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Updated: Dec 29, 2025

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
Published on: August 17, 2022
Alterations in heart rate variability are associated with abnormal myocardial perfusion
Anish S Shah1, Rachel Lampert2, Jack Goldberg3
1Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States of America.
Background:
Abnormalities in the autonomic nervous system may occur in ischemic heart disease, but the mechanisms by which they are linked are not fully defined. The risk of cardiac events is increased during morning hours. Studying the contributions of autonomic mechanisms may yield insights into risk stratification and treatment. We hypothesize that autonomic dysfunction, measured by decreased heart rate variability (HRV), associates with abnormal stress myocardial perfusion imaging (MPI).
Methods:
We performed a cross-sectional study of the association between abnormal myocardial stress perfusion with HRV using 276 middle-aged veteran twins without known ischemic heart disease. The primary independent variable was cardiac autonomic regulation measured with 24-hour electrocardiogram (ECG) monitoring, using linear and non-linear (multipole density, or Dyx) HRV metrics. The primary outcome was abnormal perfusion (>5% affected myocardium) during adenosine stress on [13N]-ammonia myocardial perfusion imaging with positron emission tomography.
Results:
The mean (SD) age was 53 (3) years and 55 (20%) had abnormal perfusion. HRV (by Dyx) was reduced during morning hours in subjects with abnormal perfusion. At 7 AM, each standard deviation (SD) decrease in Dyx was associated a 4.8 (95% CI, 1.5 - 15.8) odds ratio (OR) for abnormal MPI. With Dyx < 2.0, the 7 AM OR for abnormal MPI was 11.8 (95% CI, 1.2 - 111.4).
Conclusions:
Autonomic dysfunction, measured by non-linear HRV in the morning hours, was associated with an increased OR of abnormal MPI. These results suggest a potentially important role of ECG-based biomarkers in risk stratification for individuals with suspected ischemic heart disease.
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