Weill Cornell Center for Sleep Medicine
New York, 10065, United States
NCT Number: NCT02188498
The objective of this study is to determine if a non-invasive technique, using an innovative analysis of electrocardiogram (ECG) data, would allow for detection of respiratory events during sleep and discrimination between central and obstructive apnea. Obstructive Sleep Apnea (OSA) is the most common respiratory disturbance seen during sleep, with an estimated prevalence of 10 % in the population and is strongly associated with the development of cardiovascular disease. In patients with underlying cardiac disease, particularly in heart failure (HF), central respiratory events such as Cheyne-Stokes Respiration (CSR) are often seen during sleep. The presence of CSR is also associated with increased cardiovascular morbidity and mortality. Currently, the identification and classification of sleep related respiratory disturbances is performed during over-night sleep studies (polysomnography), which are labor-intensive, time-consuming, expensive and difficult for patients. Thus, the development of alternative techniques to assist in the identification of those events in the outpatient setting is of marked importance for widespread screening of sleep apnea.
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Notify Me18 year–95 year
All sexes
Observational
New York, 10065, United States
This study aims to use novel analyses of electrocardiogram data to detect the presence and type of respiratory event observed in patients during sleep. Our specific aims include: determining the accuracy of using a non-invasive electrocardiogram (ECG) to detect sleep apnea and to distinguish between obstructive sleep apnea (OSA) and Cheyne-Stokes Respiration (CSR). For this investigator-initiated study, data from approximately 400 consecutive patients presenting to the Weill Cornell Center for Sleep Medicine for polysomnography will be collected. A sample size of 45 subjects in each group will be needed to quantify mean amplitude change in the ECG derived respiratory signal. Study procedures are outlined below. Standard and novel, research measurements from the ECG will be correlated with findings from polysomnography and used to assess the presence and severity of a variety of ECG-based measures of cardiovascular disease, such as left ventricular hypertrophy and prior Q-wave myocardial infarction. Subjects will also have to complete a Questionnaire prior to their ECG at their visit.
Detailed procedures:
Upon completion of data attainment some de-identified data will be remote analyzed.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Polysomnography, also called a sleep study, is a test used to diagnose sleep disorders. Polysomnography records your brain waves, the oxygen level in your blood, heart rate and breathing, as well as eye and leg movements during the study.
Time frame: One night of sleep study
The variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.
Time frame: One night of sleep study
The variation in the QRS waves.
Time frame: One night of sleep study
Variation and analysis in the ecg signal.
Weill Medical College of Cornell University
Other
Acronym: Holter
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