Obstructive sleep apnea (OSA) is highly prevalent in the United States and its prevalence is increasing with the obesity epidemic1. OSA is independently associated with increased sudden cardiac death (SCD) risk2. The majority of SCD events in middle-aged adults occur without prior history of cardiovascular disease and are due to cardiac arrhythmias. There is great need for improved understanding of the pathophysiology and risk stratification of arrhythmogenic risk in individuals with OSA. Because most of these events occur during sleep, tools that can combine high-fidelity electrocardiography (ECG) data with simultaneous polysomnography information are needed to study the OSA phenotype that is at risk and to test their response to therapy. This application proposes the development of a user-friendly interface to synchronize high-fidelity 12- lead ECG recordings with polysomnography information. This software interface will permit comprehensive assessment of markers of ventricular arrhythmia susceptibility (ventricular ectopy burden, heart rate turbulence [HRT] and microvolt T-wave alternans [mTWA]) synchronous with heart rate variability (HRV) in the time and frequency domains, respiratory events, degree of hypoxia, sleep staging and cerebral cortical activity in individuals with OSA. We will use previously validated algorithms for calculating HRV, ventricular ectopy burden, HRT, and precordial mTWA. This analysis tool will be tested using pre-existing research data sets collected during the PIs current NHLBI K23 award (HL094760) and using data from newly recruited subjects before positive airway pressure therapy and during its titration. The study will collect pilot data for a planned R01 proposal to characterize the OSA phenotype that is at higher risk for sudden cardiac death and to study its response to PAP therapy. Our ECG-polysomnogram analysis tool will be designed to work across different vendor platforms and will provide synchronous physiologic assessment of the effects of OSA in cardiac arrhythmia risk. Understanding these associations will ultimately help tailor and monitor OSA treatment, but also be used to study sleep physiology and arrhythmogenic risk in other patient populations.

Public Health Relevance

Individuals with obstructive sleep apnea are at higher risk than the general population for life-threatening heart rhythm disorders when they sleep. We will develop a software tool that will allow us to merge electrical activity data from the heart with sleep information to identify factors associated with (i) risk of dying suddenly in people with sleep apnea and (ii) will help determine who benefits from treatment.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Small Research Grants (R03)
Project #
5R03HL133644-02
Application #
9336335
Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Tinsley, Emily
Project Start
2016-09-01
Project End
2018-08-31
Budget Start
2017-09-01
Budget End
2018-08-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715