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Open AccessJournal ArticleDOI

Obstructive Sleep Apnea and Risk of Cardiovascular Events and All-Cause Mortality: A Decade-Long Historical Cohort Study

TLDR
The association between physiological measures of obstructive sleep apnea other than the apnea-hypopnea index and the risk of cardiovascular events is explored.
Abstract
Background: Obstructive sleep apnea (OSA) has been reported to be a risk factor for cardiovascular (CV) disease. Although the apnea-hypopnea index (AHI) is the most commonly used measure of OSA, other less well studied OSA-related variables may be more pathophysiologically relevant and offer better prediction. The objective of this study was to evaluate the relationship between OSA-related variables and risk of CV events. Methods and Findings: A historical cohort study was conducted using clinical database and health administrative data. Adults referred for suspected OSA who underwent diagnostic polysomnography at the sleep laboratory at St Michael’s Hospital (Toronto, Canada) between 1994 and 2010 were followed through provincial health administrative data (Ontario, Canada) until May 2011 to examine the occurrence of a composite outcome (myocardial infarction, stroke, congestive heart failure, revascularization procedures, or death from any cause). Cox regression models were used to investigate the association between baseline OSA-related variables and composite outcome controlling for traditional risk factors. The results were expressed as hazard ratios (HRs) and 95% CIs; for continuous variables, HRs compare the 75th and 25th percentiles. Over a median follow-up of 68 months, 1,172 (11.5%) of 10,149 participants experienced our composite outcome. In a fully adjusted model, other than AHI OSA-related variables were significant independent predictors: time spent with oxygen saturation ,90% (9 minutes versus 0; HR=1.50, 95% CI 1.25–1.79), sleep time (4.9 versus 6.4 hours; HR=1.20, 95% CI 1.12–1.27), awakenings (35 versus 18; HR=1.06, 95% CI 1.02–1.10), periodic leg movements (13 versus 0/ hour; HR=1.05, 95% CI 1.03–1.07), heart rate (70 versus 56 beats per minute [bpm]; HR=1.28, 95% CI 1.19–1.37), and daytime sleepiness (HR=1.13, 95% CI 1.01–1.28).The main study limitation was lack of information about continuous positive airway pressure (CPAP) adherence. Conclusion: OSA-related factors other than AHI were shown as important predictors of composite CV outcome and should be considered in future studies and clinical practice. Please see later in the article for the Editors’ Summary.

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Journal ArticleDOI

Sleep Duration and Quality: Impact on Lifestyle Behaviors and Cardiometabolic Health: A Scientific Statement From the American Heart Association

TL;DR: The evidence relating sleep duration and sleep disorders to cardiometabolic risk is reviewed and it is called for health organizations to include evidence-based sleep recommendations in their guidelines for optimal health.
Journal ArticleDOI

Nocturnal hypoxaemia is associated with increased mortality in stable heart failure patients.

TL;DR: Hypoxaemic burden was a robust and independent predictor of all-cause mortality in chronic stable HF-REF patients, and whether or not targeting nocturnal hypoxaemia is associated with beneficial effects on mortality in HF-ref patients remains to be determined.
Journal ArticleDOI

Obstructive Sleep Apnea and Incident Diabetes. A Historical Cohort Study

TL;DR: Among people with OSA, and controlling for multiple confounders, initial OSA severity and its physiologic consequences predicted subsequent risk for incident diabetes.
Journal ArticleDOI

Obstructive sleep apnoea syndrome and its management

TL;DR: After more than three decades from its first use, continuous positive airway pressure (CPAP) is still recognized as the gold standard treatment and is highly effective in controlling symptoms, improving quality of life and reducing the clinical sequelae of sleep apnoea.
References
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Multiple imputation for nonresponse in surveys

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TL;DR: In this article, the authors present a case study in least squares fitting and interpretation of a linear model, where they use nonparametric transformations of X and Y to fit a linear regression model.

Multiple Imputation For Nonresponse In Surveys

TL;DR: The multiple imputation for nonresponse in surveys is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can download it instantly.
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Proportional hazards tests and diagnostics based on weighted residuals

TL;DR: In this article, Chen et al. showed that a treatment effect that decreases with time can be directly visualized by smoothing an appropriate residual plot, which can be expressed as a weighted least-squares line fitted to the residual plot.
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