Circadian Profile of QT Interval and QT Interval Variability in 172 Healthy Volunteers

BONNEMEIER, H., et al .: Circadian Profile of QT Interval and QT Interval Variability in 172 Healthy Volunteers. The limited prognostic value of QT dispersion has been demonstrated in recent studies. However, longitudinal data on physiological variations of QT interval and the influence of aging and sex are few. This analysis included 172 healthy subjects (89 women, 83 men; mean age   38.7 ± 15   years). Beat-to-beat QT interval duration (QT, QTapex [QTa], T_end[Te]), variability (QTSD, QTaSD), and the mean R-R interval were determined from 24-hour ambulatory electrocardiograms after exclusion of artifacts and premature beats. All volunteers were fully active, awoke at approximately 7:00 am , and had 6–8 hours of sleep. QT and R-R intervals revealed a characteristic day-night-pattern. Diurnal profiles of QT interval variability exhibited a significant increase in the morning hours (6–9 am ; P < 0.01) and a consecutive decline to baseline levels. In female subjects the R-R and T_end intervals were significantly lower at day- and nighttime. Aging was associated with an increase of QT interval mainly at daytime and a significant shift of the T wave apex towards the end of the T wave. The circadian profile of ventricular repolarization is strongly related to the mean R-R interval, however, there are significant alterations mainly at daytime with normal aging. Furthermore, the diurnal course of the QT interval variability strongly suggests that it is related to cardiac sympathetic activity and to the reported diurnal pattern of malignant ventricular arrhythmias. (PACE 2003; 26[Pt. II]):377–382)     

Systematic Comparisons of Electrocardiographic Morphology Increase the Precision of QT Interval Measurement

Decreased intrasubject variability of QTc values is needed to increase the power and reduce the size of the so-called thorough QT studies. One source of QTc variability is the lack of systematic measurements when electrocardiograms (ECG) with closely matching morphologies are not measured in an exactly corresponding way. The inaccuracy can be eliminated by postprocessing of QT measurements by ECG pattern matching. This study tested the effects of pattern matching in ECG measurements in two populations of healthy subjects (n = 48 + 56) and in a population of patients with advanced Parkinson's disease (n = 130) in whom both day-time and night-time data were available. Intrasubject QTc variability was measured by intrasubject standard deviations (SD) of QTc values obtained with manual measurements before and after pattern-matching measurement alignments. In each subject, QT values (n = 230–320) in one drug-free long-term ECG recording were evaluated. The pattern-matching adjustment of the QT measurement decreased the intrasubject QTc variability from 5.2 ± 1.0 to 4.5 ± 1.0 ms (P < 10⁻¹⁴) from 6.4 ± 1.7 to 5.5 ± 1.6 ms (P < 10⁻¹⁰) from 5.6 ± 1.5 to 4.6 ± 1.4 ms (P < 10⁻³⁴) and from 6.1 ± 1.9 to 5.0 ± 1.7 ms (P < 10⁻³³), in the two populations of healthy subjects and in the day-time and night-time recordings of Parkinson's disease patients, respectively. Hence, morphological pattern adjustment of QT interval measurements improves the quality of the QT data with substantial practical implications. Reductions in intrasubject QTc variability were reproducibly found in different populations and thus the technology might be recommended for every thorough QT/QTc study. Noticeable reductions of necessary study size are likely achievable in this way.     

Difference in QT Interval Measurement on Ambulatory ECG Compared with Standard ECG

