QT interval variability in type 2 diabetic patients with cardiac sympathetic dysinnervation assessed by 123I-metaiodobenzylguanidine scintigraphy

Cardiac innervations in diabetes mellitus-Anatomical evidence of neuropathy

The extensive innervations of the heart include a complex network of sympathetic, parasympathetic, and sensory nerves connected in loops that serve to regulate cardiac output. Metabolic dysfunction in diabetes affects many different organ systems, including the cardiovascular system; it causes cardiac arrhythmias, silent myocardial ischemia, and sudden cardiac death, among others. These conditions are associated with damage to the nerves that innervate the heart, cardiac autonomic neuropathy (CAN), which is caused by various pathophysiological mechanisms. In this review, the main facts about the anatomy of cardiac innervations and the current knowledge of CAN, its pathophysiological mechanisms, and its diagnostic approach are discussed. In addition, anatomical evidence for CAN from human and animal studies has been summarized.

Insulin Resistance is Associated with Longitudinal Changes of Cardiac Repolarization Heterogeneity in Apparently Healthy Subjects

INTRODUCTION

Increased heterogeneity in ventricular repolarization is a risk factor of sudden cardiac death, but its natural history is unclear. Here we examined whether insulin resistance is associated with longitudinal change in ventricular repolarization heterogeneity in apparently healthy subjects.

METHODS

The study subjects were participants in health checkups in cohort 1 and cohort 2, which were followed up for 6 years and 5 years, respectively. Subjects with diabetes, cardiovascular disease, or renal disease at baseline were excluded from the analyses. As indices of insulin resistance, the homeostasis model assessment of insulin resistance (HOMA-IR) and triglyceride to HDL-cholesterol ratio (TG/HDL-C) were used in cohort 1 and cohort 2, respectively. Heterogeneity in ventricular repolarization was assessed by heart rate-corrected Tpeak-Tend interval in V5 (cTpTe), QT interval, and QT dispersion. In regression analyses, parameters with a skewed distribution were normalized by logarithmic transformation or by Box-Cox transformation.

RESULTS

In longitudinal analyses, Box-Cox-transformed cTpTe at the end of follow-up was weakly correlated with log HOMA-IR at baseline in cohort 1 (n = 153, r = - 0.207, 95% CI - 0.354 to - 0.050, p = 0.010) and with log TG/HDL-C at baseline in cohort 2 (n = 738, r = - 0.098, 95% CI - 0.169 to - 0.026, p = 0.008). Multiple regression analysis showed that indices of insulin resistance, but not glycosylated hemoglobin (HbA1c) or plasma glucose, at baseline were significant explanatory variables for cTpTe at the end of follow-up. Neither QT interval nor QT dispersion was correlated with metabolic parameters.

CONCLUSION

Insulin resistance may be involved in the longitudinal increase of ventricular repolarization heterogeneity in apparently healthy subjects.

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.

Nocturnal ventricular repolarization lability predicts cardiovascular mortality in the Sleep Heart Health Study

The objective of the present study was to quantify repolarization lability and its association with sex, sleep stage, and cardiovascular mortality. We analyzed polysomnographic recordings of 2,263 participants enrolled in the Sleep Heart Health Study (SHHS-2). Beat-to-beat QT interval variability (QTV) was quantified for consecutive epochs of 5 min according to the dominant sleep stage [wakefulness, nonrapid eye movement stage 2 (NREM2), nonrapid eye movement stage 3 (NREM3), and rapid eye movement (REM)]. To explore the effect of sleep stage and apnea-hypopnea index (AHI) on QT interval parameters, we used a general linear mixed model and mixed ANOVA. The Cox proportional hazards model was used for cardiovascular disease (CVD) death prediction. Sex-related differences in T wave amplitude ( P < 0.001) resulted in artificial QTV differences. Hence, we corrected QTV parameters by T wave amplitude for further analysis. Sleep stages showed a significant effect ( P < 0.001) on QTV. QTV was decreased in deep sleep compared with wakefulness, was higher in REM than in NREM, and showed a distinct relation to AHI in all sleep stages. The T wave amplitude-corrected QTV index (cQTVi) in REM sleep was predictive of CVD death (hazard ratio: 2.067, 95% confidence interval: 1.105–3.867, P < 0.05) in a proportional hazards model. We demonstrated a significant impact of sleep stages on ventricular repolarization variability. Sex differences in QTV are due to differences in T wave amplitude, which should be corrected for. Independent characteristics of QTV measures to sleep stages and AHI showed different behaviors of heart rate variability and QTV expressed as cQTVi. cQTVi during REM sleep predicts CVD death.

