Status
Conditions
Treatments
About
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.
Full description
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.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
120 participants in 1 patient group
Loading...
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal