QT Adaptation and Intrinsic QT Variability in Congenital Long QT Syndrome

Holter Recordings at Initial Assessment for Long QT Syndrome: Relationship to Genotype Status and Cardiac Events

Background: The relationship of Holter recordings of repolarization length to outcome in long QT syndrome (LQTS) is unknown. Methods: Holter recordings and initial 12 lead ECG QTc were related to outcome in 101 individuals with LQTS and 28 gene-negative relatives. Mean QTc (mQTc) and mean RTPc (R-wave to peak T-wave, mRTPc) using Bazett correction were measured, analyzing heart rates 40 to 120 bpm. Previously reported upper limit of normal (ULN) were: women and children (<15 years), mQTc 454, mRTPc 318 ms; men mQTc 446 ms, mRTPc 314 ms. Results: Measurements in LQTS patients were greatly prolonged; children and women mean mQTc 482 ms (range 406−558), mRTPc 351 ms (259−443); males > 15 years mQTc 469 ms (407−531), mRTPc 338 ms (288−388). Ten patients had cardiac arrest (CA), and 24 had arrhythmic syncope before or after the Holter. Holter values were more closely related to genotype status and symptoms than 12 lead QTc, e.g., sensitivity/specificity for genotype positive status, mRTPc > ULN (89%/86%); CA, mRTPc > 30 ms over ULN (48%/100%). Of 34 symptomatic (CA/syncope) patients, only 9 (26%) had 12 lead QTc > 500 ms, whereas 33/34 (94%) had an mRTPc or mQTc above ULN. In 10 with CA, all Holter measurements were > 15 ms above ULN, but only two had 12 lead QTc > 500 m. Conclusions: Holter average repolarization length, particularly mRTPc, reflects definite LQTS status and clinical risk better than the initial 12 lead QTc. Values below ULN indicate both a low risk of having LQTS and a low risk of cardiac events in the small percentage that do.

Short-Term Beat-to-Beat QT Variability Appears Influenced More Strongly by Recording Quality Than by Beat-to-Beat RR Variability

Increases in beat-to-beat variability of electrocardiographic QT interval duration have repeatedly been associated with increased risk of cardiovascular events and complications. The measurements of QT variability are frequently normalized for the underlying RR interval variability. Such normalization supports the concept of the so-called immediate RR effect which relates each QT interval to the preceding RR interval. The validity of this concept was investigated in the present study together with the analysis of the influence of electrocardiographic morphological stability on QT variability measurements. The analyses involved QT and RR measurements in 6,114,562 individual beats of 642,708 separate 10-s ECG samples recorded in 523 healthy volunteers (259 females). Only beats with high morphology correlation (r &gt; 0.99) with representative waveforms of the 10-s ECG samples were analyzed, assuring that only good quality recordings were included. In addition to these high correlations, SDs of the ECG signal difference between representative waveforms and individual beats expressed morphological instability and ECG noise. In the intra-subject analyses of both individual beats and of 10-s averages, QT interval variability was substantially more strongly related to the ECG noise than to the underlying RR variability. In approximately one-third of the analyzed ECG beats, the prolongation or shortening of the preceding RR interval was followed by the opposite change of the QT interval. In linear regression analyses, underlying RR variability within each 10-s ECG sample explained only 5.7 and 11.1% of QT interval variability in females and males, respectively. On the contrary, the underlying ECG noise contents of the 10-s samples explained 56.5 and 60.1% of the QT interval variability in females and males, respectively. The study concludes that the concept of stable and uniform immediate RR interval effect on the duration of subsequent QT interval duration is highly questionable. Even if only stable beat-to-beat measurements of QT interval are used, the QT interval variability is still substantially influenced by morphological variability and noise pollution of the source ECG recordings. Even when good quality recordings are used, noise contents of the electrocardiograms should be objectively examined in future studies of QT interval variability.

QT interval Adaptation to Heart Rate Changes in Atrial Fibrillation as a Predictor of Sudden Cardiac Death

OBJECTIVE

The clinical significance of QT interval adaptation to heart rate changes has been poorly investigated in atrial fibrillation (AF), since QT delineation in the presence of f-waves is challenging. Therefore, the objective of the present study is to investigate new techniques for QT adaptation estimation in permanent AF.

METHODS

A multilead strategy based on generalized periodic component analysis is proposed for QT delineation, involving a spatial, linear transformation which emphasizes Twave periodicity and attenuates f-waves. QT adaptation is modeled by a linear, time-invariant filter, whose impulse response describes the dependence between the current QT interval and the preceding RR intervals, followed by a memoryless, possibly nonlinear, function. The QT adaptation time lag is determined from the estimated impulse response.

