Repolarization lability measured on 10-second ECG by spatial TT' angle: reproducibility and agreement with QT variability

Skin Sympathetic Nerve Activity and the Short-Term QT Interval Variability in Patients With Electrical Storm

Background: Skin sympathetic nerve activity (SKNA) and QT interval variability are known to be associated with ventricular arrhythmias. However, the relationship between the two remains unclear.

Objective: The aim was to test the hypothesis that SKNA bursts are associated with greater short-term variability of the QT interval (STVQT) in patients with electrical storm (ES) or coronary heart disease without arrhythmias (CHD) than in healthy volunteers (HV).

Methods: We simultaneously recorded the ECG and SKNA during sinus rhythm in patients with ES (N = 10) and CHD (N = 8) and during cold-water pressor test in HV (N = 12). The QT and QTc intervals were manually marked and calculated within the ECG. The STVQT was calculated and compared to episodes of SKNA burst and non-bursting activity.

Results: The SKNA burst threshold for ES and HV was 1.06 ± 1.07 and 1.88 ± 1.09 μV, respectively (p = 0.011). During SKNA baseline and burst, the QT/QTc intervals and STVQT for ES and CHD were significantly higher than those of the HV. In all subjects, SKNA bursts were associated with an increased STVQT (from 6.43 ± 2.99 to 9.40 ± 5.12 ms, p = 0.002 for ES; from 9.48 ± 4.40 to 12.8 ± 5.26 ms, p = 0.016 for CHD; and from 3.81 ± 0.73 to 4.49 ± 1.24 ms, p = 0.016 for HV). The magnitude of increased STVQT in ES (3.33 ± 3.06 ms) and CHD (3.34 ± 2.34 ms) was both higher than that of the HV (0.68 ± 0.84 ms, p = 0.047 and p = 0.020).

Conclusion: Compared to non-bursting activity, SKNA bursts were associated with a larger increase in the QTc interval and STVQT in patients with heart disease than in HV.

Reproducibility of global electrical heterogeneity measurements on 12-lead ECG: The Multi-Ethnic Study of Atherosclerosis

OBJECTIVE

Vectorcardiographic (VCG) global electrical heterogeneity (GEH) metrics showed clinical usefulness. We aimed to assess the reproducibility of GEH metrics.

METHODS

GEH was measured on two 10-s 12‑lead ECGs recorded on the same day in 4316 participants of the Multi-Ethnic Study of Atherosclerosis (age 69.4 ± 9.4 y; 2317(54%) female, 1728 (40%) white, 1138(26%) African-American, 519(12%) Asian-American, 931(22%) Hispanic-American). GEH was measured on a median beat, comprised of the normal sinus (N), atrial fibrillation/flutter (S), and ventricular-paced (VP) beats. Spatial ventricular gradient's (SVG's) scalar was measured as sum absolute QRST integral (SAIQRST) and vector magnitude QT integral (VMQTi).

RESULTS

Two N ECGs with heart rate (HR) bias of -0.64 (95% limits of agreement [LOA] -5.68 to 5.21) showed spatial area QRS-T angle (aQRST) bias of -0.12 (95%LOA -14.8 to 14.5). Two S ECGs with HR bias of 0.20 (95%LOA -15.8 to 16.2) showed aQRST bias of 1.37 (95%LOA -33.2 to 35.9). Two VP ECGs with HR bias of 0.25 (95%LOA -3.0 to 3.5) showed aQRST bias of -1.03 (95%LOA -11.9 to 9.9). After excluding premature atrial or ventricular beat and two additional beats (before and after extrasystole), the number of cardiac beats included in a median beat did not affect the GEH reproducibility. Mean-centered log-transformed values of SAIQRST and VMQTi demonstrated perfect agreement (Bias 0; 95%LOA -0.092 to 0.092).

CONCLUSION

GEH measurements on N, S, and VP median beats are reproducible. SVG's scalar can be measured as either SAIQRST or VMQTi.

SIGNIFICANCE

Satisfactory reproducibility of GEH metrics supports their implementation.

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.

Normal Values of QT Variability in 10-s Electrocardiograms for all Ages

Aims: QT variability is a promising electrocardiographic marker. It has been studied as a screening tool for coronary artery disease and left ventricular hypertrophy, and increased QT variability is a known risk factor for sudden cardiac death. Considering that comprehensive normal values for QT variability were lacking, we set out to establish these in standard 10-s electrocardiograms (ECGs) covering both sexes and all ages.

Methods: Ten-second, 12-lead ECGs were provided by five Dutch population studies (Pediatric Normal ECG Study, Leiden University Einthoven Science Project, Prevention of Renal and Vascular End-stage Disease Study, Utrecht Health Project, Rotterdam Study). ECGs were recorded digitally and processed by well-validated analysis software. We selected cardiologically healthy participants, 46% being women. Ages ranged from 11 days to 91 years. After quality control, 13,828 ECGs were available. We assessed three markers: standard deviation of QT intervals (SDqt), short-term QT variability (STVqt), and QT variability index (QTVI).

