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Published on: June 28, 2019
QT variability unrelated to RR variability during stress testing for identification of coronary artery disease
Marta González Del Castillo1,2, David Hernando1,2, Michele Orini3
1I3A, University of Zaragoza, IIS Aragón, Spain.
Insights
Low-frequency oscillations in QT interval variability (QTV) unrelated to RR interval variability (RRV) can help diagnose coronary artery disease (CAD) during stress tests. These QTV changes, independent of heart rate, show promise for earlier CAD detection.
Area of Science:
- Cardiovascular Physiology
- Computational Biology
- Medical Diagnostics
Background:
- Stress test electrocardiogram (ECG) analysis is a standard but imperfect tool for diagnosing coronary artery disease (CAD).
- Autonomic nervous system alterations in CAD patients during ischemia may affect cardiac electrical activity.
- QT interval variability (QTV) reflects ventricular repolarization dynamics but is influenced by RR interval variability (RRV).
Purpose of the Study:
- To investigate if low-frequency (LF) oscillations of QTV, independent of RRV, can differentiate between patients with and without CAD during stress testing.
- To assess the diagnostic value of these RRV-independent QTV markers for CAD detection.
Main Methods:
- Analysis of stress test ECG data from 100 patients undergoing coronary angiography.
- Calculation of power spectral density of QTV unrelated to RRV using time-frequency coherence estimation.
- Evaluation of instantaneous LF power of QTV and normalized LF power of QTV unrelated to RRV.
Main Results:
- No significant differences in overall LF oscillations of QTV were found between CAD and non-CAD groups.
- LF oscillations in QTV unrelated to RRV were significantly higher in the CAD group during early exercise and late recovery phases.
- Receiver operating characteristic (ROC) analysis showed area under the curve values from 61% to 73% for these markers.
- LF power of QTV unrelated to RRV emerged as an independent predictor of CAD.
Conclusions:
- Removing RRV influence is crucial for accurate QTV analysis in stress testing for CAD.
- LF oscillations of QTV unrelated to RRV offer added value for diagnosing CAD, even from the initial stages of exercise.
- This approach enhances the diagnostic potential of stress ECG for cardiovascular disease.
Abstract:
Stress test electrocardiogram (ECG) analysis is widely used for coronary artery disease (CAD) diagnosis despite its limited accuracy. Alterations in autonomic modulation of cardiac electrical activity have been reported in CAD patients during acute ischemia. We hypothesized that those alterations could be reflected in changes in ventricular repolarization dynamics during stress testing that could be measured through QT interval variability (QTV). However, QTV is largely dependent on RR interval variability (RRV), which might hinder intrinsic ventricular repolarization dynamics. In this study, we investigated whether different markers accounting for low-frequency (LF) oscillations of QTV unrelated to RRV during stress testing could be used to separate patients with and without CAD. Power spectral density of QTV unrelated to RRV was obtained based on time-frequency coherence estimation. Instantaneous LF power of QTV and QTV unrelated to RRV were obtained. LF power of QTV unrelated to RRV normalized by LF power of QTV was also studied. Stress test ECG of 100 patients were analysed. Patients referred to coronary angiography were classified into non-CAD or CAD group. LF oscillations in QTV did not show significant differences between CAD and non-CAD groups. However, LF oscillations in QTV unrelated to RRV were significantly higher in the CAD group as compared with the non-CAD group when measured during the first phases of exercise and last phases of recovery. ROC analysis of these indices revealed area under the curve values ranging from 61 to 73%. Binomial logistic regression analysis revealed LF power of QTV unrelated to RRV, both during the first phase of exercise and last phase of recovery, as independent predictors of CAD. In conclusion, this study highlights the importance of removing the influence of RRV when measuring QTV during stress testing for CAD identification and supports the added value of LF oscillations of QTV unrelated to RRV to diagnose CAD from the first minutes of exercise. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.
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