, and IHSS scores. Patients with RLS reported longer nocturnal sleep latency, more awakenings, more naps, decreased TIB, and TST overnight. RLS severity increased while QoL decreased. A significant portion of patients reported disease worsening during the lockdown (narcolepsy: 39.4%, IH: 43.6%, and RLS: 32.8%), and some patients stopped or lowered their medication (narcolepsy: 22.5%, IH: 28%, and RLS: 9.5%). During the lockdown, all patients reported later bedtimes; those with narcolepsy and IH extended their sleep duration unlike patients with RLS. These changes were often associated with negative consequences on QoL. In the current context of recurrent COVID-19 waves, the recent development of teleconsultations should enable physicians to monitor patients with chronic sleep disorders more closely and to recommend optimized sleep schedules and duration, in order to prevent psychological problems and improve their QoL.

Introduction Extended-release once-nightly sodium oxybate (ON-SXB; FT218) is in development for adults with narcolepsy. In REST-ON, significant improvements on the Maintenance of Wakefulness test, Clinical Global Impression of Improvement rating, and number of weekly cataplexy episodes occurred with all analyzed ON-SXB doses vs placebo (week 3, 6-g dose; week 8, 7.5-g dose; week 13, 9-g dose; all P&amp;lt;0.001). ON-SXB was superior to placebo on Epworth Sleepiness Scale (ESS) score and sleep quality and refreshing nature of sleep using visual analog scales (VAS; all P&amp;lt;0.001). ON-SXB 4.5 g significantly reduced cataplexy episodes vs placebo at week 1 (P&amp;lt;0.05). Post hoc analyses investigated ON-SXB efficacy on ESS score, VAS sleep quality, and VAS refreshing nature of sleep at weeks 1 and 2. Methods Participants in the double-blind, phase 3 REST-ON (NCT02720744) trial were ≥16 years old, had narcolepsy type 1 or 2, and were randomized 1:1 to ON-SXB (4.5 g, 1 week; 6 g, 2 weeks; 7.5 g, 5 weeks; 9 g, 5 weeks) or placebo. Participants recorded ESS scores and VAS for sleep quality and refreshing nature of sleep (1-100; 1=poor quality/unrefreshing sleep; 100=good quality/refreshing sleep) using electronic diaries. P-values were calculated using a mixed-effects model for repeated measures in the modified intent-to-treat (mITT) population (ie, participants receiving ≥1 dose of study drug having ≥1 efficacy assessment at week 3). Results In the mITT population (n=190; ON-SXB, n=97; placebo, n=93), baseline ESS scores were 16.6 and 17.5 with ON-SXB and placebo, respectively. At week 2, ESS score was significantly improved with ON-SXB vs placebo (P&amp;lt;0.02) with numerical improvement seen at week 1. At baseline, sleep quality was 53.8 and 55.9 on VAS in the ON-SXB and placebo groups, respectively, and baseline refreshing nature of sleep was 46.5 and 49.9. At weeks 1 and 2, sleep quality (P&amp;lt;0.01; P&amp;lt;0.001) and refreshing nature of sleep (P&amp;lt;0.05; P=0.001) were significantly improved for ON-SXB vs placebo. Conclusion Improvement in daytime sleepiness, sleep quality, and refreshing nature of sleep occurred with ON-SXB beginning the first week of treatment. Some patients may experience early narcolepsy symptom relief with ON-SXB. Support (If Any) Avadel Pharmaceuticals

Teleworking during a pandemic: perspective of an idiopathic hypersomnia patient.

SummaryThe differential diagnosis of narcolepsy type 1, a rare, chronic, central disorder of hypersomnolence, is challenging due to overlapping symptoms with other hypersomnolence disorders. While recent years have seen significant growth in our understanding of nocturnal polysomnography narcolepsy type 1 features, there remains a need for improving methods to differentiate narcolepsy type 1 nighttime sleep features from those of individuals without narcolepsy type 1. We aimed to develop a machine learning framework for identifying sleep features to discriminate narcolepsy type 1 from clinical controls, narcolepsy type 2 and idiopathic hypersomnia. The population included polysomnography data from 350 drug‐free individuals (114 narcolepsy type 1, 90 narcolepsy type 2, 105 idiopathic hypersomnia, and 41 clinical controls) collected at the National Reference Centers for Narcolepsy in Montpelier, France. Several sets of nocturnal sleep features were explored, as well as the value of time‐resolving sleep architecture by analysing sleep per quarter‐night. Several patterns of nighttime sleep evolution emerged that differed between narcolepsy type 1, clinical controls, narcolepsy type 2 and idiopathic hypersomnia, with increased nighttime instability observed in patients with narcolepsy type 1. Using machine learning models, we identified rapid eye movement sleep onset as the best single polysomnography feature to distinguish narcolepsy type 1 from controls, narcolepsy type 2 and idiopathic hypersomnia. By combining multiple feature sets capturing different aspects of sleep across quarter‐night periods, we were able to further improve between‐group discrimination and could identify the most discriminative sleep features. Our results highlight salient polysomnography features and the relevance of assessing their time‐dependent changes during sleep that could aid diagnosis and measure the impact of novel therapeutics in future clinical trials.

