Temperature dependent near-UV molar absorptivities of glyoxal and gluteraldehyde in aqueous solution

Molar absorptivities have been determined for glyoxal and gluteraldehyde in aqueous solution. Absorptivities are reported at eight temperatures in the range 5-70 degrees C for wavelengths greater than 200 nm. For glyoxal the data indicate did less than 0.02% of the glyoxal molecules exist in the free dialdehyde form, and that at 25 degrees C approximately 98% of the molecules are hydrated at both carbonyl groups, results that are consistent with previous experiments. For gluteraldehyde hydration of the two carbonyl groups occurs in an independent manner. The following thermodynamic data are found for gluteraldehyde hydration: deltaH = - 35.8+/-1.3 kJ mole(-1), deltaS = 103+/-7 J (mole K)(-1), and K = 7.5+/-2.0. The results for gluteraldehyde are compared with previous results obtained for the hydration of aliphatic aldehydes.

Measurement, interpretation and clinical potential of QT dispersion

QT dispersion was originally proposed to measure spatial dispersion of ventricular recovery times. Later, it was shown that QT dispersion does not directly reflect the dispersion of recovery times and that it results mainly from variations in the T loop morphology and the error of QT measurement. The reliability of both automatic and manual measurement of QT dispersion is low and significantly lower than that of the QT interval. The measurement error is of the order of the differences between different patient groups. The agreement between automatic and manual measurement is poor. There is little to choose between various QT dispersion indices, as well as between different lead systems for their measurement. Reported values of QT dispersion vary widely, e.g., normal values from 10 to 71 ms. Although QT dispersion is increased in cardiac patients compared with healthy subjects and prognostic value of QT dispersion has been reported, values are largely overlapping, both between healthy subjects and cardiac patients and between patients with and without adverse outcome. In reality, QT dispersion is a crude and approximate measure of abnormality of the complete course of repolarization. Probably only grossly abnormal values (e.g. > or =100 ms), outside the range of measurement error may potentially have practical value by pointing to a grossly abnormal repolarization. Efforts should be directed toward established as well as new methods for assessment and quantification of repolarization abnormalities, such as principal component analysis of the T wave, T loop descriptors, and T wave morphology and wavefront direction descriptors.

Evaluation of renormalised entropy for risk stratification using heart rate variability data

Standard time and frequency parameters of heart rate variability (HRV) describe only linear and periodic behaviour, whereas more complex relationships cannot be recognised. A method that may be capable of assessing more complex properties is the non-linear measure of 'renormalised entropy.' A new concept of the method, RE(AR), has been developed, based on a non-linear renormalisation of autoregressive spectral distributions. To test the hypothesis that renormalised entropy may improve the result of high-risk stratification after myocardial infarction, it is applied to a clinical pilot study (41 subjects) and to prospective data of the St George's Hospital post-infarction database (572 patients). The study shows that the new RE(AR) method is more reproducible and more stable in time than a previously introduced method (p<0.001). Moreover, the results of the study confirm the hypothesis that on average, the survivors have negative values of RE(AR) (-0.11+/-0.18), whereas the non-survivors have positive values (0.03+/-0.22, p<0.01). Further, the study shows that the combination of an HRV triangular index and RE(AR) leads to a better prediction of sudden arrhythmic death than standard measurements of HRV. In summary, the new RE(AR) method is an independent measure in HRV analysis that may be suitable for risk stratification in patients after myocardial infarction.

Noninvasive assessment of Wedensky modulated signal-averaged electrocardiograms

Subthreshold stimulation without capture reduces the stimulation threshold and changes the action potential of subsequent suprathreshold stimulation, a phenomenon known as Wedensky modulation (WM). Patients with ventricular tachycardia (VT) inducible during electrophysiological testing (n = 47, mean age 63 +/- 13 years, 83% men), and healthy controls (n = 30, mean age 44 +/- 16 years, 60% men) were subjected to transthoracic external subthreshold stimulation between surface precordial and left subscapular patch electrodes. Stimuli of 5, 10, 20, and 40 mA were delivered for 2 ms, in synchrony with, or 20 ms after, R wave detection. A total of 60-200 subthreshold stimulated QRS complexes were averaged and compared with averaged nonstimulated complexes recorded during the same experimental session. To detect transient changes within the QRS complex, both signals were decomposed with 54 scales of Morlet analyzing wavelets (central frequencies 40-250 Hz). Wavelet vector magnitude was obtained for stimulated and nonstimulated complexes. Their difference created a wavelet residuum (WR) that characterized WM numerically. The surface area of the three-dimensional envelope of WR was measured and statistically compared between VT patients and healthy controls. WR showed a significantly greater increase in the spectral power of the stimulated complex in healthy controls than in VT patients (P < 0.01). In conclusion, (1) wavelet decomposition is a suitable tool to analyze WM, (2) WM in the late QRS complex is short, and (3) VT patients are less sensitive to WM, particularly at low subthreshold energies.

