Stroke is the leading cause of death and disability globally. Sleep disordered breathing (SDB), a potentially modifiable risk factor of stroke, is highly prevalent in stroke survivors. Evidence ...supports a causal, bidirectional relationship between SDB and stroke. SDB may increase the risk of stroke occurrence and recurrence, and worsen stroke outcome. While SDB is associated with an increased incidence of hypertension and cardiac arrhythmias, both of which are traditional stroke risk factors, SDB is also an independent risk factor for stroke. A number of characteristics of SDB may increase stroke risk, including intermittent hypoxemia, sympathetic activation, changes in cerebral autoregulation, oxidative stress, systemic inflammation, hypercoagulability, and endothelial dysfunction. On the other hand, stroke may also cause new SDB or aggravate preexisting SDB. Continuous positive airway pressure treatment of SDB may have a beneficial role in reducing stroke risk and improving neurological outcome after stroke. The treatment should be considered as early as possible, particularly when SDB is present post-stroke. The goal of this review is to highlight the strong link between SDB and stroke and to raise awareness for practitioners to consider the possibility of SDB being present in all stroke survivors.
Abstract
Three recent randomized control trials (RCTs) found that treatment of obstructive sleep apnea (OSA) with continuous positive airway pressure (CPAP) did not reduce rates of future ...cardiovascular events. This article discusses the biases in these RCTs that may explain their negative results, and how to overcome these biases in future studies.
First, sample selection bias affected each RCT. The subjects recruited were not patients typically presenting for treatment of OSA. In particular, subjects with excessive sleepiness were excluded due to ethical concerns. As recent data indicate that the excessively sleepy OSA subtype has increased cardiovascular risk, subjects most likely to benefit from treatment were excluded. Second, RCTs had low adherence to therapy. Reported adherence is lower than found clinically, suggesting it is in part related to selection bias. Each RCT showed a CPAP benefit consistent with epidemiological studies when restricting to adherent patients, but was underpowered.
Future studies need to include sleepy individuals and maximize adherence. Since it is unethical and impractical to randomize very sleepy subjects to no therapy, alternative designs are required. Observational designs using propensity scores, which are accepted by FDA for studies of medical devices, provide an opportunity. The design needs to ensure covariate balance, including measures assessing healthy user and healthy adherer biases, between regular users of CPAP and non-users. Sensitivity analyses can evaluate the robustness of results to unmeasured confounding, thereby improving confidence in conclusions. Thus, these designs can robustly assess the cardiovascular benefit of CPAP in real-world patients, overcoming biases in RCTs.
Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used ...neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage scoring, producing a hypnodensity graph-a probability distribution conveying more information than classical hypnograms. Accuracy of sleep stage scoring was validated in 70 subjects assessed by six scorers. The best model performed better than any individual scorer (87% versus consensus). It also reliably scores sleep down to 5 s instead of 30 s scoring epochs. A T1N marker based on unusual sleep stage overlaps achieved a specificity of 96% and a sensitivity of 91%, validated in independent datasets. Addition of HLA-DQB1*06:02 typing increased specificity to 99%. Our method can reduce time spent in sleep clinics and automates T1N diagnosis. It also opens the possibility of diagnosing T1N using home sleep studies.
Manual scoring of polysomnograms (PSG) is labor intensive and has considerable variance between scorers. Automation of scoring could reduce cost and improve reproducibility. The purpose of this study ...was to compare a new automated scoring system (YST-Limited, Winnipeg, Canada) with computer-assisted manual scoring.
Technical assessment.
Five academic medical centers.
N/A.
N/A.
Seventy PSG files were selected at University of Pennsylvania (Penn) and distributed to five US academic sleep centers. Two blinded technologists from each center scored each file. Automatic scoring was performed at Penn by a YST Limited technician using a laptop containing the software. Variables examined were sleep stages, arousals, and apnea-hypopnea index (AHI) using three methods of identifying hypopneas. Automatic scores were not edited and were compared to the average scores of the 10 technologists. Intraclass correlation coefficient (ICC) was obtained for the 70 pairs and compared to across-sites ICCs for manually scored results. ICCs for automatic versus manual scoring were > 0.8 for total sleep time, stage N2, and nonrapid eye movement arousals and > 0.9 for AHI scored by primary and secondary American Academy of Sleep Medicine criteria. ICCs for other variables were not as high but were comparable to the across-site ICCs for manually scored results.
The automatic system yielded results that were similar to those obtained by experienced technologists. Very good ICCs were obtained for many primary PSG outcome measures. This automated scoring software, particularly if supplemented with manual editing, may increase laboratory efficiency and standardize PSG scoring results within and across sleep centers.
Weight loss is recommended to treat obstructive sleep apnea (OSA).
To determine whether the initial benefit of intensive lifestyle intervention (ILI) for weight loss on OSA severity is maintained at ...10 years.
Ten-year follow-up polysomnograms of 134 of 264 adults in Sleep AHEAD (Action for Health in Diabetes) with overweight/obesity, type 2 diabetes mellitus, and OSA were randomized to ILI for weight loss or diabetes support and education (DSE).