NEW & NOTEWORTHY We demonstrate here, for the first time, a significant impact of sleep stages on ventricular repolarization variability, quantified as QT interval variability (QTV). We showed that QTV is increased in rapid eye movement sleep, reflective of high sympathetic drive, and predicts death from cardiovascular disease. Sex-related differences in QTV are shown to be owing to differences in T wave amplitude, which should be corrected for.

Increased Short-Term Beat-to-Beat QT Interval Variability in Patients with Impaired Glucose Tolerance

Prediabetic states and diabetes are important risk factors for cardiovascular morbidity and mortality. Determination of short-term QT interval variability (STVQT) is a non-invasive method for assessment of proarrhythmic risk. The aim of the study was to evaluate the STVQT in patients with impaired glucose tolerance (IGT). 18 IGT patients [age: 63 ± 11 years, body mass index (BMI): 31 ± 6 kg/m2, fasting glucose: 6.0 ± 0.4 mmol/l, 120 min postload glucose: 9.0 ± 1.0 mmol/l, hemoglobin A1c (HbA1c): 5.9 ± 0.4%; mean ± SD] and 18 healthy controls (age: 56 ± 9 years, BMI: 27 ± 5 kg/m2, fasting glucose: 5.2 ± 0.4 mmol/l, 120 min postload glucose: 5.5 ± 1.3 mmol/l, HbA1c: 5.4 ± 0.3%) were enrolled into the study. ECGs were recorded, processed, and analyzed off-line. The RR and QT intervals were expressed as the average of 30 consecutive beats, the temporal instability of beat-to-beat repolarization was characterized by calculating STVQT as follows: STVQT = Σ|QTn + 1 - QTn| (30x√2)-1. Autonomic function was assessed by means of standard cardiovascular reflex tests. There were no differences between IGT and control groups in QT (411 ± 43 vs 402 ± 39 ms) and QTc (431 ± 25 vs 424 ± 19 ms) intervals or QT dispersion (44 ± 13 vs 42 ± 17 ms). However, STVQT was significantly higher in IGT patients (5.0 ± 0.7 vs 3.7 ± 0.7, P < 0.0001). The elevated temporal STVQT in patients with IGT may be an early indicator of increased instability of cardiac repolarization during prediabetic conditions.

Heart rate independent QT variability component can detect subclinical cardiac autonomic neuropathy in diabetes

Cardiac autonomic neuropathy (CAN) may lead to life threatening arrhythmia due to denervation of both the parasympathetic and sympathetic branches of autonomic nervous system innervating the heart. CAN is a frequently under diagnosed complication of diabetes, because a patient can have asymptomatic CAN for several years before it is clinically apparent. However, detection of CAN at the early or subclinical stage leads to more effective treatment outcomes. Cardiac autonomic reflex tests (CART) (i.e. Ewing test battery) are normally used for the detection and staging of CAN. These tests have limitations with the necessity of active participation of the patients for test maneuvers, as a majority of patients will not be able to complete all five tests required due to comorbidities such as frailty, obesity or cardiorespiratory disease. CAN affects both heart rate (measured by RR interval dynamics) and ventricular repolarization function (i.e. QT interval dynamics) of the heart, which can be efficiently analyzed from surface ECG. Therefore, ECG based diagnosis techniques of CAN analysis are becoming popular as they can reduce the limitations of CARTs used traditionally for CAN detection and it complements CART results. In this study, the performance of an ECG based QTV feature derived using a model free approach, which can quantify the QTV component not affected directly by the heart rate (HR) variation, is compared with some other measures of QTV and HRV in subclinical CAN detection in diabetes. Short-term ECGs (i.e. 5 min long) of 60 diabetic subjects without CAN and 50 diabetic subjects detected with early level of CAN determined by CART were analyzed. The proposed measure for quantifying the QTV component independent of HR denoted as QTV~RR stands out to be more discriminatory than other existing variability measures of QTV and HRV in subclinical detection of CAN.

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.