New descriptors of homogeneity of the propagation of ventricular repolarization

Available descriptors of irregularities of ventricular repolarization are of limited clinical value. We studied the effect of autonomic variations on several new descriptors of the three-dimensional T loop. Twelve-lead digital ECGs were recorded continuously in 40 healthy subjects at baseline in the supine position, during postural changes (supine-->sitting-->standing-->supine-->standing), and during Valsalva maneuver performed three times in the supine and three times in the standing positions. A minimum dimensional space was constructed from the 12-lead ECG, using singular value decomposition, on the basis of median ECG beats constructed from 10-second consecutive ECG recordings. Temporal variations (TLA and PL, which measure the T loop area, and LD, the interlead relationship during repolarization) and wavefront direction descriptors (TCRT, the deviation between the QRS and T vectors) were calculated and expressed as normalized values. Values of TLA, PL, and TCRT were significantly lower in the sitting than in the supine position (-38,139 +/- 9099 vs 47,133 +/- 7511, -0.017 +/- 0.005 vs 0.033 +/- 0.005 and -0.032 +/- 0.019 vs 0.071 +/- 0.015, respectively, P < 0.001 for all) and decreased further in the standing position (-88,288 +/- 14,468, -0.067 +/- 0.013, -0.198 +/- 0.025, respectively, P < 0.001 for all). LD increased from supine to sitting (98.7 +/- 29.4 vs -87.5 +/- 15.2, P < 0.001) and increased further, though nonsignificantly in the standing position (118.3 +/- 35.2). TLA, PL, and TCRT decreased from baseline during Valsalva in the supine (-34,118 +/- 11,424 vs 62,234 +/- 12,215, -0.038 +/- 0.014 vs 0.065 +/- 0.010, -0.08 +/- 0.03 vs 0.10 +/- 0.02, respectively, P < 0.001 for all) and standing positions (-108,263 +/- 21,051 vs -68,909 +/- 10,271, -0.109 +/- 0.014 vs -0.048 +/- 0.009, -0.30 +/- 0.035 vs -015 +/- 0.016, respectively, P < 0.05 for all). LD was significantly increased by Valsalva in the supine position (13 +/- 46 vs -153 +/- 30, P < 0.001) and nonsignificantly in the standing position (99 +/- 50 vs 86 +/- 30, P = NS). There were significant correlations among TLA, PL, and LD, and no significant correlation between TCRT and any of the temporal variation descriptors. These new temporal and wavefront direction descriptors are sensitive and rapid detectors of autonomic effects on ventricular repolarization.

Can the assessment of dynamic QT dispersion on exercise electrocardiogram predict sudden cardiac death in hypertrophic cardiomyopathy?

Premature sudden cardiac death (SD) is a critical event in the natural history of hypertrophic cardiomyopathy (HCM), and occurs during or just after physical exertion in approximately 60% of instances. Abnormalities in ventricular repolarization may not be present at rest in some patients but may become apparent under certain conditions. This study was performed to examine whether dynamic QT dispersion during exercise is associated with SD in HCM. Twenty-four HCM patients with catastrophic events (group I; 18 SD, 6 ventricular fibrillation) and 24 event-free survivors (group II) were studied. The two groups were pair-matched for age, gender, and maximum left ventricular wall thickness. QT intervals were manually measured from 12-lead exercise electrocardiogram (ECG) with a digitizing board. A custom-developed program was used to calculate QT and JT dispersion. The QT/RR relationship was evaluated by the slope of linear regression analysis. Before exercise, significant differences in heart rate and JT dispersion were found between group I and II. During exercise, heart rate increased and QT decreased significantly in both groups. QT and JT dispersion decreased in both groups, though the magnitude of reduction was greater in group I than in group II. No significant differences in QTc interval and QT or JT dispersion were found between the groups at any stages. At 3 minutes of recovery, heart rate had decreased but remained higher than before exercise, and all measurements of QT components remained shorter compared with those made before exercise in both groups. There was a strong correlation between QT and RR interval during exercise in all study patients (r = 0.95). No difference in the slope of QT against RR intervals was found between the groups (0.317 vs 0.319). In conclusion, exercise reduced QT dispersion in patients with HCM. The dynamic changes in QT dispersion examined by this method on exercise ECG did not make additional contributions in their risk stratification.

