Effect of transnasal insufflation on sleep disordered breathing in acute stroke: a preliminary study

Background and Purpose: Sleep disordered breathing (SDB) is frequent in acute stroke patients and is associated with early neurologic worsening and poor outcome. Although continuous positive airway pressure (CPAP) effectively treats SDB, compliance is low. The objective of the present study was to assess the tolerance and the efficacy of a continuous high-flow-rate air administered through an open nasal cannula (transnasal insufflation, TNI), a less-intrusive method, to treat SDB in acute stroke patients. Methods: Ten patients (age, 56.8 ± 10.7years), with SDB ranging from moderate to severe (apnea-hypopnea index, AHI, >15/h of sleep) and on a standard sleep study at a mean of 4.8 ± 3.7days after ischemic stroke (range, 1-15days), were selected. The night after, they underwent a second sleep study while receiving TNI (18L/min). Results: TNI was well tolerated by all patients. For the entire group, TNI decreased the AHI from 40.4 ± 25.7 to 30.8 ± 25.7/h (p = 0.001) and the oxygen desaturation index >3% from 40.7 ± 28.4 to 31 ± 22.5/h (p = 0.02). All participants except one showed a decrease in AHI. The percentage of slow-wave sleep significantly increased with TNI from 16.7 ± 8.2% to 22.3 ± 7.4% (p = 0.01). There was also a trend toward a reduction in markers of sleep disruption (number of awakenings, arousal index). Conclusions: TNI improves SDB indices, and possibly sleep parameters, in stroke patients. Although these changes are modest, our findings suggest that TNI is a viable treatment alternative to CPAP in patients with SDB in the acute phase of ischemic strok

The effect of continuous positive airway pressure on total cerebral blood flow in healthy awake volunteers

Purpose: Continuous positive airway pressure (CPAP) is the gold standard treatment for obstructive sleep apnea. However, the physiologic impact of CPAP on cerebral blood flow (CBF) is not well established. Ultrasound can be used to estimate CBF, but there is no widespread accepted protocol. We studied the physiologic influence of CPAP on CBF using a method integrating arterial diameter and flow velocity (FV) measurements obtained for each vessel supplying blood to the brain. Methods: FV and lumen diameter of the left and right internal carotid, vertebral, and middle cerebral arteries were measured using duplex Doppler ultrasound with and without CPAP at 15cmH2O, applied in a random order. Transcutaneous carbon dioxide (PtcCO2), heart rate (HR), blood pressure (BP), and oxygen saturation were monitored. Results were compared with a theoretical prediction of CBF change based on the effect of partial pressure of carbon dioxide on CBF. Results: Data were obtained from 23 healthy volunteers (mean ± SD; 12 male, age 25.1 ± 2.6years, body mass index 21.8 ± 2.0kg/m2). The mean experimental and theoretical CBF decrease under CPAP was 12.5% (p < 0.001) and 11.9% (p < 0.001), respectively. The difference between experimental and theoretical CBF reduction was not statistically significant (3.84 ± 79ml/min, p = 0.40). There was a significant reduction in PtcCO2 with CPAP (p = <0.001) and a significant increase in mean BP (p = 0.0017). No significant change was observed in SaO2 (p = 0.21) and HR (p = 0.62). Conclusion: Duplex Doppler ultrasound measurements of arterial diameter and FV allow for a noninvasive bedside estimation of CBF. CPAP at 15cmH2O significantly decreased CBF in healthy awake volunteers. This effect appeared to be mediated predominately through the hypocapnic vasoconstriction coinciding with PCO2 level reduction. The results suggest that CPAP should be used cautiously in patients with unstable cerebral hemodynamic

Hormone Targets for the Treatment of Sleep Disorders in Postmenopausal Women with Schizophrenia: A Narrative Review

