Key result
The automatic wavelet-based algorithm demonstrated that T-wave amplitude decreased significantly with atropine compared to baseline (p=0.005), confirming TWA as a marker of ventricular innervation.
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Why the study?
Does a new wavelet-based ECG delineator accurately measure T-wave amplitude to evaluate autonomic ventricular innervation in healthy subjects?
Does a new wavelet-based ECG delineator accurately measure T-wave amplitude to evaluate autonomic ventricular innervation in healthy subjects?
p-value: p=0.005
A novel wavelet-based algorithm accurately delineates ECG features and automatically calculates T-wave amplitude, which responds to autonomic blockade, supporting its use as a non-invasive marker of ventricular innervation.
Supports automated TWA assessment of innervation; leaves open clinical utility pending prospective validation.
T-wave amplitude (TWA) has been proposed as a marker of the innervation of the myocardium. Until now, TWA has been calculated manually or with poor algorithms, thus making its use not efficient in a clinical environment. We introduce a new wavelet-based algorithm for the delineation QRS complexes and T-waves, and the automatic calculation of TWA. When validated in the MIT/BIH Arrhythmia database, the QRS detector achieved sensitivity and positive predictive value of 99.84% and 99.87%, respectively. The algorithm was validated also on the QT database and it achieved sensitivity of 99.50% for T-peak detection. In addition, the algorithm achieved delineation accuracy that is similar to the differences in delineation between expert cardiologists. We applied the algorithm for the evaluation of the influence in TWA of anticholinergic and antiadrenergic drugs (i.e., atropine and metoprolol) for healthy subjects. We found that the TWA decreased significantly with atropine and that metoprolol caused a significant increase in TWA, thus confirming the clinical hypothesis that the TWA is a marker of the innervation of the myocardium. The results of this paper show that the proposed algorithm can be used as a useful and efficient tool in clinical practice for the automatic calculation of TWA and its interpretation as a non-invasive marker of the autonomic ventricular innervation.
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Cesari et al. (2017) studied Healthy (n=8). Atropine and metoprolol vs. Isotonic saline was evaluated on Normalized T-wave amplitude (TWA) change from baseline (p=0.005). The automatic wavelet-based algorithm demonstrated that T-wave amplitude decreased significantly with atropine compared to baseline (p=0.005), confirming TWA as a marker of ventricular innervation.
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