Reflex autonomic modulation of automatically measured repolarization parameters

Automatic recognition of repolarization abnormalities from the standard electrocardiogram (ECG) is of considerable clinical importance. This study examined the autonomic variations in automatically measured repolarization parameters, including maximum QT interval (QTmax), global QT dispersion (QTd), T area dispersion (T area D) and principal component analysis ratio 2 (PCA-2). Twelve-lead ECGs were recorded continuously in 40 healthy subjects during supine, sitting and standing positions, and during the Valsalva maneuver. With the exception of PCA-2, the other repolarization parameters correlated either moderately or strongly during the steady-state supine position. QTmax, PCA-2, and T area D decreased significantly between supine and sitting position (P < 0.001, P < 0.001 and P < 0.01, respectively). QTmax, QTD, and T area D decreased significantly between sitting and standing (P < 0.001, P < 0.05 and P < 0.01, respectively). All parameters significantly decreased between supine and standing position: QTmax (P < 0.001), QTD (P < 0.05), PCA-2 (P < 0.05) and T area D (P < 0.001). During Valsalva, only PCA-2 increased significantly (P < 0.001) between supine and standing position. There were no significant changes in QT dispersion and dispersion of T wave area during Valsalva, compared to baseline, in both supine and standing positions. Automatic conventional measures of repolarization heterogeneity have limited practical value in detecting the effects of autonomic changes on ventricular repolarization. Newer concepts evaluating spatial and temporal irregularity of ventricular repolarization are still needed to reliably detect the effects of autonomic activity on ventricular repolarization.

Automatic ectopic beat elimination in short-term heart rate variability measurement

Our studies deal with fully automatic measurement of heart rate variability (HRV) in short term electrocardiograms. Presently, all existing HRV analysis programs require user intervention for ectopic beat identification, especially of supraventricular ectopic beats (SVE). This makes the HRV measurement in large, e.g. epidemiological studies problematic. In this paper, we present a fully automatic algorithm for the discrimination of the ventricular (VE) and SVE ectopic beats from the normal QRS complexes suited for a reliable HRV analysis. The QRS identification is based on the template matching method. The ectopic beats are identified based on several morphological and timing properties of the electrocardiogram (ECG) signal. The method incorporates several approaches and makes HRV analysis of large numbers of electrocardiograms feasible. It uses the template matching for the basic morphology check of the QRS complex and the P-wave, the timing information to avoid unnecessary ectopic beat checks and to adjust thresholds and it also looks for a special QRS morphology, which is common in VEs. We used a testing set of 69 electrocardiograms selected from a large number of recordings. The selected ECGs contained abnormalities including ectopic beats, right branch bundle block, respiratory arrhythmia, blocked atrial extrasystole, high amplitude and wide T-waves. The evaluation of our method showed a specificity of 0.99, supraventricular ectopic beat sensitivity of 0.99 and ventricular ectopic beat sensitivity of 0.98.

Analysis of 12-lead T-wave morphology for risk stratification after myocardial infarction

BACKGROUND

The stratification of post-myocardial infarction (MI) patients at risk of sudden cardiac death remains important. The aim of the present study was to assess the prognostic value of novel T-wave morphology descriptors derived from resting 12-lead ECGs.

METHODS AND RESULTS

In 280 consecutive post-MI patients, a 12-lead ECG was recorded before discharge, optically scanned, and digitized. For the present study, 5 T-wave morphology descriptors were automatically calculated after singular value decomposition of the ECG signal. The total cosine R-to-T (TCRT [describes the global angle between repolarization and depolarization wavefront]) and the T-wave loop dispersion were univariately associated (P:=0.0002 and P:<0.002, respectively, U: test) with 27 prospectively defined clinical events in 261 patients (mean follow-up 32+/-10 months). Kaplan-Meier event probability curves for strata above and below the median confirmed the strong risk discrimination by TCRT and T-wave loop dispersion (P:<0.003 and P:<0.001, respectively, log-rank test). On Cox regression analysis, with the entering of age, left ventricular ejection fraction, heart rate, QRS width, reperfusion therapy, beta-adrenergic-blocker treatment, and standard deviation of R-R intervals on 24-hour Holter monitoring, TCRT (P:<0.03) yielded independent predictive value, whereas T-wave loop dispersion was of borderline independence (P:=0.064). Heart rate (P:<0.02), left ventricular ejection fraction (P:<0.02), and reperfusion therapy (P:<0.02) also remained in the final model.

CONCLUSIONS

Computerized T-wave morphology analysis of the 12-lead resting ECG permits independent assessment of post-MI risk and an improved risk stratification when combined with other risk markers.