While the early identification of insomnia in patients with schizophrenia is of clinical relevance, the use of specific compounds to treat insomnia has been studied less in postmenopausal women with schizophrenia. We aimed to explore the effects of melatonin, sex hormones, and raloxifene for the treatment of insomnia in these populations. Although melatonin treatment improved the quality and efficiency of the sleep of patients with schizophrenia, few studies have explored its use in postmenopausal women with schizophrenia. The estrogen and progesterone pathways are dysregulated in major psychiatric disorders, such as in schizophrenia. While, in the context of menopause, a high testosterone-to-estradiol ratio is associated with higher frequencies of depressive symptoms, the effects of estradiol and other sex hormones on sleep disorders in postmenopausal women with schizophrenia has not been sufficiently investigated. Raloxifene, a selective estrogen receptor modulator, has shown positive effects on sleep disorders in postmenopausal women. Future studies should investigate the effectiveness of hormonal compounds on insomnia in postmenopausal women with schizophrenia

Spatial clusters of daytime sleepiness and association with nighttime noise levels in a Swiss general population (GeoHypnoLaus).

Daytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between noise and daytime sleepiness, little research has explored the individual-level spatial distribution of noise-related sleep disturbances. We assessed the spatial dependence of daytime sleepiness and tested whether clusters of individuals exhibiting higher daytime sleepiness were characterized by higher nocturnal noise levels than other clusters. Population-based cross-sectional study, in the city of Lausanne, Switzerland. Sleepiness was measured using the Epworth Sleepiness Scale (ESS) for 3697 georeferenced individuals from the CoLaus|PsyCoLaus cohort (period = 2009-2012). We used the sonBASE georeferenced database produced by the Swiss Federal Office for the Environment to characterize nighttime road traffic noise exposure throughout the city. We used the GeoDa software program to calculate the Getis-Ord G &lt;sub&gt;i&lt;/sub&gt; * statistics for unadjusted and adjusted ESS in order to detect spatial clusters of high and low ESS values. Modeled nighttime noise exposure from road and rail traffic was compared across ESS clusters. Daytime sleepiness was not randomly distributed and showed a significant spatial dependence. The median nighttime traffic noise exposure was significantly different across the three ESS Getis cluster classes (p &lt; 0.001). The mean nighttime noise exposure in the high ESS cluster class was 47.6, dB(A) 5.2 dB(A) higher than in low clusters (p &lt; 0.001) and 2.1 dB(A) higher than in the neutral class (p &lt; 0.001). These associations were independent of major potential confounders including body mass index and neighborhood income level. Clusters of higher daytime sleepiness in adults are associated with higher median nighttime noise levels. The identification of these clusters can guide tailored public health interventions

Respiratory Polygraphy Patterns and Risk of Recurrent Cardiovascular Events in Patients With Acute Coronary Syndrome

