Slow QT interval adaptation to heart rate changes in normal ambulatory subjects

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

The adaptation lag of the QT interval after heart rate (HR) has been proposed as an arrhythmic risk marker. Most studies have quantified the QT adaptation lag in response to abrupt, step-like changes in HR induced by atrial pacing, in response to tilt test or during ambulatory recordings. Recent studies have introduced novel methods to quantify the QT adaptation lag to gradual, ramp-like HR changes in stress tests by evaluating the differences between the measured QT series and an estimated, memoryless QT series obtained from the instantaneous HR. These studies have observed the QT adaptation lag to progressively reduce when approaching the stress peak, with the underlying mechanisms being still unclear. This study analyzes the contribution of β-adrenergic stimulation to QT interval rate adaptation in response to gradual, ramp-like HR changes. We first quantify the QT adaptation lag in Coronary Artery Disease (CAD) patients undergoing stress test. To uncover the involved mechanisms, we use biophysically detailed computational models coupling descriptions of human ventricular electrophysiology and β-adrenergic signaling, from which we simulate ventricular action potentials and ECG signals. We characterize the adaptation of the simulated QT interval in response to the HR time series measured from each of the analyzed CAD patients. We show that, when the simulated ventricular tissue is subjected to a time-varying β-adrenergic stimulation pattern, with higher stimulation levels close to the stress peak, the simulated QT interval presents adaptation lags during exercise that are more similar to those measured from the patients than when subjected to constant β-adrenergic stimulation. During stress test recovery, constant and time-varying β-adrenergic stimulation patterns render similar adaptation lags, which are generally shorter than during exercise, in agreement with results from the patients. In conclusion, our findings support the role of time-varying β-adrenergic stimulation in contributing to QT interval adaptation to gradually increasing HR changes as those seen during the exercise phase of a stress test.

Adaptation of ventricular repolarization time following abrupt changes in heart rate: comparisons and reproducibility of repeated atrial and ventricular pacing

Adequate adaptation of ventricular repolarization (VR) duration to changes in heart rate (HR) is important for cardiac electromechanical function and electrical stability. We studied the QT and QT_peak adaptation in response to abrupt start and stop of atrial and ventricular pacing on two occasions with an interval of at least 1 mo in 25 study subjects with permanent pacemakers. Frank vectorcardiography was used for data collection. Atrial or ventricular pacing was performed for 8 min aiming at a cycle length (CL) of 500 ms. We measured the immediate response (IR), the time constant (τ) of the exponential phase, and T90 End, the time to reach 90% change of QT and QT_peak from baseline to steady state during and after pacing. During atrial pacing, the CL decreased on average 45% from mean (SD) 944 (120) to 518 (46) ms and QT decreased on average 18% from 388 (20) to 318 (17) ms. For QT, T90 End was 103 (24) s and 126 (15) s after start versus stop of atrial pacing; a difference of 24 (27) s (P = 0.006). The response pattern was similar for τ but IR did not differ significantly between pacing start and stop. The response pattern was similar for QT_peak and also for QT and QT_peak following ventricular pacing start and stop. The coefficients of variation for repeated measures were 7%-21% for T90 End and τ. In conclusion, the adaptation of VR duration was significantly more rapid following increasing than decreasing HR and intraindividually a relatively reproducible process.NEW & NOTEWORTHY We studied the duration of ventricular repolarization (VR) adaptation and its hysteresis, following increasing and decreasing heart rate by abrupt start and stop of 8-min atrial or ventricular pacing in study subjects with permanent pacemakers and repeated the protocol with ≥1 mo interval, a novel approach. VR adaptation was significantly longer following decreasing than increasing heart rate corroborating previous observations. Furthermore, VR adaptation was intraindividually a reproducible and, hence, robust phenomenon, a novel finding.

Categorization and theoretical comparison of quantitative methods for assessing QT/RR hysteresis

BACKGROUND

In the human electrocardiogram, there is a lag of adaptation of the QT interval to heart rate changes, usually termed QT/RR hysteresis (QT-hys). Subject-specific quantifiers of QT-hys have been proposed as potential biomarkers, but there is no consensus on the choice of the quantifier.

METHODS

A comprehensive literature search was conducted to identify original articles reporting quantifiers of repolarization hysteresis from the surface ECG in humans.

RESULTS

Sixty articles fulfilled our inclusion criteria. Reported biomarkers were grouped under four categories. A simple mathematical model of QT/RR loop was used to illustrate differences between the methods. Category I quantifiers use direct measurement of QT time course of adaptation. They are limited to conditions where RR intervals are under strict control. Category IIa and IIb quantifiers compare QT responses during consecutive heart rate acceleration and deceleration. They are relevant when a QT/RR loop is observed, typically during exercise and recovery, but are not robust to protocol variations. Category III quantifiers evaluate the optimum RR memory in dynamic QT/RR relationship modeling. They estimate an intrinsic memory parameter independent from the nature of RR changes, but their reliability remains to be confirmed when multiple memory parameters are estimated. Promising approaches include the differentiation of short-term and long-term memory and adaptive estimation of memory parameters.