QT dispersion does not represent electrocardiographic interlead heterogeneity of ventricular repolarization

INTRODUCTION

QT dispersion (QTd, range of QT intervals in 12 ECG leads) is thought to reflect spatial heterogeneity of ventricular refractoriness. However, QTd may be largely due to projections of the repolarization dipole rather than "nondipolar" signals.

METHODS AND RESULTS

Seventy-eight normal subjects (47+/-16 years, 23 women), 68 hypertrophic cardiomyopathy patients (HCM; 38+/-15 years, 21 women), 72 dilated cardiomyopathy patients (DCM; 48+/-15 years, 29 women), and 81 survivors of acute myocardial infarction (AMI; 63+/-12 years, 20 women) had digital 12-lead resting supine ECGs recorded (10 ECGs recorded in each subject and results averaged). In each ECG lead, QT interval was measured under operator review by QT Guard (GE Marquette) to obtain QTd. QTd was expressed as the range, standard deviation, and highest-to-lowest quartile difference of QT interval in all measurable leads. Singular value decomposition transferred ECGs into a minimum dimensional time orthogonal space. The first three components represented the ECG dipole; other components represented nondipolar signals. The power of the T wave nondipolar within the total components was computed to measure spatial repolarization heterogeneity (relative T wave residuum, TWR). QTd was 33.6+/-18.3, 47.0+/-19.3, 34.8+/-21.2, and 57.5+/-25.3 msec in normals, HCM, DCM, and AMI, respectively (normals vs DCM: NS, other P < 0.009). TWR was 0.029%+/-0.031%, 0.067%+/-0.067%, 0.112%+/-0.154%, and 0.186%+/-0.308% in normals, HCM, DCM, and AMI (HCM vs DCM: NS, other P < 0.006). The correlations between QTd and TWR were r = -0.0446, 0.2805, -0.1531, and 0.0771 (P = 0.03 for HCM, other NS) in normals, HCM, DCM, and AMI, respectively.

CONCLUSION

Spatial heterogeneity of ventricular repolarization exists and is measurable in 12-lead resting ECGs. It differs between different clinical groups, but the so-called QT dispersion is unrelated to it.

Pitfalls of the concept of incremental specificity used in comparisons of dual chamber VT/VF detection algorithms

The concepts of incremental specificity and incremental positive predictive accuracy (PPA) have been proposed to measure the success of dual chamber cardioverter defibrillator (ICD) algorithms for tachyarrhythmia detection in improving specificity while maintaining very high sensitivity to detection of episodes of ventricular tachycardia/fibrillation (VT/VF). While dual chamber VT/VF detection algorithms differ substantially among different ICD manufacturers, they all operate as "add-on" features to the single chamber elementary detection algorithms that are based on simple criteria of increased ventricular rate. The incremental specificity and PPA characterize the performance of the dual chamber detection operation in this "add-on" mode, that is within a database of rhythm episodes all meet the simple rate-based criteria. A statistical model of hypothetical devices has been used to demonstrate that the concepts of incremental specificity and PPA are very dependent on the composition of the database used to evaluate a particular dual chamber ICD. Because some sinus tachycardia and supraventricular tachyarrhythmias with regular atrioventricular conduction are more easily discriminated from true VT/VF than other supraventricular tachyarrhythmias, the model shows that rather than the performance of the dual chamber detection functions, the major contributor to the incremental specificity may be the proportion between the "easy" and "difficult" supraventricular episodes. The algorithms used by different ICD manufacturers to detect tachyarrhythmias based on ventricular rate are known to differ substantially in the ability to differentiate true VT/VF from other tachyarrhythmias. Consequently, the databases of rhythms against which the different dual camber ICDs are tested are also different in composition of different types of supraventricular tachyarrhythmias. Therefore, the values of incremental specificity and PPA reported by different manufacturers do not have an equivalent meaning and do not offer a valid comparison of the true performance of different dual chamber ICDs.

A new approach for TU complex characterization

In this paper, we present a new TU complex detection and characterization algorithm that consists of two stages; the first is a mathematical modeling of the electrocardiographic segment after QRS complex; the second uses classic threshold comparison techniques, over the signal and its first and second derivatives, to determine the significant points of each wave. Later, both T and U waves are morphologically classified. Amongst the principal innovations of this algorithm is the inclusion of U-wave characterization and a mathematical modeling stage, that avoids many of the problems of classic techniques when there is a low signal-to-noise ratio or when wave morphology is atypical. The results of the algorithm validation with the recently appeared QT database are also shown. For T waves these results are better when compared to other existing algorithms. U-wave results cannot be contrasted with other algorithms as, to our knowledge, none are available. Examples showing the causes of principal discrepancies between our algorithm and the QT database annotations are also given, and some ways of attempting to improve and benefit from the proposed algorithm are suggested.