Measurement of the QT interval on standard ECG has diagnostic importance in the congenital long QT syndrome, in pharmacological therapy of arrhythmias, as well as in ischemic heart disease. It has been suggested that QT prolongation on ambulatory ECG (Holter) may have similar importance. To assess agreement between methods, QT interval measurement on standard ECG was compared to that on Holter. Simultaneously obtained ECG and Holter tracings (25 mm/s) of the same complexes in leads V₁ and V₅ were studied in 14 patients (age range 4–36 years). ECG pairs (n = 100, 49 V₁ and 51 V₅) were compared over a range of QT interval from 300–620 ms, as determined with the use of calipers by two observers blinded to pairing relationship. Correlation between methods was high for both observers (observer 1: r[V₁] = 0.872, r[V₅] = 0.973; observer 2: r[V₁] = 0.972, r[V₅] = 0.988), and interobserver variability was small (> 85% of measurements within 20 ms). As compared to ECG, Holter underestimated QT interval in V₁ mean difference (QT [Holter]—QT [ECG]) observer 1 (-23 ms, P < 0.001), observer 2 (-7 ms, P < 0.05), and overestimated QT in V5, mean difference observer 1 (+ 13 ms, P < 0.001), observer 2 (+13 ms, P < 0.001). However, individual variation between methods was wide, as expressed by the difference between individual measurements (95% confidence interval [V₁]: observer 1 [-99 to +53 ms] observer 2 [-47 to +33 ms]; [V₅]: observer 1 [-33 to +59 ms] observer 2 [-17 to +43 ms]). Furthermore, when using the QTA (interval from onset of Q wave to apex of T wave) similar variability was observed. In the assessment of QT interval, potential sources of error of this magnitude could limit the clinical utility of ambulatory monitoring in detecting prolongation of the QT interval for diagnostic purposes.     

The JT Interval as a Depolarization Independent Measurement of Repolarization: Lessons from Catheter Ablation of the Wolff-Parkinson-White Syndrome

In patients with Wolff-Parkinson-White syndrome (WPW), preexcitation precludes accurate assessment of the ventricular repolarization by the QT_C. In patients with long QT syndrome, it has been demonstrated that the JT_C does not change when depolarization abnormalities develop. We hypothesized that this phenomenon should also be applicable to WPW patients. To test this, we assessed the surface ECG of 29 patients (16 males, 13 females) with WPW pre- and postablation. The QRS, QT, and JT intervals were measured pre- and postablation at 50 mm/s paper speed in leads II and V₂. QT_C and JT_C were calculated according to Bazett's formula. The average age was 12.8 ± 4.9 years (range 1.5–21). All patients had no residual preexcitation on postablation ECG. Early and late follow-up ECGs were obtained at 32 ± 34 days and 388 ± 197 days postablation, respectively. Both the QRS and the QT_C intervals shortened significantly on the postablation versus preablation ECGs (QRS: 115 ± 23 ms vs 89 ± 15 ms, respectively; P < 0.0001), (QT_C: 454 ± 26 vs 423 ± 23, respectively; P < 0.0001). The preablation JT_C interval did not change, postablation (319 ± 21 vs 323 ± 23, respectively; P > 0.2). Also, the JT_C interval did not change between early and late follow- up, postablation. JT_C: is an independent measure of repolarization, not related to depolarization. JT_C may be a useful tool in assessing repolarization in patients with WPW and other depolarization abnormalities.     

Heart Rate Variability and Sudden Infant Death Syndrome

PERTICONE, F., ET AL.: Heart Rate Variability and Sudden Infant Death Syndrome. The sudden infant death syndrome (SIDS) is the most common cause of death in infancy. The pathophysiological mechanism leading to SIDS is still obscure. In the QT hypothesis, the mechanism must be an arrhythmogenic sympathetic imbalance: the infants die suddenly of cardiac arrhythmia. Recently, it has been suggested that analysis of heart rate variability (HRV), expressed as standard deviation or variance analysis, can provide adequate information on sympathovagal interaction. We studied 150 newborns enrolled in a previous prospective electrocardiographic study to evaluate the predictive value of QT interval for SIDS. We analyzed the ECGs recorded with infants alert on the fourth day of life and after 2 months. For each ECG, the HRV was calculated using the first standard deviation of of RR intervals (ms) measured for 1 minute. The average RR interval was 441 ± 71 ms at the fourth day and 420 ± 39 ms at the second month. The QT_c and HRV mean values were 396 ± 23 and 23 ± 12 ms at the fourth day, 412 ± 19 and 15 ± 7 msec at the second month. Therefore, the SD values of heart rate were correlated with QT_cin order to assess a possible relationship between the two variables. The correlation coefficient and regression equation were: -0.639 and y = 423.67 - 2.18*× (P < 0.002) at the fourth day, -0.146 and y = 418.09 - 0.37*× (NS) at the second month. In conclusion, our data seems to confirm a delayed maturation or impaired fuctioning of the autonomic nervous system in the first weeks of life, reflecting a direct correlation with QT prolongation.     