Jazz DUET (Develop hypersomnia Understanding by Evaluating low-sodium oxybate Treatment) was a phase 4, prospective, multicenter, single-arm, open-label, multiple-cohort study of individuals with idiopathic hypersomnia or narcolepsy evaluating safety and effectiveness of low-sodium oxybate (LXB; Xywav®) treatment on sleep and daytime symptoms. Results from the idiopathic hypersomnia cohort are reported here. The DUET study included a screening period (with a 2-week washout for current oxybate users), an8-day baseline (BL) period, a 2- to 8-week LXB titration period, a 2-week stable-dose period, an 8-day end-of-treatment period (EOT) period, and a2-week safety follow-up. The primary endpoint was the change in Epworth Sleepiness Scale (ESS) score from BL to EOT. Secondary endpoints for the idiopathic hypersomnia cohort included change in Idiopathic Hypersomnia Severity Scale (IHSS) total score; Patient Global Impression of Change (PGI-C) and Severity (PGI-S) for overall idiopathic hypersomnia disease, sleep inertia, and fatigue; and changes in sleep quality and feeling rested upon awakening (from self-reported daily sleep diary). Exploratory outcomes included sleep patterns measured by actigraphy, the British Columbia Cognitive Complaints Inventory, Functional Outcomes of Sleep Questionnaire-10 (FOSQ-10), and Work Productivity and Activity Impairment Questionnaire: Specific Health Problem. Incidence and severity of treatment-emergent adverse events (TEAEs) were assessed. Forty-six participants with idiopathic hypersomnia enrolled and took LXB for ≥ 1 night after the BL period; n = 40 completed. Most enrolled participants were female (80.4%), White (84.8%), and non-Hispanic/Latino (76.1%), with mean (SD) age of 38.1 (11.8) years; 19 (41.3%) were taking concomitant alerting agents. Least squares mean (LSM; standard error [SE]) changes in ESS score and IHSS total score from BL to EOT were - 8.4 (0.7), p < 0.0001, and - 15.5 (1.5), p < 0.0001, respectively. On the PGI-C at EOT, most participants (94.6%; 95% CI 81.8, 99.3) reported improvement in overall idiopathic hypersomnia disease. Additionally, participants showed improvements (BL vs EOT) in sleep quality (36.7% vs 6.7% reporting "poor" or "very poor") and level of feeling rested upon awakening (73.3% vs 26.7% reporting "slightly" or "not at all rested"), and number of awakenings on actigraphy (LSM [SE] change - 3.4 [0.6], p < 0.0001). Participants also exhibited improved daytime functioning in parallel with reduced nocturnal sleep time. From BL to EOT, LSmean (SE) changes for work time missed, impairment while working, overall work impairment, and activity impairment were - 4.6% (1.8%), p = 0.0179;- 30.7% (3.9%), p< 0.0001;- 32.4% (4.3%), p < 0.0001;and - 37.3% (4.3%),p < 0.0001, respectively. Treatment-emergent adverse events (occurring in ≥ 10% of participants) included nausea (19.6%), dizziness (17.4%), headache (17.4%), and vomiting (10.9%). Individuals with idiopathic hypersomnia treated with open-label LXB showed improvements in subjective and objective measures of sleep and symptoms. Treatment-emergent adverse events were consistent with the known safety profile of LXB. This study supports the effectiveness of LXB in treating this condition with a 24-h burden of symptoms. ClinicalTrials.gov NCT05875974. [Graphical abstract available].

Many patients with severe obstructive sleep apnea (OSA) do not complain of excessive daytime sleepiness (EDS), possibly due to increased sympathetic nervous activity (SNA) and accompanying heightened alertness. We hypothesized that in patients with OSA, those without subjective EDS (Epworth Sleepiness Scale, ESS score < 11) would have higher very low frequency (VLF) heart rate variability (HRV) during sleep, reflecting greater sympathetic heart rate modulation than patients with an ESS score ≥ 11. Patients with severe OSA (AHI ≥ 30: 26 with and 65 without heart failure) were divided into those with and without EDS. Heart rate (HR) signals were acquired in stage 2 sleep during periods of recurrent apneas and hypopneas and submitted to coarse graining spectral analysis, which extracts harmonic, neurally mediated contributions to HRV from total spectral power. Because the apnea-hyperpnea cycle entrains muscle SNA at VLF (0 to 0.04 Hz), VLF power was our principal between-group comparison. Subjects without EDS had higher harmonic VLF power (944 ± 839 vs 447 ± 461 msec(2), p = 0.003) than those with EDS, irrespective of the presence or absence of heart failure (1218 ± 944 vs 426 ± 299 msec(2), p = 0.043, and 1029 ± 873 vs 503 ± 533 msec(2), p = 0.003, respectively). ESS scores correlated inversely with VLF power in all (r = -0.294, p = 0.005) and in heart failure subjects (r = -0.468, p = 0.016). Patients with severe OSA but without EDS have higher VLF-HRV than those with EDS. This finding suggests that patients with severe OSA but without EDS have greater sympathetic modulation of HRV than those with EDS that may reflect elevated adrenergically mediated alertness. Taranto Montemurro L; Floras JS; Picton P; Kasai T; Alshaer H; Gabriel JM; Bradley TD. Relationship of heart rate variability to sleepiness in patients with obstructive sleep apnea with and without heart failure.