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Objective: To compare the QT/RR relation in healthy subjects in order to investigate the differences in optimum heart rate correction of the QT interval. Methods: 50 healthy volunteers (25 women, mean age 33.6 (9.5) years, range 19-59 years) took part. Each subject underwent serial 12 lead electrocardiographic monitoring over 24 hours with a 10 second ECG obtained every two minutes. QT intervals and heart rates were measured automatically. In each subject, the QT/RR relation was modelled using six generic regressions, including a linear model (QT = β + α × RR), a hyperbolic model (QT = β + α/RR), and a parabolic model (QT = β × RR α ). For each model, the parallelism and identity of the regression lines in separate subjects were statistically tested. Results: The patterns of the QT/RR relation were very different among subjects. Regardless of the generic form of the regression model, highly significant differences were found not only between the regression lines but also between their slopes. For instance, with the linear model, the individual slope (parameter α) of any subject differed highly significantly (p < 0.000001) from the linear slope of no fewer than 21 (median 32) other subjects. The linear regression line of 20 subjects differed significantly (p < 0.000001) from the linear regression lines of each other subject. Conversion of the QT/RR regressions to QTc heart rate correction also showed substantial intersubject differences. Optimisation of the formula QTc = QT/RR α led to individual values of α ranging from 0.234 to 0.486. Conclusion: The QT/RR relation exhibits a very substantial intersubject variability in healthy volunteers. The hypothesis underlying each prospective heart rate correction formula that a "physiological" QT/RR relation exists that can be mathematically described and applied to all people is incorrect. Any general heart rate correction formula can be used only for very approximate clinical assessment of the QTc interval over a narrow window of resting heart rates. For detailed precise studies of the QTc interval (for example, drug induced QT interval prolongation), the individual QT/RR relation has to be taken into account.T he QT interval adapts to changes in heart rate, which makes it difficult to compare the QT interval recorded at different heart rates. To allow such a comparison, the concept of the heart rate corrected QTc interval was developed and many formulas have been proposed to describe the QT interval heart rate adaptation. Bazett's formula 1 is both the most frequently used and the most criticised. 2-4In principle, every heart rate correction formula assumes that a mathematical form exists to describe the physiological QT/RR relation. Such a form may be converted into a formula that normalises a measured QT interval to that which would be associated with a "standard" heart rate, for example, of 60 beats/min. Most studies that have proposed a heart rate correction formula relied on QT and RR interval data obtained from healthy volunteers, different groups of patients, o...

Three new approaches for the analysis of ventricular repolarisation in 12-lead electrocardiograms (ECGs) are presented: the spatial and temporal variations in T-wave morphology and the wavefront direction difference between the ventricular depolarisation and repolarisation waves. The spatial variation characterises the morphology differences between standard leads. The temporal variation measures the change in interlead relationships. A minimum dimensional space, constructed by ECG singular value decomposition, is used. All descriptors are measured using the ECG vector in the constructed space and the singular vectors that define this space. None of the descriptors requires time domain measurements (e.g. the precise detection of the T-wave offset), and so the inaccuracies associated with conventional QT interval related parameters are avoided. The new descriptors are compared with the conventional measurements provided by a commercial system for an automatic evaluation of QT interval and QT dispersion in digitally recorded 12-lead ECGs. The basic comparison uses a set of 1100 normal ECGs. The short-term intrasubject reproducibility of the new descriptors is compared with that of the conventional measurements in a set of 760 ECGs recorded in 76 normal subjects and a set of 630 ECGs recorded in 63 patients with hypertrophic cardiomyopathy (ten serial recordings in each subject of both these sets). The discriminative power of the new and conventional parameters to distinguish normal and abnormal repolarisation patterns is compared using the same set. The results show that the new parameters do not correlate with the conventional QT interval-related descriptors (i.e. they assess different ECG qualities), are generally more reproducible than the conventional parameters, and lead to a more significant separation between normal and abnormal ECGs, both univariately and in multivariate regression models.

AimsTo investigate the combination of heart rate turbulence (HRT) and deceleration capacity (DC) as risk predictors in post-infarction patients with left ventricular ejection fraction (LVEF) > 30%.Methods and resultsWe enrolled 2343 consecutive survivors of acute myocardial infarction (MI) (<76 years) in sinus rhythm. HRT and DC were obtained from 24 h Holter recordings. Patients with both abnormal HRT (slope ≤ 2.5 ms/RR and onset ≥ 0%) and abnormal DC (≤4.5 ms) were considered suffering from severe autonomic failure (SAF) and prospectively classified as high risk. Primary and secondary endpoints were all-cause, cardiac, and sudden cardiac mortality within the first 5 years of follow-up. During follow-up, 181 patients died; 39 deaths occurred in 120 patients with LVEF ≤ 30%, and 142 in 2223 patients with LVEF>30% (cumulative 5-year mortality rates of 37.9% and 7.8%, respectively). Among patients with LVEF > 30%, SAF identified another high-risk group of 117 patients with 37 deaths (cumulative 5-year mortality rates of 38.6% and 6.1%, respectively). Merging both high-risk groups (i.e. LVEF ≤ 30% and/or SAF) doubled the sensitivity of mortality prediction compared with LVEF ≤ 30% alone (21.1% vs. 42.1%, P < 0.001) while preserving 5-year mortality rate (38.2%).ConclusionIn post-MI patients with LVEF>30%, SAF identifies a high-risk group equivalent in size and mortality risk to patients with LVEF ≤ 30%.