Gender Differences in Ventricular Repolarization:

NAKAGAWA, M., et al. : Gender Difference in Ventricular Repolarization: Terminal T Wave Interval was Shorter in Woman than in Men . The incidence of sudden death is lower in women than in men, although women have a longer QT interval and are more prone to develop torsades de points than men. It has been recently proposed that the time interval between the apex and end of the T wave (Ta-e) represents the transmural dispersion of ventricular repolarization. Gender and age differences in Ta-e interval have not been fully assessed previously. Standard surface 12-lead ECGs recorded in 760 healthy subjects (382 women, 0–88 years of age) were studied. The intervals from j-point to the apex of the T wave (JaT) and to the end of the T wave (JeT) were measured in lead V₅ in each ECG and corrected by preceding RR intervals using the formula of Bazett (JaTc and JeTc). The Ta-e and Ta-e/JeT ratio were also evaluated. Both JaTc and JeTc intervals were significantly longer in women aged > 20 years than in men of the same age   (P < 0.0001)   . The difference was due to shortening of these intervals after puberty in men. However, the Ta-e interval was significantly shorter in women than in men   (P < 0.05)   and subsequently the Ta-e/JeT ratio was significantly smaller in women than in men (P < 0.0001). The results showed gender differences in the Ta-e interval and JaTc and JeTc intervals in healthy adults, and suggest that the small transmural dispersion of repolarization in women, in spite of the long JaTc and JeTc intervals, might be a beneficial antiarrhythmic property. (PACE 2003; 26[Pt. I]:59–64)     

QT Interval Variability and Adaptation to Heart Rate Changes in Patients with Long QT Syndrome

Background: Increased QT variability (QTV) has been reported in conditions associated with ventricular arrhythmias. Data on QTV in patients with congenital long QT syndrome (LQTS) are limited.
Methods: Ambulatory electrocardiogram recordings were analyzed in 23 genotyped LQTS patients and in 16 healthy subjects (C). Short-term QTV was compared between C and LQTS. The dependence of QT duration on heart rate was evaluated with three different linear models, based either on the RR interval preceding the QT interval (RR₀), the RR interval preceding RR₀ (RR_-1), or the average RR interval in the 60-second period before QT interval (mRR).
Results: Short-term QTV was significantly higher in LQTS than in C subjects (14.94 ± 9.33 vs 7.31 ± 1.29 ms; P < 0.001). It was also higher in the non-LQT1 than in LQT1 patients (23.00 ± 9.05 vs 8.74 ± 1.56 ms; P < 0.001) and correlated positively with QTc in LQTS (r = 0.623, P < 0.002). In the C subjects, the linear model based on mRR predicted QT duration significantly better than models based on RR₀ and RR_-1. It also provided better fit than any nonlinear model based on RR₀. This was also true for LQT1 patients. For non-LQT1 patients, all models provided poor prediction of QT interval.
Conclusions: QTV is elevated in LQTS patients and is correlated with QTc in LQTS. Significant differences with respect to QTV exist among different genotypes. QT interval duration is strongly affected by noninstantaneous heart rate in both C and LQT1 subjects. These findings could improve formulas for QT interval correction and provide insight on cellular mechanisms of QT adaptation.     