Introduction: Obstructive sleep apnea (OSA) severity is based on the apnea-hypopnea index (AHI). The AHI is a simplistic measure that is inadequate for capturing disease severity and its consequences in cardiovascular diseases (CVDs). Deleterious effects of OSA have been suggested to influence the prognosis of specific endotypes of patients with acute coronary syndrome (ACS). We aim to identify respiratory polygraphy (RP) patterns that contribute to identifying the risk of recurrent cardiovascular events in patients with ACS. Methods: Post hoc analysis of the ISAACC study, including 723 patients admitted for a first ACS (NCT01335087) in which RP was performed. To identify specific RP patterns, a principal component analysis (PCA) was performed using six RP parameters: AHI, oxygen desaturation index, mean and minimum oxygen saturation (SaO2), average duration of events and percentage of time with SaO2 < 90%. An independent HypnoLaus population-based cohort was used to validate the RP components. Results: From the ISAACC study, PCA showed that two RP components accounted for 70% of the variance in the RP data. These components were validated in the HypnoLaus cohort, with two similar RP components that explained 71.3% of the variance in the RP data. The first component (component 1) was mainly characterized by low mean SaO2 and obstructive respiratory events with severe desaturation, and the second component (component 2) was characterized by high mean SaO2 and long-duration obstructive respiratory events without severe desaturation. In the ISAACC cohort, component 2 was associated with an increased risk of recurrent cardiovascular events in the third tertile with an adjusted hazard ratio (95% CI) of 2.44 (1.07 to 5.56; p-value = 0.03) compared to first tertile. For component 1, no significant association was found for the risk of recurrent cardiovascular events. Conclusion: A RP component, mainly characterized by intermittent hypoxemia, is associated with a high risk of recurrent cardiovascular events in patients without previous CVD who have suffered a first ACS.Instituto de Salud Carlos III (ISCIII; PI10/02763, PI10/02745, PI18/00449, and PI19/00907), co-funded by FEDER, “Una manera de hacer europa,” IRBLleida – Fundació Pifarré, CERCA Programme/Generalitat de Catalunya, SEPAR, ResMed Ltd. (Australia), Esteve-Teijin (Spain), Oxigen Salud (Spain), Associació Lleidatana de Respiratori (ALLER), and Sociedad Española de Sueño (SES). AZ is the recipient of a predoctoral fellowship “Ajuts 2021 de Promoció de la Recerca en Salut-9a edició” from IRBLleida/Diputació de Lleida. JD acknowledges receiving financial support from ISCIII (Miguel Servet 2019: CP19/00108), co-funded by the European Social Fund (ESF), “Investing in your future.” MS-d-l-T has received financial support from a “Ramón y Cajal” grant (RYC2019-027831-I) from the “Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación” co-funded by the European Social Fund (ESF)/“Investing in your future.” FB received funding from from ResMed (an Australian company that develops products related to sleep apnea), the Health Research Fund, the Spanish Ministry of Health, the Spanish Respiratory Society, the Catalonian Cardiology Society, Esteve-Teijin (Spain), Oxigen Salud (Spain), and ALLER. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication

Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning

Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of poorly defined diseases with excessive daytime sleepiness as a core feature. Due to the considerable overlap of symptoms and the rarity of the diseases, it is difficult to identify distinct phenotypes of CH. Machine learning (ML) can help to identify phenotypes as it learns to recognize clinical features invisible for humans. Here we apply ML to data from the huge European Narcolepsy Network (EU-NN) that contains hundreds of mixed features of narcolepsy making it difficult to analyze with classical statistics. Stochastic gradient boosting, a supervised learning model with built-in feature selection, results in high performances in testing set. While cataplexy features are recognized as the most influential predictors, machine find additional features, e.g. mean rapid-eye-movement sleep latency of multiple sleep latency test contributes to classify NT1 and NT2 as confirmed by classical statistical analysis. Our results suggest ML can identify features of CH on machine scale from complex databases, thus providing 'ideas' and promising candidates for future diagnostic classifications.</p

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles

Characteristics and Determinants of Respiratory Event-Associated Leg Movements

Abstract Study Objectives To (1) replicate the recently described distribution of respiratory event-associated leg movements (rLMs) in participants with mild-to-moderate obstructive sleep apnea syndrome (OSAS), (2) explore global and local factors associated with the presence of rLMs, and (3) investigate differences related to OSAS severity and periodic leg movements during sleep (PLMS) status. Methods We randomly selected six groups of participants without restless legs syndrome (12-15 participants in each group), stratified by apnea-hypopnea index (AHI) severity (AHI 10-20, 20-30, and 30-40) and PLMS status (PLMS index 15 per hr) from the population-based HypnoLaus study that assessed full polysomnography at home in participants aged 40 to 80 years, randomly selected from the population register of the city of Lausanne, Switzerland. Results Our results confirmed the distribution of leg movement activity at the end of respiratory events (−2.0 to +10.25 s). Mixed effects logistic regression modeling rLM-probability showed that rLMs were more frequent in participants with high-PLMS, at the end of obstructive apneas (vs. hypopneas) and in the presence of arousals at the end of the events. In participants with high-PLMS, rLM-probability decreased with time of night and was more reduced during REM sleep (vs. NREM sleep), whereas the duration of the respiratory event had a significant effect only in participants with low-PLMS. Conclusions We confirm the previously reported distribution of rLMs in participants with mild-to-moderate OSAS and our results suggest that rLMs are sensitive to both sleep-related and respiratory-related factors in a complex interaction with the PLMS status