Sleep complaints are reported by 40–60 % of menopausal women. Poor sleep is a risk factor for cardiovascular disease, diabetes, and obesity. The effect of menopausal hormone therapy on sleep quality is unclear. A systematic review and meta-analysis were conducted to summarize the efficacy of menopausal hormone therapy on self-reported sleep quality. Electronic databases (PubMed, Scopus, Ovid MEDLINE, EMBASE, EBM Reviews CENTRAL, and Psyclnfo) were searched from 2002 to October 2015. Randomized trials assessing the effect of menopausal hormone therapy with a minimum follow up of 8 weeks were included. Titles, abstracts, and full texts were screened independently and in duplicate. Primary outcome included sleep items within a questionnaire, scale or diary. Standardized mean differences across trials were pooled using random-effects models. The search identified 424 articles, from which 42 trials were included. Seven trials at a moderate to high risk of bias enrolling 15,468 women were pooled in meta-analysis. Menopausal hormone therapy improved sleep quality in women who had vasomotor symptoms at baseline [standardized mean difference −0. 54 (−0. 91 to −0. 18), moderate quality evidence]. No difference was noted when women without such symptoms were analyzed separately or combined. Across 31 sleep quality questionnaires, daytime dysfunction was the most evaluated sleep domain. Menopausal hormone therapy improves sleep in women with concomitant vasomotor symptoms. Heterogeneity of trials regarding study population, formulations, and sleep scales; limit overall certainty in the evidence. Future menopausal hormone therapy trials should include assessment of self-reported sleep quality using standardized scales and adhere to reporting guidelines.

There are currently no effective biomarkers for diagnosing Parkinson’s disease (PD) or tracking its progression. Here, we developed an artificial intelligence (AI) model to detect PD and track its progression from nocturnal breathing signals. The model was evaluated on a large dataset comprising 7,671 individuals, using data from several hospitals in the United States, as well as multiple public datasets. The AI model can detect PD with an area-under-the-curve of 0.90 and 0.85 on held-out and external test sets, respectively. The AI model can also estimate PD severity and progression in accordance with the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (R = 0.94, P = 3.6 × 10–25). The AI model uses an attention layer that allows for interpreting its predictions with respect to sleep and electroencephalogram. Moreover, the model can assess PD in the home setting in a touchless manner, by extracting breathing from radio waves that bounce off a person’s body during sleep. Our study demonstrates the feasibility of objective, noninvasive, at-home assessment of PD, and also provides initial evidence that this AI model may be useful for risk assessment before clinical diagnosis.

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There appears to be a strong association between obstructive sleep apnea (OSA) and cardioembolic (CE) stroke. In patients with OSA presenting with cryptogenic stroke, high clinical suspicion for CE is warranted. This may lead to consideration of diagnostic studies to identify CE risk factors such as paroxysmal atrial fibrillation (AF). CE strokes are more common in patients with OSA even after adjusting for AF. This finding may reflect a high rate of occult paroxysmal AF in this population; alternatively, OSA may lead to CE strokes through mechanisms independent of AF.

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Study Objectives Isolated REM sleep behavior disorder (iRBD) carries a high lifetime risk for phenoconversion to a defined neurodegenerative disease (NDD) including Parkinson disease, dementia with Lewy bodies, and multiple system atrophy. We aimed to examine iRBD patient values and preferences regarding prognostic counseling. Methods 113 iRBD patient participants with enrolled in the Mayo Clinic iRBD Patient Registry were sent an email survey concerning their values and preferences concerning NDD prognostic counseling and their experiences following diagnosis with iRBD. Results Of 81 respondents (71.7% response rate), the majority were men (74.0%) with an average age of 65.7 (±9.7) years. Responses indicated a strong preference toward receiving prognostic information about possible future NDD development. 92.5% of respondents felt knowledge concerning personal NDD risk was important, while 87.6% indicated prognostic discussions were important to maintaining trust in their physician. 95.7% indicated a desire for more information, while only 4.3% desired less information regarding their NDD prognostic risk. Most respondents strongly agreed that prognostic information was important to discuss with their family and friends and inform future life planning, and most expressed interest in learning more about future neuroprotective therapies and symptomatic treatments for parkinsonism and dementia. Conclusions Most iRBD patients indicated strong preferences for disclosure of NDD prognostic risk and indicated that prognostic information was important for family discussions and future life planning. Future broader surveys and qualitative studies of clinic-based and ultimately community dwelling iRBD patients’ values and preferences are needed to guide appropriately tailored and individualized prognostic counseling approaches following iRBD diagnosis.

Background Obstructive sleep apnea (OSA) has been shown to be an independent risk factor for ischemic stroke and may increase the risk of atrial fibrillation (AF) by up to four-fold. Given these relationships, it is possible that OSA may provide a link between stroke and AF. A case-control study was conducted to examine the association between AF and stroke in patients with OSA. Methods Olmsted county, MN, USA, residents with a new diagnosis of OSA based on polysomnography (PSG) between 2005 and 2010 (N=2980) who suffered a first-time ischemic stroke during the same period were identified as cases. Controls with no history of stroke were randomly chosen from the same database. Univariate and multiple logistic regression analyses were performed with age, gender, body mass index (BMI), smoking, hypertension, hyperlipidemia, diabetes mellitus, apnea-hypopnea index (AHI) and coronary artery disease as co-variates, with the diagnosis of AF as the variable of interest. Results A total of 108 subjects were studied. Mean age of cases (n=34) was 73 ±12 years and 53% were men. Among controls (n=74), mean age was 61 ±16 years and 55% were male. On univariate analyses, AF was significantly more common in the cases than among controls (50.0% vs 10.8%, p<0.01). On multivariate regression analyses, the association between AF and stroke was significant after controlling for age, BMI, coronary artery disease, hypertension, diabetes mellitus, hyperlipidemia and smoking status (corrected OR: 5.34; 95% CI: 1.79-17.29). Conclusions Patients with OSA who had a stroke had higher rates of AF even after accounting for potential confounders.