QT interval variability in body surface ECG: measurement, physiological basis, and clinical value: position statement and consensus guidance endorsed by the European Heart Rhythm Association jointly with the ESC Working Group on Cardiac Cellular Electrophysiology

Baumert, Mathias; Porta, Alberto; Vos, Marc A.; Malik, Marek; Couderc, Jean Philippe; Laguna, Pablo; Piccirillo, Gianfranco; Smith, Godfrey L.; Tereshchenko, Larisa G.; Volders, Paul G.A.

doi:10.1093/europace/euv405

Cited by 194 publications

(299 citation statements)

References 226 publications

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“…However, permission to use this material for any other purposes must be obtained from the IEEE by sending an email to pubs-permissions@ieee.org. lead to SCD [2], and increased spatio-temporal repolarization variability has been linked to increased arrhythmic risk [3] in both beat-to-beat (short-term) scenarios [4,5], and when measuring at different stable heart rates [6,7]. The T-wave on the electrocardiogram (ECG) reflects the spatiotemporal dispersion of repolarization times of the ventricular myocites, with homogeneous increments of this dispersion being reflected as both linear and non-linear variations of the T-wave width and amplitude, and enhanced heterogeneities being manifested as additional non-linear deformations of the T-wave, such as notches or asymmetries [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Previous techniques developed to investigate cardiac repolarization from the surface ECG were based on interval repolarization durations and have been shown to reflect spatiotemporal repolarization heterogeneity [11,12], such as the QT interval, its corrected version [13], T-wave width [14], the distance from the peak to the end of the T wave (T pe interval) [15], the dynamic changes in the T pe interval with respect to the heart rhythm [16], the variability of the QT interval [3], the T-wave alternans [17], or the ST elevation [18]. However, these markers might not be able to capture both linear and non-linear T-wave morphological variations, and extracting such information may provide improved ventricular arrhythmic risk.…”

Section: Introductionmentioning

confidence: 99%

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Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves

Ramírez

Orini

Tucker

et al. 2017

IEEE Trans. Biomed. Eng.

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109

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Abstract-Objective: We propose two electrocardiogram (ECG)-derived markers of T-wave morphological variability in the temporal, dw, and amplitude, da, domains. Two additional markers, d NL w and d NL a , restricted to measure the non-linear information present within dw and da are also proposed. Methods: We evaluated the accuracy of the proposed markers in capturing T-wave time and amplitude variations in 3 situations: (1) In a simulated set up with presence of additive Laplacian noise, (2) when modifying the spatio-temporal distribution of electrical repolarization with an electro-physiological cardiac model and (3) in ECG records from healthy subjects undergoing a tilt table test. Results: The metrics dw, da, d NL w and d NL a followed T-wave time and amplitude induced variations under different levels of noise, were strongly associated with changes in the spatiotemporal dispersion of repolarization, and showed to provide additional information to differences in the heart rate, QT and Tpe intervals, and in the T-wave width and amplitude. Conclusion: The proposed ECG-derived markers robustly quantify T-wave morphological variability, being strongly associated with changes in the dispersion of repolarization. Significance: The proposed ECG-derived markers can help to quantify the variability in the dispersion of ventricular repolarization, showing a great potential to be used as arrhythmic risk predictors in clinical situations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves

Ramírez

Orini

Tucker

et al. 2017

IEEE Trans. Biomed. Eng.

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109

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“…The predictive value of this new marker of T-wave variability will be assessed in future studies to determine whether it may improve or complement existing markers [2,10].…”

Section: Discussionmentioning

confidence: 99%

“…Variabilities in such spatiotemporal repolarization heterogeneities are associated with increased arrhythmic risk [2], and this motivates the quantification of the variations of the amplitude of the Twave. However, those repolarization heterogeneities, or other physiological situations like changes in the heart rate, might induce variabilities in the temporal domain (such as stretches and translations of the T-wave) that need to be separated (warped) from the variability along the amplitude domain.…”

Section: Introductionmentioning

confidence: 99%

An Index for T:wave Pointwise Amplitude Variability Quantification

Ramírez

Orini

Tucker

et al. 2016

2016 Computing in Cardiology Conference (CinC)

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The comparison between the pointwise amplitude of different T-waves provides insight into ventricular repolarization liability. However, T-wave pointwise amplitude variability can be confounded by time-domain variability. We, first, compared two algorithms for removing (warping) time-domain variability, one using the original and another one using a transformed T-wave (SRSF). We, next, compared the robustness against noise of two markers, d y and d a , of pointwise amplitude variability, after warping the underlying temporal variability with the preferred warping algorithm. d y was obtained from the transformed T-waves while d a was proposed in this work and was derived from the original T-waves. We, finally, used the most robust marker to measure the T-wave pointwise amplitude variability between every T-wave recorded during a Tilt test and their mean T-wave. Results showed that the preferred warping algorithm was the SRSF because it is not affected by differences between the amplitudes of the original T-waves. In addition, the marker d a presented lower relative error values than d y for every level of noise. The analysis of electrocardiogram records showed that d a was significantly lower during the tilt than in supine position (-5.5 % vs 6.5 %, p<0.01). In conclusion, d a robustly quantifies physiological variabilities of the T-wave amplitude, showing its potential to be used as an arrhythmic risk predictor in future clinical situations.

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“…Undoubtedly, cardiac muscle abnormalities in myotonic dystrophy lead to repolarization changes and, perhaps next time, these should be properly addressed by the battery of focused and validated methods ranging from the spatial QRS-T angle to the T wave temporal variability [6]. However, in any case, we do not understand why any spatial cardiac electrophysiology abnormalities should be interpreted as a suggestion of autonomic dysfunction.…”

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confidence: 97%

The purpose of heart rate variability measurements

et al. 2017

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It is well known and has been repeatedly published [1,2] that analyses of heart rate variability (HRV) offer an insight into the autonomic modulations of cardiac periodicity and might thus be used to study autonomic responsiveness. This makes HRV investigations useful for the characterization of autonomic dysfunction as well as for risk stratification.Both these goals have distinct specifics. Detection of primary autonomic abnormalities is best achieved by wellcontrolled short-term recordings obtained under provocative conditions, such as the head-up tilt test, the postural test, and other well-defined autonomic provocations during which continuous electrocardiographic recordings (ECG) are made. In most quantifications of primary autonomic dysfunction, it is also advantageous to accompany continuous ECG by simultaneous continuous recordings of blood pressure, e.g. by plethysmography, and of respiration, e.g. by end-tidal CO 2 , chest belt or chest impedance measurements. If these signals are obtained under stationary conditions of different autonomic provocative stages (e.g. different tilt inclinations), standard spectral [1] and coherence analyses of the ECG and blood pressure records, as well as novel signal processing advances [2], allow not only the quantifying of the differences between the different provocation stages but also measuring the influences that the provocations have on the separate limbs of the autonomic nervous system, on the baroreflex, and on other autonomic-based regulatory processes.Since the autonomic nervous system reflects the homeostasis of the whole organism, HRV suppression in controlled short-term recordings (e.g. the absence of respiratory sinus arrhythmia) also signifies increased risk.

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QT interval variability in body surface ECG: measurement, physiological basis, and clinical value: position statement and consensus guidance endorsed by the European Heart Rhythm Association jointly with the ESC Working Group on Cardiac Cellular Electrophysiology

Cited by 194 publications

References 226 publications

Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves

Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves

An Index for T:wave Pointwise Amplitude Variability Quantification

The purpose of heart rate variability measurements

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