Objective: Depression and sleep apnea (SA) are common among patients with a recent acute myocardial infarction (AMI), and both are associated with increased risk for adverse outcomes. We tested the hypothesis that there is an interaction between them in relation to post-AMI prognosis.
Methods: Participants were patients with a recent AMI, 337 of them were depressed and 379 were nondepressed, who participated in a substudy of the Enhancing Recovery in Coronary Heart Disease (ENRICHD) clinical trial.
Purpose: Sleep-disordered breathing (SDB) is associated with increased risk for cardiovascular morbidity and mortality and for sleepiness-related accidents, but >75 % of the patients remain undiagnosed. We sought to determine the diagnostic accuracy of ECG-based detection of SDB when used for population-based screening.
Methods: All male workers, mostly truck drivers, of a transport company (n = 165; age, 43 ± 12 years) underwent standard attended overnight polysomnography.
Annu Int Conf IEEE Eng Med Biol Soc
May 2012
Cyclic variation of heart rate (CVHR) associated with sleep apnea/hypopnea episodes has been suggested as a marker of sleep disordered breathing (SDB). This study examined the utility of ECG-based CVHR detection for diagnosing SDB using simultaneous polysomnography as the reference standard. We used a previously developed automated CVHR detection algorithm (autocorrelated wave detection with adaptive threshold, ACAT) that provides the number of CVHR per hour (CVHR index).
View Article and Find Full Text PDFCirc Arrhythm Electrophysiol
February 2011
Background: Despite the adverse cardiovascular consequences of obstructive sleep apnea, the majority of patients remain undiagnosed. To explore an efficient ECG-based screening tool for obstructive sleep apnea, we examined the usefulness of automated detection of cyclic variation of heart rate (CVHR) in a large-scale controlled clinical setting.
Methods And Results: We developed an algorithm of autocorrelated wave detection with adaptive threshold (ACAT).