Predictive value of wavelet decomposition of the signal-averaged electrocardiogram in idiopathic dilated cardiomyopathy

BACKGROUND

Wavelet decomposition of the signal-averaged electrocardiogram has been proposed as a method of detecting small and transient irregularities hidden within the QRS complex and of overcoming some of the limitations of time domain analysis of the signal-averaged electrocardiogram.

AIM

This study evaluated the potential utility of wavelet decomposition analysis in the risk stratification of patients with idiopathic dilated cardiomyopathy.

METHODS AND RESULTS

Both wavelet decomposition and time domain analysis were applied to the signal-averaged electrocardiogram recordings of 82 patients with idiopathic dilated cardiomyopathy (mean age 43 +/- 14 years, 60 men) and 72 normal controls (mean age 44 +/- 15 years, 48 men). Three conventional time domain indices and four wavelet decomposition analysis parameters (QRS length, maximum count, surface area, and relative length) were derived from each recording using a Del Mar CEWS system and an in-house software package, respectively. The results showed that (1) more patients with idiopathic dilated cardiomyopathy than without had late potentials, and that the filtered QRS duration was significantly longer in patients than in controls (P<0.001). Similarly, abnormal wavelet decomposition analysis was more common in patients and wavelet decomposition measurements were significantly different between patients and controls (P<0.01); (2) conventional time domain analysis did not distinguish between clinically stable patients and patients who developed progressive heart failure, or between patients with and without arrhythmic events; (3) wavelet decomposition analysis identified patients who went on to develop progressive heart failure but failed to distinguish patients with arrhythmic events from those without; (4) survival analyses of a mean follow-up of 23 months showed that patients with late potentials tended to develop progressive heart failure more frequently than others (P=0.06). Patients with an abnormal wavelet decomposition result more frequently developed progressive heart failure than those with a normal wavelet decomposition result (P=0.027); (5) in a univariate analysis (Cox model), wavelet decomposition measurements but not time domain indices significantly correlated with the development of progressive heart failure (P=0.01). Multivariate analysis showed that only left ventricular end-diastolic dimension and peak oxygen consumption during exercise remained significant predictors of progressive heart failure.

CONCLUSION

Wavelet decomposition analysis of the signal-averaged electrocardiogram is superior to conventional time domain analysis for identifying patients with idiopathic dilated cardiomyopathy at increased risk of clinical deterioration. Wavelet decomposition analysis, however, is unlikely to prospectively distinguish patients at a high risk of arrhythmic events in idiopathic dilated cardiomyopathy in its present form.

Can plasma fructosamine substitute for glycated haemoglobin (HbA1c) estimation in the assessment of diabetic control?

The 'gold standard' marker of overall glycaemic control in diabetes mellitus is the level of glycated haemoglobin (HbA1c). It is, however, an expensive and technically difficult assay and is rarely appropriate to tropical laboratories. Plasma fructosamine measurement is cheaper and easier, though it reflects shorter-term glycaemia. We have measured both indices of control in a group of 154 diabetic patients. There was close correlation between the two measurements (r = 0.6506, P < 0.001), but many patients with abnormal HbA1c levels had normal fructosamine levels. This resulted in an assay sensitivity (compared with HbA1c as gold standard) of only 30%, though specificity was 98%. We conclude that fructosamine measurement cannot be regarded as a substitute for HbA1c determination.

Summer-winter differences in 24 h variability of heart rate

OBJECTIVE

To examine possible seasonal changes in heart rate variability (HRV).

BACKGROUND

Greater than normal mortality from cardiovascular disease (CVD) in the winter has been reported for many countries and might be partly explained by considering seasonal changes in CVD risk factors. Depression of HRV is an independent predictor of arrhythmic complications and of cardiac death, and it is also among the variables that may be affected by the season of the year.

METHODS

We compared pairs of 24 h HRV data of 120 healthy men who were examined once in the summer and once in the winter. Multivariate analyses were performed for each dependent variable (HRV indexes) in separate statistical models with age, resting heart rate, serum level of cholesterol, cigarette smoking, body mass index, sports habits, alcohol consumption, systolic blood pressure, physical activity at work, years of education, consumption of energy, and season as the independent variables.

