QT variability improves risk stratification in patients with dilated cardiomyopathy

The pivotal role of ECG in cardiomyopathies

Cardiomyopathies are a heterogeneous group of pathologies characterized by structural and functional alterations of the heart. Recent technological advances in cardiovascular imaging offer an opportunity for deep phenotypic and etiological definition. Electrocardiogram (ECG) is the first-line diagnostic tool in the evaluation of both asymptomatic and symptomatic individuals. Some electrocardiographic signs are pathognomonic or fall within validated diagnostic criteria of individual cardiomyopathy such as the inverted T waves in right precordial leads (V1-V3) or beyond in individuals with complete pubertal development in the absence of complete right bundle branch block for the diagnosis of arrhythmogenic cardiomyopathy of the right ventricle (ARVC) or the presence of low voltages typically seen in more than 60% of patients with amyloidosis. Most other electrocardiographic findings such as the presence of depolarization changes including QRS fragmentation, the presence of epsilon wave, the presence of reduced or increased voltages as well as alterations in the repolarization phase including the negative T waves in the lateral leads, or the profound inversion of the T waves or downsloping of the ST tract are more non-specific signs which can however raise the clinical suspicion of cardiomyopathy in order to initiate a diagnostic procedure especially using imaging techniques for diagnostic confirmation. Such electrocardiographic alterations not only have a counterpart in imaging investigations such as evidence of late gadolinium enhancement on magnetic resonance imaging, but may also have an important prognostic value once a definite diagnosis has been made. In addition, the presence of electrical stimulus conduction disturbances or advanced atrioventricular blocks that can be seen especially in conditions such as cardiac amyloidosis or sarcoidosis, or the presence of left bundle branch block or posterior fascicular block in dilated or arrhythmogenic left ventricular cardiomyopathies are recognized as a possible expression of advanced pathology. Similarly, the presence of ventricular arrhythmias with typical patterns such as non-sustained or sustained ventricular tachycardia of LBBB morphology in ARVC or non-sustained or sustained ventricular tachycardia with an RBBB morphology (excluding the "fascicular pattern") in arrhythmogenic left ventricle cardiomyopathy could have a significant impact on the course of each disease. It is therefore clear that a learned and careful interpretation of ECG features can raise suspicion of the presence of a cardiomyopathy, identify diagnostic "red flags" useful for orienting the diagnosis toward specific forms, and provide useful tools for risk stratification. The purpose of this review is to emphasize the important role of the ECG in the diagnostic workup, describing the main ECG findings of different cardiomyopathies.

The electrocardiogram in non-ischaemic-dilated cardiomyopathy

This article summarizes the main electrocardiogram (ECG) findings in dilated cardiomyopathy (DCM) patients. Recent reports are described in the great 'pot' of DCM peculiar ECG patterns that are typical of specific forms of DCM. Patients with late gadolinium enhancement on CMR, who are at greatest arrhythmic risk, have also distinctive ECG features. Future studies in large DCM populations should evaluate the diagnostic and prognostic value of the ECG.

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

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

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.

Repolarization variability independent of heart rate during sympathetic activation elicited by head-up tilt

The fraction of repolarization variability independent of RR interval variability is of clinical interest. It has been linked to direct autonomic nervous system (ANS) regulation of the ventricles in healthy subjects and seems to reflect the instability of the ventricular repolarization process in heart disease. In this study, we sought to identify repolarization measures that best reflect the sympathetic influences on the ventricles independent of the RR interval. ECG was recorded in 46 young subjects during supine and then following 45 degrees head-up tilt. RR intervals and five repolarization features (QTend, QTpeak, RTend, RTpeak, and TpTe) were extracted from the ECG recordings. Repolarization variability was separated into RR-dependent and RR-independent variability using parametric spectral analysis. Results show that LF power of TpTe is independent of RR in both supine and tilt, while the LF power of QTend and RTend independent of RR and respiration increases following tilt. We conclude that TpTe is independent of RR and is highly affected by respiration. QTend and RTend LF power might reflect the sympathetic influences on the ventricles elicited by tilt. Graphical abstract.

Recording duration and short-term reproducibility of heart rate and QT interval variability in patients with myocardial infarction

Beat-to-beat variability of the QT interval (QTV) measured on surface ECG has emerged as a potential marker for ventricular repolarization instability and has been used along with heart rate variability (HRV) to predict arrhythmic risk. Since measurement modalities of QTV have not been standardized, the objective of this study was to investigate the effect of ECG recording duration on QTV as well as HRV. Using a database of 30 min ECG recorded from 500 patients with acute myocardial infraction during rest, we extracted RR and QT interval time series and estimated different HRV and QTV metrics over windows of varying length. Analysis of variance (ANOVA) and intra-class correlation analyses were computed to investigate the effect of recording length on consistency and short-term reproducibility of HRV and QTV variables. Good consistency (non-significant ANOVA results) and short-term reproducibility (intra-class correlation coefficients  >0.8) were demonstrated for all but standard deviation based metrics when at least 200 beats were included in the estimation. In conclusion, QTV can be quantified from resting ECG with good short-term consistency and reproducibility that is comparable to that of HRV.

Ventricular repolarization measures for arrhythmic risk stratification

Ventricular repolarization is a complex electrical phenomenon which represents a crucial stage in electrical cardiac activity. It is expressed on the surface electrocardiogram by the interval between the start of the QRS complex and the end of the T wave or U wave (QT). Several physiological, pathological and iatrogenic factors can influence ventricular repolarization. It has been demonstrated that small perturbations in this process can be a potential trigger of malignant arrhythmias, therefore the analysis of ventricular repolarization represents an interesting tool to implement risk stratification of arrhythmic events in different clinical settings. The aim of this review is to critically revise the traditional methods of static analysis of ventricular repolarization as well as those for dynamic evaluation, their prognostic significance and the possible application in daily clinical practice.

Ventricular repolarization measures for arrhythmic risk stratification

Ventricular repolarization is a complex electrical phenomenon which represents a crucial stage in electrical cardiac activity. It is expressed on the surface electrocardiogram by the interval between the start of the QRS complex and the end of the T wave or U wave (QT). Several physiological, pathological and iatrogenic factors can influence ventricular repolarization. It has been demonstrated that small perturbations in this process can be a potential trigger of malignant arrhythmias, therefore the analysis of ventricular repolarization represents an interesting tool to implement risk stratification of arrhythmic events in different clinical settings. The aim of this review is to critically revise the traditional methods of static analysis of ventricular repolarization as well as those for dynamic evaluation, their prognostic significance and the possible application in daily clinical practice.