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. 2016 Jun;18(6):925-44.
doi: 10.1093/europace/euv405. Epub 2016 Jan 27.

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

Affiliations

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

Mathias Baumert et al. Europace. 2016 Jun.

Abstract

This consensus guideline discusses the electrocardiographic phenomenon of beat-to-beat QT interval variability (QTV) on surface electrocardiograms. The text covers measurement principles, physiological basis, and clinical value of QTV. Technical considerations include QT interval measurement and the relation between QTV and heart rate variability. Research frontiers of QTV include understanding of QTV physiology, systematic evaluation of the link between QTV and direct measures of neural activity, modelling of the QTV dependence on the variability of other physiological variables, distinction between QTV and general T wave shape variability, and assessing of the QTV utility for guiding therapy. Increased QTV appears to be a risk marker of arrhythmic and cardiovascular death. It remains to be established whether it can guide therapy alone or in combination with other risk factors. QT interval variability has a possible role in non-invasive assessment of tonic sympathetic activity.

Keywords: Autonomic nervous system; ECG; Heart rate variability; QT interval variability; Repolarization; Sympathetic activity.

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Figures

Figure 1
Figure 1
Example traces of RR (left) and QT intervals (right) of a normal subject (A) in comparison to a patient following MI (B), demonstrating augmented beat-to-beat QT variability after MI despite the reduction in HRV (unpublished data).
Figure 2
Figure 2
Inverse relation between T wave amplitude and QT variability. Data were obtained from 2-min, 12-lead ECG of 69 healthy subjects.
Figure 3
Figure 3
Power spectra l density (PSD) of RR (left) and QT series (right) at rest in supine position (A) and during 90° head-up tilt (B) (unpublished data).
Figure 4
Figure 4
Left panels: squared coherence function between RR and QT series. Right panels: gain (red lines) and phase (green lines) of the transfer function from RR variability to QTV. The top row (A) shows results at rest in supine position and the bottom row (B) during 90° head-up tilt (unpublished data).
Figure 5
Figure 5
Decomposition of QTV into partial processes due to RR variability, respiration, and noise at rest (A) and during 90° head-up tilt (B) (unpublished data).Var, variance
Figure 6
Figure 6
Example traces of RR (in red) and QT intervals (in green) in a patient during spontaneous sinus rhythm and during right atrial pacing at different rates, illustrating the rate adaption of the QT interval and residual QT variability in the absence of RR interval variability (unpublished data).
Figure 7
Figure 7
Reported values of QTVi (top) and SDQT (bottom). Data are presented as mean and standard deviations. The size of the circle indicates sample size. (Two studies were excluded due to reported methodical differences in the QT interval extraction that lead to very small SDQT values.),

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