Predictors of Atrial Tachyarrhythmias in Subjects with Type 1 ECG Pattern of Brugada Syndrome

Background: Previous studies have demonstrated a high incidence of atrial tachyarrhythmias (ATs) in patients with Brugada syndrome (BS). The present study aimed to investigate whether various 12-lead electrocardiogram (ECG) and electrophysiological parameters may help to differentiate subjects with a high probability to develop ATs.
Methods and Results: The clinical records of 38 individuals (31 males, age 44.4 ± 13.9) with spontaneous (n = 15) or ajmaline-induced (n = 23) type 1 ECG pattern of BS were analyzed. During a mean follow-up period of 4.6 ± 2.2 years, nine subjects suffered ATs (24%). Six subjects displayed paroxysmal atrial fibrillation and three typical atrial flutter. Among the studied 12-lead ECG parameters, subjects with ATs exhibited increased values of P-wave duration in lead II, P-wave dispersion, PR interval in leads II, QRS duration in leads II and V₂, Tpeak-end interval in lead II, and Tpeak-end dispersion of the 12 leads in relation to those without ATs (P < 0.05). Among the assessed electrophysiological parameters, atrial-His (AH) and His-ventricular (HV) intervals were significantly prolonged in subjects with ATs (P < 0.05). Multiple Cox proportional hazards analysis revealed that P-wave duration in lead II, P-wave dispersion, Tpeak-end in lead II, Tpeak-end dispersion of the 12 leads, as well as AH and HV intervals are independent predictors of ATs in subjects with BS (P < 0.05). Cut-off point analysis showed that an HV interval ≥ 56 ms displayed the highest predictive ability (P < 0.01).
Conclusion: Our findings demonstrate that simple 12-lead ECG and electrophysiological parameters may easily be applied to identify high-risk subjects with BS ECG phenotype to develop ATs .     

New Insight into Repolarization Abnormalities in Patients with Congenital Long QT Syndrome: the Increased Transmural Dispersion of Repoiarization

There is evidence from experimental studies that the time interval from the peak to the end of T-wave reflects the transmural dispersion in repolarization (electrical gradient) between myocardial "layers" (epicardial, M-cells, endocardial). Since Congenital Long QT Syndrome (LQTS) is considered to be classical disease or repolarisation abnormalities, we performed the present study to assess the transmtiral dispersion of repolarization in LQTS patients. The study group consisted of 17 patients: 7 LQTS pts and 10 pts from the control group. In each patient the 24-hour ECG recording was performed on magnetic tape. The interval from the peak to the end of the T-wave (TpTo) was automatically measured by Holter system during every hour as a measure of transmural dispersion of repolarisation. Thereafter the mean TpTo from 24-hours was calculated. In addition the spatial QT dispersion was measured from 12 lead ECG and 3 channel Holter tape as a difference between the shortest and the longest QT interval between leads. The values were compared between groups using the Anova test.
TpTo was 79,6±9,6 ms (72–92 ms) in LQTS group and 62,4±7,5 ms (51–70) in the control group (p< 0.001). In LQTS group TpTo was significantly longer at night hours 72,5±2 when compared to day hours 87,4±8 (p<0.01). The spatial QT dispersion was significantly higher in LQTS patients when compared to control, both in 12-lead standard and Holter ECG.
Congenital long QT syndrome is associated with increase in both transmural and spatial dispersion of repolarization. The extent of prolongation of the terminal portion of QT in patients with congenital long QT syndrome is greater at night sleep hours compared to daily activity.     

Magnetocardiographic QT Interval Dispersion in Postmyocardial Infarction Patients with Sustained Ventricular Tachycardia: Validation of Automated QT Measurements

T dispersion is a measure of heterogeneity in ventricular repolarization. Increased ECG QT dispersion is associated with life-threatening ventricular arrhythmias. We studied if magnetocardiographic (MCG) measures of QT dispersion can separate postmyocardial infarction patients with and without susceptibility to sustained VT. Manual dispersion measurements were compared to a newly adapted automatic QT interval analysis method. Ten patients with a history of sustained VT (VT group) and eight patients without ventricular arrhythmias (Controls) were studied after a remote myocardial infarction. Single-channel MCGs were recorded from 42 locations over the frontal chest area and the signals were averaged. QT dispersion was defined as maximum — minimum or standard deviation of measured QT intervals. VT group showed significantly more QT and JT dispersion than Controls. QT_apex dispersions were 127 ± 26 versus 83 ± 21 ms (P = 0.004) and QT_end dispersions 130 ± 37 versus 82 ± 37 ms (P = 0.013), respectively. Automatic method gave comparable values. Their relative differences were 9% for QT_apex and 27% for QT_end dispersion on average. In conclusion, increased MCG QT interval dispersion seems to be associated with a susceptibility to VT in postmyocardial infarction patients. MCG mapping with automated QT interval analysis may provide a user independent method to detect nonhomogeneity in ventricular repolarization.     