RESULTS

Using simulated ECGs in permanent AF, the transformed lead was found to offer more accurate QT delineation and time lag estimation than did the original ECG leads for a wide range of f-wave amplitudes (the time lag estimation error was found to be -0.2+/-0.6 s for SNR = 12 dB). In a population with chronic heart failure and permanent AF, the time lag estimated from the transformed lead was found to have the strongest, statistically significant association with sudden cardiac death (SCD) (hazard ratio = 3.49), whereas none of the original, orthogonal leads had any such association.

CONCLUSIONS

Periodic component analysis provides more accurate QT delineation and improves time lag estimation in AF. A prolonged adaptation time of the QT interval to heart rate changes is associated with a high risk for SCD.

SIGNIFICANCE

This study demonstrates that SCD risk markers, originally developed for sinus rhythm, can also be used in AF, provided that Twave periodicity is emphasized. The time lag is a potentially useful marker for identifying patients at high risk for SCD, guiding clinicians in adopting effective therapeutic decisions.

Information Flow Between Heart Rhythm, Repolarization, and the Diastolic Interval Series for Healthy Individuals and LQTS1 Patients

Using information theoretic measures, relations between heart rhythm, repolarization in the tissue of the heart, and the diastolic interval time series are analyzed. These processes are a fragment of the cardiovascular physiological network. A comparison is made between the results for 84 (42 women) healthy individuals and 65 (45 women) long QT syndrome type 1 (LQTS1) patients. Self-entropy, transfer entropy, and joint transfer entropy are calculated for the three time series and their combinations. The results for self-entropy indicate the well-known result that regularity of heart rhythm for healthy individuals is larger than that of QT interval series. The flow of information depends on the direction with the flow from the heart rhythm to QT dominating. In LQTS1 patients, however, our results indicate that information flow in the opposite direction may occur—a new result. The information flow from the heart rhythm to QT dominates, which verifies the asymmetry seen by Porta et al. in the variable tilt angle experiment. The amount of new information and self-entropy for LQTS1 patients is smaller than that for healthy individuals. However, information transfers from RR to QT and from DI to QT are larger in the case of LQTS1 patients.

Absence of Rgs5 Influences the Spatial and Temporal Fluctuation of Cardiac Repolarization in Mice

Aims

This study investigated the contribution of the regulator of G-protein signaling 5 (Rgs5) knockout to the alteration of the action potential duration (APD) restitution and repolarizing dispersion in ventricle.

Methods and Results

The effects of Rgs5^–/– were investigated by QT variance (QTv) and heart rate variability analysis of Rgs5^–/– mice. Monophasic action potential analysis was investigated in isolated Rgs5^–/– heart. Rgs5^–/– did not promote ventricular remodeling. The 24-h QTv and QT variability index (QTVI) of the Rgs5^–/– mice were higher than those of wild-type (WT) mice (P < 0.01). In WT mice, a positive correlation was found between QTv and the standard deviation of all NN intervals (r = 0.62; P < 0.01), but not in Rgs5^–/– mice (R = 0.01; P > 0.05). The absence of Rgs5 resulted in a significant prolongation of effective refractory period and APD in isolated ventricle. In addition, compared with WT mice, the knockout of Rgs5 significantly deepened the slope of the APD recovery curve at all 10 sites of the heart (P < 0.01) and increased the spatial dispersions of S_max (COV-S_max) (WT: 0.28 ± 0.03, Rgs5^–/–: 0.53 ± 0.08, P < 0.01). Compared with WT heart, Rgs5^–/– increased the induced S1–S2 interval at all sites of heart and widened the window of vulnerability of ventricular tachyarrhythmia (P < 0.05).

Conclusion

Our findings indicate that Rgs5^–/– is an important regulator of ventricular tachyarrhythmia in mice by prolonging ventricular repolarization and increasing spatial dispersion in ventricle.

Heart Rate Influence on the QT Variability Risk Factors

QT interval variability, mostly expressed by QT variability index (QTVi), has repeatedly been used in risk diagnostics. Physiologic correlates of QT variability expressions have been little researched especially when measured in short 10-second electrocardiograms (ECGs). This study investigated different QT variability indices, including QTVi and the standard deviation of QT interval durations (SDQT) in 657,287 10-second ECGs recorded in 523 healthy subjects (259 females). The indices were related to the underlying heart rate and to the 10-second standard deviation of RR intervals (SDRR). The analyses showed that both QTVi and SDQT (as well as other QT variability indices) were highly statistically significantly (p < 0.00001) influenced by heart rate and that QTVi showed poor intra-subject reproducibility (coefficient of variance approaching 200%). Furthermore, sequential analysis of regression variance showed that SDQT was more strongly related to the underlying heart rate than to SDRR, and that QTVi was influenced by the underlying heart rate and SDRR more strongly than by SDQT (p < 0.00001 for these comparisons of regression dependency). The study concludes that instead of QTVi, simpler expressions of QT interval variability, such as SDQT, appear preferable for future applications especially if multivariable combination with the underlying heart rate is used.

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.