RESULTS

Although there were no seasonal differences in mean R-R interval, all indexes of HRV were found to be lower in the summer than they were during winter. Differences and 95% confidence intervals were standard deviation (SD) of coupling intervals between normal beats 12 ms, 6-17 ms; SD of 5 min mean R-R intervals 14 ms, 8-20 ms; mean of all 5 min SD of R-R intervals 2.0 ms, 0.6-2.5 ms; proportion of adjacent R-R intervals differing by > 50 ms 1.5%, 0.6-2.5% and root mean square of the difference between successive normal intervals 3.1 ms, 1.5-4 ms. Multivariate analyses showed that HRV in the winter was less than that in the summer even after adjustment for age, serum level of cholesterol, systolic blood pressure, and body mass index.

CONCLUSIONS

HRV indexes of healthy men vary physiologically by season, with lowest values obtained in the winter. Since low HRV is linked to pathologic conditions, the significance of seasonal changes for those suffering from CVD and their possible contribution to the greater mortality rates in winter have to be considered.

Depressed heart rate variability identifies postinfarction patients who might benefit from prophylactic treatment with amiodarone: a substudy of EMIAT (The European Myocardial Infarct Amiodarone Trial)

OBJECTIVES

This substudy tested a prospective hypothesis that European Myocardial Infarct Amiodarone Trial (EMIAT) patients with depressed heart rate variability (HRV) benefit from amiodarone treatment.

BACKGROUND

The EMIAT randomized 1,486 survivors of acute myocardial infarction (MI) aged < or =75 years with left ventricular ejection fraction (LVEF) < or =40% to amiodarone or placebo. Despite a reduction of arrhythmic mortality on amiodarone, all-cause mortality was not changed.

METHODS

Heart rate variability was assessed from prerandomization 24-h Holter tapes in 1,216 patients (606 on amiodarone). Two definitions of depressed HRV were used: standard deviation of normal to normal intervals (SDNN) < or =50 ms and HRV index < or =20 units. The survival of patients with depressed HRV was compared in the placebo and amiodarone arms. A retrospective analysis investigated the prospective dichotomy limits. All tests were repeated in five subpopulations: patients with first MI, patients on beta-adrenergic blocking agents, patients with LVEF < or =30%, patients with Holter arrhythmia and patients with baseline heart rate > or =75 beats/min.

RESULTS

Centralized Holter processing produced artificially high SDNN but accurate HRV index values. Heart rate variability index was < or =20 U in 363 (29.9%) patients (183 on amiodarone) with all-cause mortality 22.8% on placebo and 17.5% on amiodarone (23.2% reduction, p = 0.24) and cardiac arrhythmic mortality 12.8% on placebo and 4.4% on amiodarone (66% reduction, p = 0.0054). Among patients with prospectively defined depressed HRV, the largest reduction of all-cause mortality was in patients with first MI (placebo 17.9%, amiodarone 10.3%, 42.5% reduction, p = 0.079) and in patients with heart rate < or =75 beats/min (placebo 29.0%, amiodarone 19.3%, 33.7% reduction, p = 0.075). Among patients with first MI and depressed HRV, amiodarone treatment was an independent predictor of survival in a multivariate Cox analysis. The retrospective analysis found a larger reduction of mortality on amiodarone in 313 (25.7%) patients with HRV index < or =19 U: 23.9% on placebo and 17.1% on amiodarone (28.4% reduction, p = 0.15). This was more expressed in patients with first MI: 49.4% mortality reduction on amiodarone (p = 0.046), on beta-blockers: 69.0% reduction (p = 0.047) and with heart rate > or =75 beats/min: 37.9% reduction (p = 0.054).

CONCLUSION

Measurement of HRV in a large set of centrally processed Holter recordings is feasible with robust methods of assessment. Patients with LVEF < or =40% and depressed HRV benefit from prophylactic antiarrhythmic treatment with amiodarone. However, this finding needs confirmation in an independent data set before clinical practice is changed.

Measurement and interpretation of QT dispersion

QT dispersion was proposed as an index of the spatial inhomogeneity of ventricular recovery times. The results of studies that found significant correlation between dispersion of ventricular recovery times measured with monophasic action potentials and QT dispersion were interpreted as proof of the direct link between QT dispersion and the dispersion of ventricular recovery times. Later it was shown that QT dispersion is not a direct reflection of the spatial variation of the recovery times and cannot be used for quantification of this variation. The interlead variability of the QT intervals is a result of different projections of the spatial T-wave loop into the various electrocardiographic leads. The reliability of both manual and automatic measurement of QT dispersion is low and is often of the order of the differences of Qt dispersion between different patient groups. The measurement reliability is influenced by intrinsic factors (e.g., amplitude of the T wave) and extrinsic factors (e.g., noise, paper speed of recording, instruments for manual measurements, and type of algorithm and interalgorithmic settings for automatic measurement). There is very little to choose between the different indices of expression of QT dispersion, as well as between the different lead configurations used for its measurement. QT dispersion is not simply a result of measurement error, but a crude measure of abnormalities during the whole course of repolarization. Only grossly prolonged QT dispersion (e.g., > or =100 ms), must be interpreted simply as a sign of the abnormal course of the repolarization, and inferences about the actual dispersion of the ventricular recovery times should not be made. Newer concepts of assessment of the morphology of the T wave are already emerging and will probably be of higher clinical value.