Beat-to-Beat repolarization variability in LQTS patients with the SCN5A sodium channel gene mutation

Current techniques evaluating beat-to-beat variability of repolarization rely on accurate determination of T wave endpoints. This study proposes a T wave endpoint-independent method to quantify repolarization variability in a standard 12-lead ECG using a wavelet transformation. Our method was used to identify repolarization variability in long QT syndrome patients (LQTS) with the SCN5A sodium channel gene mutation. Using wavelet transformations based on the second Gaussian derivative, we evaluated repolarization variability in 11 LQTS patients with the mutation, 13 noncarrier family members, and 28 unrelated healthy subjects. Time-domain repolarization variability parameters (SDRTo, SDRTm) and wavelet parameters describing temporal (beat-to-beat) variability of repolarization in time (TVT) and in amplitude (TVA) were analyzed. Reproducibility of wavelet parameters and relationship of wavelet-based variability with heart rate and preceding RR interval were investigated. The wavelet-based method quantified beat-to-beat variability of the entire repolarization segment (regardless of QT interval identification) providing insight into variability in repolarization morphology. Our method showed that SCN5A carriers have significantly increased repolarization variability in amplitude (23% +/14% vs 8 +/- 4%, P < 0.001) and in time (14 +/- 17 ms vs 3 +/-2 ms, P < 0.004) compared to noncarriers. Variability of repolarization amplitude was found to be heart rate dependent with variability decreasing with increasing heart rate. Relative error describing reproducibility of TVA and TVT was < or = 5% and < or =10%, respectively. Our method quantifies repolarization variability in amplitude and in time without the need to identify T or U wave endpoints. Wavelet-detected repolarization variability contributes to phenotypic identification of SCN5A carriers, with more pronounced beat-to-beat variability in repolarization amplitude than in time.     

Autonomic Effects of Dipyridamole Stress Testing on Frequency Distribution of RR and QT Interval Variability

Transient myocardial ischemia and associated changes in the autonomic nervous system may influence heart rate and ventricular repolarization to variable degrees. This study evaluated the effect of dipyridamole (DIP) induced ischemia on the autonomic balance by spectral analysis of RR and QT intervals variability. Patients with coronary artery disease undergoing DIP stress echocardiography were studied. From high resolution ECG recordings, RR and QT interval measurements were performed by a dynamic template-matching algorithm. A time-variant analysis was used to estimate power in the LF (0.05–0,15 Hz) and in the HF (0.15–0.4 Hz) band of RR and QT interval spectra. Patients were grouped in ischemic and nonischemic subgroups based on the echocardiographic detection of wall-motion abnormalities. In patients without ischemia (n = 28), DIP caused a decrease in LF power and an increase in HF power of the RR and QT interval variability, indicating concordant changes of both intervals. In contrast, patients with inducible ischemia (n = 11) showed a decrease in HF power of the RR interval spectra and an increase of HF power of QT interval spectra. Furthermore, LF power was increased for RR but decreased for QT interval spectra. Our study suggests that DIP induced ischemia causes a loss of autonomic coupling between heart rate and ventricular repolarization for sympathetic and parasympathetic activities. This lability in ventricular repolarization may constitute an arrhythmogenic substrate during acute ischemia in patients with coronary artery disease.     

