The role of β-adrenergic stimulation in QT interval adaptation to heart rate during stress test

Characterization of QT-Interval Adaptation Time Lag in Response to Sport-Induced Heart Rate Changes Measured From Wearable ECG Recordings

OBJECTIVES

Elevated heterogeneity in ventricular repolarization can promote malignant ventricular arrhythmias. During exercise, distinct ventricular cells may present different repolarization adaptation to heart-rate (HR) changes potentially increasing ventricular repolarization dispersion. An electrocardiographic descriptor of the temporal adaptation of action potential duration to HR changes is the time delay the QT interval takes in accommodating to abrupt acceleration and deceleration in HR. Previous investigations have been performed on standard electrocardiograms acquired during stress tests. The present work aims to characterize the time delay of QT-interval accommodation to HR changes for a healthy trained population during real training.

METHODS

The time delay was estimated through an optimally derived, model-based time-delay estimator as the lag between the actual QT series and an HR-derived expected memoryless QT series. The last one was obtained by fitting a logarithmic regression model to the instantaneous QT and HR measurements in assumed stationary time windows. The QT lag was estimated separately in HR acceleration, and HR deceleration, of single-lead ECG acquired through a chest strap while practicing sport.

RESULTS

The QT-adaptation time lag estimated during HR deceleration is longer than during HR acceleration, especially after intense physical exertion of athletes when they have overcome their theoretical maximal HR 14.5[2.4;28.0] s or they have been involved in dynamic sports 9.9[5.8;24.9] s.

CONCLUSION

Higher repolarization dispersion can be captured by the proposed time delay biomarker in a distinctive way to the HR acceleration.

SIGNIFICANCE

Eventually the time lag is a biomarker for exacerbated increase of ventricular repolarization dispersion while exercising.

Performance Evaluation of QT-RR Adaptation Time Lag Estimation in Exercise Stress Testing

BACKGROUND

Slower adaptation of the QT interval to sudden changes in heart rate has been identified as a risk marker of ventricular arrhythmia. The gradual changes observed in exercise stress testing facilitates the estimation of the QT-RR adaptation time lag.

METHODS

The time lag estimation is based on the delay between the observed QT intervals and the QT intervals derived from the observed RR intervals using a memoryless transformation. Assuming that the two types of QT interval are corrupted with either Gaussian or Laplacian noise, the respective maximum likelihood time lag estimators are derived. Estimation performance is evaluated using an ECG simulator which models change in RR and QT intervals with a known time lag, muscle noise level, respiratory rate, and more. The accuracy of T-wave end delineation and the influence of the learning window positioning for model parameter estimation are also investigated.

RESULTS

Using simulated datasets, the results show that the proposed approach to estimation can be applied to any changes in heart rate trend as long as the frequency content of the trend is below a certain frequency. Moreover, using a proper position of the learning window for exercise so that data compensation reduces the effect of nonstationarity, a lower mean estimation error results for a wide range of time lags. Using a clinical dataset, the Laplacian-based estimator shows a better discrimination between patients grouped according to the risk of suffering from coronary artery disease.

CONCLUSIONS

Using simulated ECGs, the performance evaluation of the proposed method shows that the estimated time lag agrees well with the true time lag.

Model-based Estimators of QT Series Time Delay in Following Heart-Rate Changes

Sudden cardiac death is the leading cause of death among cardiovascular diseases. Markers for patient risk stratification focusing on QT-interval dynamics in response to heart-rate (HR) changes can be characterized in terms of parametric QT to RR dependence and QT/RR hysteresis. The QT/RR hysteresis can be quantified by the time delay the QT interval takes to accommodate for the HR changes. The exercise stress test has been proposed as a proper test, with large HR dynamics, to evaluate the QT/RR hysteresis. The present study aims at evaluating several time-delay estimators based on noise statistic (Gaussian or Laplacian) and HR changes profile at stress test (gradual transition change). The estimator's performance was assessed on a simulated QT transition contaminated by noise and in a clinical study including patients affected by coronary arteries disease (CAD). As expected, the Laplacian and Gaussian estimators yield the best results when noise follows the respective distribution. Further, the Laplacian estimator showed greater discriminative power in classifying different levels of cardiac risk in CAD patients, suggesting that real data fit better the Laplacian distribution than the Gaussian one. The Laplacian estimator appears to be the choice for time-delay estimation of QT/RR hysteresis lag in response to HR changes in stress test.Clinical Relevance-The proposed time-delay estimator of QT/RR hysteresis lag improves its significance as biomarkers for coronary artery diseases risk stratification.