Consistency of multicenter measurements of heart rate variability in survivors of acute myocardial infarction

Heart rate variability (HRV) analysis from 24-hour ambulatory ECG has been widely used in risk stratification of patients after myocardial infarction (MI). The accuracy of HRV assessment is known to potentially vary when different commercial systems are used. However, the consistency of HRV measurements has never been fully investigated. Twenty-six post-MI patients (mean age 59 +/- 8 years, 22 men) were studied, of whom 13 succumbed to sudden cardiac death (SCD) within 1 year and 13 remained alive for at least 3 years (MI survivors). Each patient had a 24-hour Holter ECG recorded before hospital discharge. HRV analysis was performed four times from the same recordings using three different Holter tape analysis systems (Marquette, Reynolds, and CardioData) by four independent operators (CardioData system was used twice, once in the United Kingdom and once in the United States). Mean normal-to-normal RR intervals (mNN) and 3 HRV parameters (SDNN, RMSSD, and HRV triangular index [HRVi]) were derived from each recording. The consistency of mNN and HRV measurements was evaluated by coefficient of variance (CV) and by the Bland-Altman method. The results demonstrated that (1) all indices measured by different systems were statistically similar (P = NS) except the measurement of RMSSD (P = 0.01), (2) the measurements of mNN were highly reproducible with a maximum mean difference of 1.8 +/- 13.8 ms and maximum limits of agreement from -14.6 to +15.6 ms. The maximum mean differences were--1.8 +/- 1.4 unit and 4.4 +/- 9.6 ms for HRVi and SDNN, respectively, and RMSSD was less reproducible with a maximum mean difference of--11.1 +/- 11.5 ms, and limits of agreement from -16.2 to +9.6 ms; and (3) the consistency of mNN (CV 0.9% +/- 0.9%) was significantly higher than that of HRVi, SDNN, and RMSSD (P < 0.0001). The consistency of HRVi was similar to that of SDNN (4.8% +/- 2.1% vs 5.7% +/- 4.8%, P = 0.4), and the consistency of RMSSD (26.6% +/- 13.3%) was significantly lower than that of the other measurements (P < 0.00001). In conclusion, the measurements of mNN by different analytical systems are the most consistent among the parameters studied. The global 24-hour measurements of HRV (SDNN and HRVi) are highly reproducible, whereas the measurement of short-term HRV components (RMSSD) is significantly less reproducible.

Short-, mid-, and long-term reproducibility of the atrial signal-averaged electrocardiogram in healthy subjects: comparison with the conventional ventricular signal-averaged electrocardiogram

Although atrial signal-averaged electrocardiogram (SAECG) has been proposed for noninvasive identification of patients with atrial tachyarrhythmias, the substantial variability of the measurement limits the clinical value. The aim of the study was to assess the short- to long-term reproducibility of atrial SAECG and to compare it to that of the conventional ventricular SAECG in 51 healthy volunteers (30 men; age 32 +/- 8 years). In each subject, SAECG recordings were obtained using MAC-VU electrocardiograph and HiRES and PHiRES software (Marquette Medical Systems) and repeated after 5 minutes, 1 day, 1 week, and 1 month. Automatically detected onset and offset of the filtered QRS complex and P wave were subsequently corrected by two independent observers, and the averaged values were used for the analysis. Conventional ventricular SAECG parameters: filtered QRS duration (QRStot), low amplitude signal duration, and root mean square voltage (RMS) of the terminal 40 ms of QRS, and 5 atrial parameters: filtered P wave duration (Ptot), RMS of the terminal 40, 30, 20 ms, and of the entire P wave were obtained. Relative errors of different pairs of measures were used to assess the intrasubject reproducibility. QRStot and Ptot were the most reproducible parameters. The relative errors after 5 minutes, 1 day, 1 week, and 1 month were 0.8% to 2.4% for QRStot, and 1.3% to 4.2% for Ptot. For RMS voltages, the relative errors exceeded 15% in short-term and 20% in long-term recordings. Although Ptot was statistically less reproducible than QRStot, the reproducibility of the former was good and comparable to that of the QRStot. The reproducibility of the voltage parameters was significantly poorer than that of the duration parameters. The study showed a satisfactory short- and long-term reproducibility of Ptot in the atrial SAECG in healthy subjects. However, low reproducibility of the voltage parameters should be considered in clinical applications.