Changes of QT Intervals Associated with Postural Change in Patients with Chronic Atrial Fibrillation

Although different computerized systems have been developed to localize specific patterns in electrocardiographic (ECG) signals, it is still difficult to detect T waves and measure QT intervals during atrial fibrillation. This article demonstrates the use of an auto-correlation (ECG) based system that was used to investigate the dynamicity of QT intervals related to active postural change in patients with chronic atrial fibrillation. Twenty patients (9 male, mean age 63 years) with chronic atrial fibrillation (8 idiopathic, 12 organic heart disease) were examined. Seventeen of these patients were on digoxin, but patients with other conditions potentially affecting the autonomic nervous system were not included. A 3-channel ECG was recorded digitally during active postural change from supine to standing. Data were first analyzed by the Burdick Altair system and subsequently processed using an in-house software package evaluating auto-correlations of ECG signals. An ECG channel with suitable repolarization patterns was found in 15 patients. The mean QT interval of 409.8 ± 11.1 ms (mean ± SE) recorded during supine position shortened to 401.9 ± 9.89 ms during the first minute of active standing (P < 0.05) and to 394.8 ± 10.0 ms during the second minute of active standing (P < 0.005). It did not further change during the subsequent minutes of active standing. The study shows that automatic detection of QT intervals during atrial fibrillation is possible. Although the effect of position change of the heart cannot be completely excluded, the study suggests that QT interval is changed directly by autonomic nervous mechanisms rather than indirectly via the mean heart rate.     

Gender Effects on Novel Time Domain Parameters of Ventricular Repolarization Inhomogeneity

Introduction: Parameters of ventricular repolarization variability are increasingly being used in an attempt to understand better and predict the occurrence of ventricular tachycardia. Nevertheless, some of the measures used have thus far not been analyzed regarding gender differences in a large group of healthy subjects. Furthermore, new parameters might give further insight.
Methods and Results: We investigated 139 healthy volunteers (mean age 41.6 ± 15.3 years, range 20–77, median 40.0 years, 76 women) without evidence of organic cardiac disease. Mean RR interval and established time domain parameters of heart rate variability (rMSSD; SDNN) were measured for each subject. Beat-to-beat QT interval and time-domain QT interval variability were analyzed. Characteristics of the QT interval and QT interval variability were determined as hourly mean values. The standard deviation of all QT intervals/hour (SDQT) and the standard deviation of all QTc intervals/hour (SDQTc) were used to measure QT interval variability. Four novel ratios of repolarization inhomogeneity (VRI: SDQT/SDNN; VR II: SDQT/rMSSD; VR III: SDQTc/SDNN; VR IV: SDQTc/rMSSD) were introduced. Female subjects exhibited significantly higher values in all four ratios of variability.
Conclusion: The obvious gender differences in repolarization inhomogeneity found in this study might be valuable in better understanding differences between men and women in the genesis of ventricular tachycardia.     

Evaluation of a subject-specific transfer-function-based nonlinear QT interval rate-correction method

The QT interval in the electrocardiogram (ECG) is a measure of total duration of depolarization and repolarization. Correction for heart rate is necessary to provide a single intrinsic physiological value that can be compared between subjects and within the same subject under different conditions. Standard formulas for the corrected QT (QTc) do not fully reproduce the complexity of the dependence in the preceding interbeat intervals (RR) and inter-subject variability. In this paper, a subject-specific, nonlinear, transfer function-based correction method is formulated to compute the QTc from Holter ECG recordings. The model includes five parameters: three describing the static QT-RR relationship and two representing memory/hysteresis effects that intervene in the calculation of effective RR values. The parameter identification procedure is designed to minimize QTc fluctuations and enforce zero correlation between QTc and effective RR. Weighted regression is used to better handle unbalanced or skewed RR distributions. The proposed optimization approach provides a general mathematical framework for further extensions of the model. Validation, robustness evaluation and comparison with existing QT correction formulas is performed on ECG signals recorded during sinus rhythm, atrial pacing, tilt-table tests, stress tests and atrial flutter (29 subjects in total). The resulting average modeling error on the QTc is 4.9 ± 1.1 ms with a sampling interval of 2 ms, which outperforms correction formulas currently used. The results demonstrate the benefits of subject-specific rate correction and hysteresis reduction.     

