Symptom Severity and Treatment Satisfaction in Patients with Idiopathic Hypersomnia: The Real World Idiopathic Hypersomnia Outcomes Study (ARISE).

Objective: Idiopathic hypersomnia is a debilitating sleep disorder characterized by excessive daytime sleepiness, sleep inertia, and prolonged sleep duration. The patient burden of idiopathic hypersomnia is poorly understood. The Real World Idiopathic Hypersomnia Outcomes Study (ARISE) evaluated symptoms and treatment effectiveness/satisfaction in participants with idiopathic hypersomnia. Methods: ARISE was a United States-based virtual cross-sectional survey. Participants were adults 21-65 years of age with idiopathic hypersomnia recruited from social media, the Hypersomnia Foundation website, and a patient panel. Self-assessments included the Epworth Sleepiness Scale (ESS), Idiopathic Hypersomnia Severity Scale (IHSS), Treatment Satisfaction Questionnaire for Medication, version II (TSQM-vII), and additional treatment questions. Data were analyzed for all participants and for subgroups with/without long sleep time (LST; ≥11 hours in 24 hours). Results: Of 75 participants enrolled, most were female (81.3%). The mean (SD) age was 34.1 (10.7) years and 49% had LST. Most participants took off-label prescription medications (89.3%) and/or used other measures (93.3%) to manage their symptoms. The mean (SD) ESS score was 14.5 (3.5) and the mean IHSS score was 35.2 (7.6). Treatment satisfaction was low (mean [SD] TSQM-vII score: overall, 61.9 [21.2]; with LST, 57.9 [21.4]; without LST, 66.7 [20.3]), primarily driven by dissatisfaction with treatment effectiveness. The most common classes of prescription medications used were stimulants (61.3%), wake-promoting agents (28.0%), and antidepressants (18.7%); non-prescription measures used to manage symptoms included caffeine (73.3%), planned naps (34.7%), and individual accommodations (32.0%). Conclusion: Overall, participants with idiopathic hypersomnia, with or without LST, had substantial symptom burden despite most of the study population taking off-label medications and using nonprescription measures to manage symptoms.

Automatic, electrocardiographic-based detection of autonomic arousals and their association with cortical arousals, leg movements, and respiratory events in sleep.

Study Objectives: The current definition of sleep arousals neglects to address the diversity of arousals and their systemic cohesion. Autonomic arousals (AA) are autonomic activations often associated with cortical arousals (CA), but they may also occur in relation to a respiratory event, a leg movement event or spontaneously, without any other physiological associations. AA should be acknowledged as essential events to understand and explore the systemic implications of arousals. Methods: We developed an automatic AA detection algorithm based on intelligent feature selection and advanced machine learning using the electrocardiogram. The model was trained and tested with respect to CA systematically scored in 258 (181 training size/77 test size) polysomnographic recordings from the Wisconsin Sleep Cohort. Results: A precision value of 0.72 and a sensitivity of 0.63 were achieved when evaluated with respect to CA. Further analysis indicated that 81% of the non-CA-associated AAs were associated with leg movement (38%) or respiratory (43%) events. Conclusions: The presented algorithm shows good performance when considering that more than 80% of the false positives (FP) found by the detection algorithm appeared in relation to either leg movement or respiratory events. This indicates that most FP constitute autonomic activations that are indistinguishable from those with cortical cohesion. The proposed algorithm provides an automatic system trained in a clinical environment, which can be utilized to analyze the systemic and clinical impacts of arousals.

Breathing Disturbances Without Hypoxia Are Associated With Objective Sleepiness in Sleep Apnea.

Study Objectives: To determine whether defining two subtypes of sleep-disordered breathing (SDB) events-with or without hypoxia-results in measures that are more strongly associated with hypertension and sleepiness. Methods: A total of 1022 participants with 2112 nocturnal polysomnograms from the Wisconsin Sleep Cohort were analyzed with our automated algorithm, developed to detect breathing disturbances and desaturations. Breathing events were time-locked to desaturations, resulting in two indices-desaturating (hypoxia-breathing disturbance index [H-BDI]) and nondesaturating (nonhypoxia-breathing disturbance index [NH-BDI]) events-regardless of arousals. Measures of subjective (Epworth Sleepiness Scale) and objective (2981 multiple sleep latency tests from a subset of 865 participants) sleepiness were analyzed, in addition to clinically relevant clinicodemographic variables. Hypertension was defined as BP ≥ 140/90 or antihypertensive use. Results: H-BDI, but not NH-BDI, correlated strongly with SDB severity indices that included hypoxia (r ≥ 0.89, p ≤ .001 with 3% oxygen-desaturation index [ODI] and apnea hypopnea index with 4% desaturations). A doubling of desaturation-associated events was associated with hypertension prevalence, which was significant for ODI but not H-BDI (3% ODI OR = 1.06, 95% CI = 1.00-1.12, p < .05; H-BDI OR 1.04, 95% CI = 0.98-1.10) and daytime sleepiness (ß = 0.20 Epworth Sleepiness Scale [ESS] score, p < .0001; ß = -0.20 minutes in MSL on multiple sleep latency test [MSLT], p < .01). Independently, nondesaturating event doubling was associated with more objective sleepiness (ß = -0.52 minutes in MSL on MSLT, p < .001), but had less association with subjective sleepiness (ß = 0.12 ESS score, p = .10). In longitudinal analyses, baseline nondesaturating events were associated with worsening of H-BDI over a 4-year follow-up, suggesting evolution in severity. Conclusions: In SDB, nondesaturating events are independently associated with objective daytime sleepiness, beyond the effect of desaturating events.