Change in apnea-hypopnea index (AHI) was measured. Mean ± SE weight losses of ILI participants of 10.7 ± 0.7, 7.4 ± 0.7, 5.1 ± 0.7, and 7.1 ± 0.8 kg at 1, 2, 4, and 10 years, respectively, were significantly greater than the 1-kg weight loss at 1, 2, and 4 years and 3.5 ± 0.8 kg weight loss at 10 years for the DSE group (
values ≤ 0.0001). AHI was lower with ILI than DSE by 9.7, 8.0, and 7.9 events/h at 1, 2, and 4 years, respectively (
values ≤ 0.0004), and 4.0 events/h at 10 years (
= 0.109). Change in AHI over time was related to amount of weight loss, baseline AHI, visit year (
values < 0.0001), and intervention independent of weight change (
= 0.01). OSA remission at 10 years was more common with ILI (34.4%) than DSE (22.2%).
Participants with OSA and type 2 diabetes mellitus receiving ILI for weight loss had reduced OSA severity at 10 years. No difference in OSA severity was present between ILI and DSE groups at 10 years. Improvement in OSA severity over the 10-year period with ILI was related to change in body weight, baseline AHI, and intervention independent of weight change.
Chronic nonmalignant pain, sleep disturbances and sleep disorders are highly prevalent conditions among U.S. military veterans. Evidence summaries highlight the influence of sleep on pain outcomes in ...the general adult population but not for the military veteran population. This is a significant gap as U.S. military veterans are an exceedingly high-risk population for both chronic pain and sleep disturbances and/or disorders. We aimed to review the influence of sleep disturbances and sleep disorders on pain outcomes among veterans with chronic nonmalignant pain. A systematic scoping review was conducted using PubMed/Medline, EMBASE, Scopus, CINAHL, and PsycINFO. Twenty-six out of 1450 studies from initial search were included in this review resulting in a combined sample size of N = 923,434 participants. Sleep disturbances and sleep disorders were associated with worse pain outcomes among veterans with chronic pain. Treatment-induced sleep improvements ameliorated pain outcomes in veterans with sleep disorders and sleep disturbances. Research is indicated to address an overlooked pain treatment opportunity – that of sleep disturbance and sleep disorder management.
OBJECTIVE: To assess the risk factors for the presence and severity of obstructive sleep apnea (OSA) among obese patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: Unattended polysomnography ...was performed in 306 participants. RESULTS: Over 86% of participants had OSA with an apnea-hypopnea index (AHI) greater-than-or-equal5 events/h. The mean AHI was 20.5 ± 16.8 events/h. A total of 30.5% of the participants had moderate OSA (15 less-than or equal to AHI <30), and 22.6% had severe OSA (AHI greater-than-or-equal30). Waist circumference (odds ratio 1.1; 95% CI 1.0-1.1; P = 0.03) was significantly related to the presence of OSA. Severe OSA was most likely in individuals with a higher BMI (odds ratio 1.1; 95% CI 1.0-1.2; P = 0.03). CONCLUSIONS: Physicians should be particularly cognizant of the likelihood of OSA in obese patients with type 2 diabetes, especially among individuals with higher waist circumference and BMI.
Abstract
Study Objectives
Conventional metrics of sleep quantity/depth have serious shortcomings. Odds-Ratio-Product (ORP) is a continuous metric of sleep depth ranging from 0 (very deep sleep) to ...2.5 (full-wakefulness). We describe an ORP-based approach that provides information on sleep disorders not apparent from traditional metrics.
Methods
We analyzed records from the Sleep-Heart-Health-Study and a study of performance deficit following sleep deprivation. ORP of all 30-second epochs in each PSG and percent of epochs in each decile of ORPs range were calculated. Percentage of epochs in deep sleep (ORP < 0.50) and in full-wakefulness (ORP > 2.25) were each assigned a rank, 1–3, representing first and second digits, respectively, of nine distinct types (“1,1”, “1,2” … ”3,3”). Prevalence of each type in clinical groups and their associations with demographics, sleepiness (Epworth-Sleepiness-Scale, ESS) and quality of life (QOL; Short-Form-Health-Survey-36) were determined.
Results
Three types (“1,1”, “1,2”, “1,3”) were prevalent in OSA and were associated with reduced QOL. Two (“1,3” and “2,3”) were prevalent in insomnia with short-sleep-duration (insomnia-SSD), but only “1,3” was associated with poor sleep depth and reduced QOL, suggesting two phenotypes in insomnia-SSD. ESS was high in types “1,1” and “1,2”, and low in “1,3” and “2,3”. Prevalence of some types increased with age while in others it decreased. Other types were either rare (“1,1” and “3,3”) or high (“2,2”) at all ages.
Conclusions
The proposed ORP histogram offers specific and unique information on the underlying neurophysiological characteristics of sleep disorders not captured by routine metrics, with potential of advancing diagnosis and management of these disorders.
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