Comparison of Time-Domain Short-Term Heart Interval Variability Analysis Using a Wrist-Worn Heart Rate Monitor and the Conventional Electrocardiogram

Background: Wrist-worn heart rate monitors have not been extensively validated for heart rate variability analysis. The purpose of this study was to compare time-domain variability of heart interval series (R-Ri) recorded by the Polar S810 monitor (Polar Electro Oy, Kempele, Finland) and the conventional electrocardiogram (ECG).
Methods: Agreement was verified between variability indices of 5-minute R-Ri simultaneously recorded by both devices and processed by unique software, from 33 subjects aged 18 to 42 years, normal or with different clinical conditions, in rest supine and active standing. ECG minus Polar differences were quantified by the Bland-Altman analysis, and tested by the one-sample t-test or Wilcoxon test.
Results: In the supine position, the Polar overestimates (P < 0.0001) the absolute and percentage mean or median of the number (−2.00; −0.49%) and mean of R-Ri (–1.85 ms; –0.20%) and pNN50 (−2.20%; −8.68%), and underestimates the standard deviation (SDNN) (0.32 ms; 0.59%) (P = 0.08; P = 0.02) and root mean square successive difference (RMSSD) (0.90 ms; 1.56%) (P = 0.0008; P < 0.0001). The coefficient of variation (CV) showed null difference. On standing, differences were overestimated for the number (−2.61 intervals; −0.64%) and mean of R-Ri (−0.70 ms; −0.09%), and underestimated for rMSSD (1.70 ms; 10.84%) (P < 0.0001 to < 0.02). The SDNN, CV, and pNN50 indices did not show differences (P = 0.12 to 0.73).
Conclusions: The Polar S810 monitor was feasible and reliable for recording short-term R-R interval series, showing excellent agreement with the ECG in providing the time-domain indexes of heart interval variability with differences functionally not relevant. The CV showed the higher agreement in both postures, and the SDNN and pNN50 in the standing posture.     

Prolongation of the QT interval in heart failure occurs at low but not at high heart rates

Abnormal left ventricular structure and function as in, for example, left ventricular hypertrophy or chronic heart failure, is associated with sudden cardiac death and, when the ejection fraction is depressed, with prolongation of the QT interval. The dependence on heart rate of QT interval prolongation in these conditions, and the relationship of any abnormalities either to deranged autonomic nervous system function or to an adverse prognosis, has not been well studied. We therefore investigated (1) the dependence on heart rate of the QT interval, and (2) the relationship between both QT interval and the QT/heart rate slope and markers of adverse prognosis in these two conditions. The QT interval was measured at rest and during exercise in 34 subjects with heart failure, 16 subjects with left ventricular hypertrophy and 16 age-matched controls with normal left ventricular structure and function. QTc (corrected QT) intervals at rest were significantly longer in heart failure patients (471+/-10 ms) than in controls (421+/-6 ms) or in subjects with hypertrophy (420+/-6 ms) (P<0.05). At peak exercise, despite the attainment of similar heart rates, the QT intervals no longer differed from each other, being 281+/-7 ms for controls, 296+/-11 ms in hypertrophy and 303+/-10 ms in heart failure (no significant difference). The QT/heart rate slope was significantly increased in heart failure [2.3+/-0.1 ms.(beats/min)(-1)] compared with controls [1.55+/-0.06 ms.(beats/min)(-1)] and hypertrophy [1. 66+/-0.1 ms.(beats/min)(-1)] (P<0.001). In left ventricular hypertrophy, despite animal data suggesting that QT interval prolongation should occur, no abnormalities were found in QT intervals at rest or during exercise. The QT/heart rate slope did not relate to any markers for an adverse prognosis, except that of prolongation of QT interval. Long QT intervals were associated principally with impairment of left ventricular systolic function. Our data emphasize the dynamic nature of the QT interval abnormalities found in heart failure.     