Results: For SDqt and STVqt, the median and the lower limit of normal remained stable with age. The upper limit of normal declined until around age 45, and increased strongly in the elderly, notably so in women. This implies that a subset of the population, small enough not to have appreciable effect on the median, shows a high degree of QT variability with a possible risk of arrhythmias or worse, especially in women. Otherwise, sex differences were negligible in all three measurements. For QTVI, median, and normal limits decreased until age 20, and steadily went up afterwards except for the lower limit of normal, which flattens off after age 65.

Conclusion: We report the first set of normal values for QT variability based on 10-s ECGs, for all ages and both sexes.

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

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.

Beat-to-beat determinants of the beat-to-beat temporal and spatial variability of repolarization

BACKGROUND

The goal of this study was to compare the time series predictors of beat-to-beat variability in repolarization in healthy individuals.

METHODS

Spatial QRS- and T-vector amplitudes, spatial QRS-T, RR' and TT' angles, RR' and QT intervals, and QRS- and T-loop roundness were measured on 453 consecutive sinus beats in 168 healthy subjects (mean age 39.8±15.6years; 50% men; 93% white). Panel time-series regression models were adjusted by age, sex, and race. Appropriate time series of ECG metrics served as predictors and outcomes.

RESULTS

Increase in T-loop roundness index by 0.1 was associated with 1.1° (95%CI 0.9-2.2; P=0.048) increase in corresponding TT' angle. One unit increase in a respiration index was associated with 4ms (95%CI 0.6-7.0; P=0.021) increase in QT interval.

CONCLUSIONS

Spatial TT' angle and beat-to-beat variability in T-loop roundness represent intrinsic measures of repolarization variability. QT interval variability characterizes the effect of respiration and heart rate variability.

Beat-to-beat spatiotemporal variability in the T vector is associated with sudden cardiac death in participants without left ventricular hypertrophy: the Atherosclerosis Risk in Communities (ARIC) Study

Background

Despite advances in prevention and treatment of cardiovascular disease, sudden cardiac death (SCD) remains a clinical challenge. Risk stratification in the general population is needed.

Methods and Results

Beat‐to‐beat spatiotemporal variability in the T vector was measured as the mean angle between consecutive T‐wave vectors (mean TT′ angle) on standard 12‐lead ECGs in 14 024 participants in the Atherosclerosis Risk in Communities (ARIC) study. Subjects with left ventricular hypertrophy, atrial arrhythmias, frequent ectopy, ventricular pacing, or QRS duration ≥120 ms were excluded. The mean spatial TT′ angle was 5.21±3.55°. During a median of 14 years of follow‐up, 235 SCDs occurred (1.24 per 1000 person‐years). After adjustment for demographics, coronary heart disease risk factors, and known ECG markers for SCD, mean TT′ angle was independently associated with SCD (hazard ratio 1.089; 95% CI 1.044 to 1.137; P<0.0001). A mean TT′ angle >90th percentile (>9.57°) was associated with a 2‐fold increase in the hazard for SCD (hazard ratio 2.01; 95% CI 1.28 to 3.16; P=0.002). In a subgroup of patients with T‐vector amplitude ≥0.2 mV, the association with SCD was almost twice as strong (hazard ratio 3.92; 95% CI 1.91 to 8.05; P<0.0001). A significant interaction between mean TT′ angle and age was found: TT′ angle was associated with SCD in participants aged <55 years (hazard ratio 1.096; 95% CI 0.043 to 1.152; P<0.0001) but not in participants aged ≥55 years (P_interaction=0.009).

Conclusions

In a large, prospective, community‐based cohort of left ventricular hypertrophy–free participants, increased beat‐to‐beat spatiotemporal variability in the T vector, as assessed by increasing TT′ angle, was associated with SCD.

Repolarization Lability Measured by Spatial TT' Angle

AIMS

Increased T peaks cloud volume is associated with increased risk of ventricular arrhythmias (VA) in cardiomyopathy (CM) patients. T peaks cloud volume is formed, as a result, of (1) the angle between consecutive T-vectors and (2) temporal variability in T-vector amplitude. This study compares association of these two factors with VA.

METHODS

Baseline orthogonal ECGs were recorded during 5 min at rest in 414 patients with structural heart disease [mean age 59.4±12.0; 68% whites; 73% men; 45% non-ischemic CM] before implantation of implantable cardioverter-defibrillator (ICD) for primary prevention of sudden cardiac death. The spatial TT' angle between consecutive spatial T vectors was calculated using the definition of the inner product.

RESULTS

During a median 14 months of follow-up, 61 patients experienced sustained VA with appropriate ICD therapies. In a multivariable Cox regression model after adjustment for age, sex, race, spatial TT' angle was associated with VA (HR 1.03; 95%CI 1.0-1.05; P=0.034). Interaction with CM type was found: TT' angle was strongly associated with polymorphic VT/VF in non-ischemic CM (HR 1.04; 95%CI 1.0-1.05; P=0.033).

CONCLUSION

Increased spatial TT' angle is associated with increased risk of VA.