"Optimum" formulae for heart rate correction of the QT interval

The study investigated the performance of several generic QT/RR regression models in a dataset of QT and RR intervals obtained from resting electrocardiograms of 1,100 healthy subjects (913 male, mean age 33+/-12 years). All the investigated models have three degrees of freedom and included the hyperparabolic and hyper-hyperbolic models, algorithmic models, negative exponential models, and models involving inverse tangent, hyperbolic tangent, and inverse hyperbolic sign functions. For each generic model, the combination of parameters leading to the lowest regression residuum was found. The results of the study show that the goodness of the optimum fit is practically independent of the generic form of the regression model and that different datasets lead to different combinations of the numerical values of parameters of the corresponding regression models. The study concludes that the search for a universally applicable QT/RR regression model that would provide the best fit in all circumstances is most likely fruitless. Rather, individual studies such as those investigating drug related QT prolongation might benefit from establishing a best-fit regression that would provide the optimum model for each particular dataset.

Comparison of different methods for manual P wave duration measurement in 12-lead electrocardiograms

To determine whether different methods for the manual measurement of P wave duration are mutually consistent, we evaluated the intraobserver and interobserver errors of P wave measurements obtained in three different ways: (1) by cursor on a high resolution computer screen (on screen), (2) by calipers and a magnifying glass (on paper), and (3) by a high resolution digitizing board (on board). The agreement between the methods was assessed in 30 normal subjects and 30 patients with a history of atrial fibrillation. The maximum P wave duration (P maximum), the minimum P wave duration (P minimum), mean P wave duration (P mean), P wave dispersion (P dispersion = P maximum - P minimum), and the standard deviation of the P wave duration in all measured leads (P SD) were calculated from a 12-lead electrocardiogram in each subject. Only P maximum, P mean, and P dispersion were significantly higher in patients than in controls with all three methods. Intraobserver and interobserver relative errors were significantly different among the three methods; the lowest errors were associated with the on-screen measurement. The agreement between the three different methods was acceptable for P maximum, P mean, and P SD and rather poor for P minimum and P dispersion in both groups. The differences of the measurement by different methods did not consistently differ between the two groups. Hence, the on-screen measurements are consistent with other manual methods and provide more stable results. Manual measurement of ECG patterns should be preferably performed with digital ECG recordings displayed on a high resolution computer screen.

Automatic measurement of long-term heart rate variability by implanted single-chamber devices

Heart rate variability (HRV) measurement is an established technology for the assessment of cardiac autonomic status. Recently 24 h HRV has been shown to correlate with disease severity in heart failure. This potentially makes continuous 24 h HRV measurement suitable for monitoring of heart-failure patients. Day-to-day 24 h measurement of HRV is, in principle, feasible when implemented using implanted devices (pacemakers and defibrillators) used in patients who are predominantly in the sinus rhythm. However, a number of such devices used in heart-failure patients are single-chamber devices, in which the distinction between sinus rhythm beats and ectopic beats is problematic. The study investigates whether a reasonably accurate 24 h HRV measurement can be achieved by automatic algorithms, suitable for implementation using implanted devices, without the need for identification of ectopic beats. A set of 5321 nominal 24 h Holter recordings of cardiac patients are used. Each of the recordings contains at least one ectopic beat; approximately 30% of the recordings have more than 1% of ectopic beats. Conventional 24 h measures of HRV, that is the SDNN, HRV index, and SDANN indices, are obtained from each recording after elimination of the ectopic beats and are approximated by HRV measures computed by the same formulas without exclusion of the ectopic beats. The SDANN values are also approximated by the standard deviation of 5 min medians of all RR intervals (SDMRR measure). The errors introduced by including the ectopic beats in the HRV computation were evaluated using the Bland-Altman statistics and by Cohen's kappa statistics investigating the precision of identifying patients with depressed and preserved 24 h HRV. The SDNN measure is very sensitive to the quality of the RR interval sequence and cannot be reasonably used without distinction between sinus rhythm and ectopic beats. The HRV index measure is marginally more acceptable when used without ectopic elimination. The SDANN is rather insensitive, and its replacement by SDMRR values leads to relative errors in the region of 2-5% that are almost independent of the number of ectopic beats included. Even in recordings with a substantial proportion of ectopic beats, a practically acceptable (kappa > 0.9) identification of depressed and preserved SDANN values is possible without ectopic elimination. Thus, continuous monitoring of 24 h HRV is technically feasible within implanted devices, provided the SDANN measure is monitored and either computed from the sequence of all RR intervals or, potentially preferably, replaced by the SDMRR measure.