Dynamic Beat-to-Beat QT-RR Relationship During Physiotherapy Effort in Elderly Patients Without Primary Heart Disease

The ECGs from 18 patients hospitalized in a rehabilitation setting, following surgery for hip fracture, were examined to characterize the dynamic behavior of uncorrected QT interval in relation to changing RR interval during physiotherapy effort. ECG waveforms were analyzed to extract beat-to-beat QT and RR intervals using a computerized ECG Analyzer (CEA-1100). The method of defining the QT and RR intervals is based on performing multiple cross-correlations that enable rejection of artifacts from the analysis. The relationship between the RR and QT intervals was found using the following general formula QTi = cRRi-1b. Linear regression was performed on the logarithms of QT and RR measurements obtained to estimate the constant (a = log c) and the slope (b) values, reflecting the dynamic change of QT during physiotherapy effort. Having these two values, the dynamic QT extrapolated to a heart period of 1 second (QTcd) was calculated. The results were compared to the conventional corrected static QT according to the Bazzet formula (QTcs). The mean values of constants (a = log c) and slopes (b) over all patients were found to be 1.61 +/- 0.23 and 0.33 +/- 0.08, respectively, giving a QT (ms) heart-period (ms) dynamic relation of QTi = 41 x RR(i-1)0.33. The correlation between the dynamic QT and the static QT intervals was not significant. The mean values of the QTcd and QTcs intervals were significantly different (392 +/- 25 ms vs 434 +/- 28 ms; P < 0.0001). This dynamic measurement method of QT intervals may provide additional information on normal and abnormal cardiac repolarization in health and disease, helping in the diagnosis of cardiac disorders and arrhythmia risk.     

Dispersion of QT Intervals: A Measure of Dispersion of Repolarization or Simply a Projection Effect?

QT interval dispersion may provide little information about repolarization dispersion. Some clinical measurements demonstrate an association between high QT interval dispersion and high morbidity and mortality, but what is being measured is not clear. This study was designed to help resolve this dilemma. We compared the association between different clinical measures of QT interval dispersion and the ECG lead amplitudes derived from a heart vector model of repolarization with no repolarization dispersion whatsoever. We compared our clinical QT interval dispersion data obtained from 25 subjects without cardiac disease with similar data from published studies, and correlated these QT dispersion results with the distribution of lead amplitudes derived from the projection of the heart vector onto the body surface during repolarization. Published results were available for mean relative QT intervals and mean differences from the maximum QT interval. The leads were derived from Uijen and Dower lead vector data. Using the Uijen lead vector data, the correlation between measurements of dispersion and derived lead amplitudes ranged from 0.78 to 0.99 for limb leads, and using the Dower values ranged from 0.81 to 0.94 for the precordial leads. These results show a clear association between the measured QT interval dispersion and the variation in ECG lead amplitudes derived from a simple heart vector model of repolarization with no regional information. Therefore, measured QT dispersion is related mostly to a projection effect and is not a true measure of repolarization dispersion. Our existing interpretation of QT dispersion must be reexamined, and other measurements that provide true repolarization dispersion data investigated.     

Influence of posture and handgrip on the QT interval in left ventricular hypertrophy and in chronic heart failure

In certain disease states prolongation of the QT interval has been shown to be arrhythmogenic. Whether QTc interval changes with position and thus whether certain positions are more arrhythmogenic than others is not known for different diseases that predispose to arrhythmias, and was therefore studied. Patients with left ventricular hypertrophy and heart failure, and the appropriate matched controls, were recruited. Subjects were studied in the lying, sitting, standing and squatting positions and had QT intervals determined by computer algorithm 2 min after each position change. After resting, QT interval was determined while the subjects performed maximum handgrip exercise with their dominant hand. QT intervals were rate-corrected using Bazett's method. QTc interval is prolonged in heart failure patients compared with either left ventricular hypertrophy or control subjects in the lying and sitting position, but not in the standing or squatting position. The QTc intervals for heart failure and control subjects were, respectively, 443+/-7 ms versus 421+/-6 ms when lying (P<0.05), 451+/-10 ms versus 419+/-6 ms when sitting (P<0.05), 429+/-10 versus 414+/-7 ms when standing (P not significant) and 437+/-10 versus 419+/-8 ms when squatting (P not significant). The values for patients with hypertrophy did not differ from control values. Maximum handgrip does not affect the QTc interval in heart failure, but prolongs it in both the hypertrophy and control groups. Position and static exercise are important modifiers of QTc interval and their effect depends on the condition of the left ventricle.