CONCLUSION

Model-based approaches to QT-hys assessment appear to be the most versatile, as they allow separate quantification of QT/RR dependency and QT-hys, and can be applied to a wide range of experimental settings.

Recent heart rate history affects QT interval duration in atrial fibrillation

QT interval prolongation is associated with a risk of polymorphic ventricular tachycardia. QT interval shortens with increasing heart rate and correction for this effect is necessary for meaningful QT interval assessment. We aim to improve current methods of correcting the QT interval during atrial fibrillation (AF). Digitized Holter recordings were analyzed from patients with AF. Models of QT interval dependence on RR intervals were tested by sorting the beats into 20 bins based on corrected RR interval and assessing ST-T variability within the bins. Signal-averaging within bins was performed to determine QT/RR dependence. Data from 30 patients (29 men, 69.3±7.3 years) were evaluated. QT behavior in AF is well described by a linear function (slope ~0.19) of steady-state corrected RR interval. Corrected RR is calculated as a combination of an exponential weight function with time-constant of 2 minutes and a smaller “immediate response” component (weight ~ 0.18). This model performs significantly (p<0.0001) better than models based on instantaneous RR interval only including Bazett and Fridericia. It also outperforms models based on shorter time-constants and other previously proposed models. This model may improve detection of repolarization delay in AF. QT response to heart rate changes in AF is similar to previously published QT dynamics during atrial pacing and in sinus rhythm.

QT Adaptation and Intrinsic QT Variability in Congenital Long QT Syndrome

BACKGROUND

Increased variability of QT interval (QTV) has been linked to arrhythmias in animal experiments and multiple clinical situations. Congenital long QT syndrome (LQTS), a pure repolarization disease, may provide important information on the relationship between delayed repolarization and QTV.

METHODS AND RESULTS

Twenty-four-hour Holter monitor tracings from 78 genotyped congenital LQTS patients (52 females; 51 LQT1, 23 LQT2, 2 LQT5, 2 JLN, 27 symptomatic; age, 35.2±12.3 years) were evaluated with computer-assisted annotation of RR and QT intervals. Several models of RR-QT relationship were tested in all patients. A model assuming exponential decrease of past RR interval contributions to QT duration with 60-second time constant provided the best data fit. This model was used to calculate QTc and residual "intrinsic" QTV, which cannot be explained by heart rate change. The intrinsic QTV was higher in patients with long QTc (r=0.68; P<10(-4)), and in LQT2 than in LQT1/5 patients (5.65±1.28 vs 4.46±0.82; P<0.0002). Both QTc and intrinsic QTV were similar in symptomatic and asymptomatic patients (467±52 vs 459±53 ms and 5.10±1.19 vs 4.74±1.09, respectively).

CONCLUSIONS

In LQTS patients, QT interval adaptation to heart rate changes occurs with time constant ≈60 seconds, similar to results reported in control subjects. Intrinsic QTV correlates with the degree of repolarization delay and might reflect action potential instability observed in animal models of LQTS.

Nighttime instabilities of neurophysiological, cardiovascular, and respiratory activity: integrative modeling and preliminary results

Unstable (cyclical alternating pattern, or CAP) sleep is associated with surges of sympathetic nervous system activity, increased blood pressure and vasoconstriction, heightened baroreflex sensitivity, and unstable heart rhythm and breathing. In susceptible persons, CAP sleep provokes clinically significant events, including hypertensive crises, sleep-disordered breathing, and cardiac arrhythmias. Here we explore the neurophysiology of CAP sleep and its impact on cardiovascular and respiratory functions. We show that: (i) an increase in neurophysiological recovery rate can explain the emergence of slow, self-sustained, hypersynchronized A1 CAP-sleep pattern and its transition to the faster A2-A3 CAP-sleep patterns; (ii) in a two-dimensional, continuous model of cardiac tissue with heterogeneous action potential duration (APD) distribution, heart rate accelerations during CAP sleep may encounter incompletely recovered electrical excitability in cell clusters with longer APD. If the interaction between short cycle length and incomplete, spatially heterogeneous repolarization persists over multiple cycles, irregularities and asymmetry of depolarization front may accumulate and ultimately lead to a conduction block, retrograde conduction, breakup of activation waves, reentrant activity, and arrhythmias; and (iii) these modeling results are consistent with the nighttime data obtained from patients with structural heart disease (N=13) that show clusters of atrial and ventricular premature beats occurring during the periods of unstable heart rhythm and respiration that accompany CAP sleep. In these patients, CAP sleep is also accompanied by delayed adaptation of QT intervals and T-wave alternans.