QT interval variability in body surface ECG: measurement, physiological basis, and clinical value: position statement and consensus guidance endorsed by the European Heart Rhythm Association jointly with the ESC Working Group on Cardiac Cellular Electrophysiology

This consensus guideline discusses the electrocardiographic phenomenon of beat-to-beat QT interval variability (QTV) on surface electrocardiograms. The text covers measurement principles, physiological basis, and clinical value of QTV. Technical considerations include QT interval measurement and the relation between QTV and heart rate variability. Research frontiers of QTV include understanding of QTV physiology, systematic evaluation of the link between QTV and direct measures of neural activity, modelling of the QTV dependence on the variability of other physiological variables, distinction between QTV and general T wave shape variability, and assessing of the QTV utility for guiding therapy. Increased QTV appears to be a risk marker of arrhythmic and cardiovascular death. It remains to be established whether it can guide therapy alone or in combination with other risk factors. QT interval variability has a possible role in non-invasive assessment of tonic sympathetic activity.

Relation between QT interval variability and muscle sympathetic nerve activity in normal subjects

Beat-to-beat variability of the QT interval (QTV) is sought to provide an indirect noninvasive measure of sympathetic nerve activity, but a formal quantification of this relationship has not been provided. In this study we used power contribution analysis to study the relationship between QTV and muscle sympathetic nerve activity (MSNA). ECG and MSNA were recorded in 10 healthy subjects in the supine position and after 40° head-up tilt. Power spectrum analysis was performed using a linear autoregressive model with two external inputs: heart period (RR interval) variability (RRV) and MSNA. Total and low-frequency power of QTV was decomposed into contributions by RRV, MSNA, and sources independent of RRV and MSNA. Results show that the percentage of MSNA power contribution to QT is very small and does not change with tilt. RRV power contribution to QT power is notable and decreases with tilt, while the greatest percentage of QTV is independent of RRV and MSNA in the supine position and after 40° head-up tilt. In conclusion, beat-to-beat QTV in normal subjects does not appear to be significantly affected by the rhythmic modulations in MSNA following low to moderate orthostatic stimulation. Therefore, MSNA oscillations may not represent a useful surrogate for cardiac sympathetic nerve activity at moderate levels of activation, or, alternatively, sympathetic influences on QTV are complex and not quantifiable with linear shift-invariant autoregressive models.

Detecting Subclinical Diabetic Cardiac Autonomic Neuropathy by Analyzing Ventricular Repolarization Dynamics

In this study, a linear parametric modeling technique was applied to model ventricular repolarization (VR) dynamics. Three features were selected from the surface ECG recordings to investigate the changes in VR dynamics in healthy and cardiac autonomic neuropathy (CAN) participants with diabetes including heart rate variability (calculated from RR intervals), repolarization variability (calculated from QT intervals), and respiration [calculated by ECG-derived respiration (EDR)]. Surface ECGs were recorded in a supine resting position from 80 age-matched participants (40 with no cardiac autonomic neuropathy (NCAN) and 40 with CAN). In the CAN group, 25 participants had early/subclinical CAN (ECAN) and 15 participants were identified with definite/clinical CAN (DCAN). Detecting subclinical CAN is crucial for designing an effective treatment plan to prevent further cardiovascular complications. For CAN diagnosis, VR dynamics was analyzed using linear parametric autoregressive bivariate (ARXAR) and trivariate (ARXXAR) models, which were estimated using 250 beats of derived QT, RR, and EDR time series extracted from the first 5 min of the recorded ECG signal. Results showed that the EDR-based models gave a significantly higher fitting value (p < 0.0001) than models without EDR, which indicates that QT-RR dynamics is better explained by respiratory-information-based models. Moreover, the QT-RR-EDR model fitting values gradually decreased from the NCAN group to ECAN and DCAN groups, which indicate a decoupling of QT from RR and the respiration signal with the increase in severity of CAN. In this study, only the EDR-based model significantly distinguished ECAN and DCAN groups from the NCAN group (p < 0.05) with large effect sizes (Cohen's d > 0.75) showing the effectiveness of this modeling technique in detecting subclinical CAN. In conclusion, the EDR-based trivariate QT-RR-EDR model was found to be better in detecting the presence and severity of CAN than the bivariate QT-RR model. This finding also establishes the importance of adding respiratory information for analyzing the gradual deterioration of normal VR dynamics in pathological conditions, such as diabetic CAN.

Beat-to-beat QT interval variability and T-wave amplitude in patients with myocardial infarction

The purpose of this study was to investigate the effects of T-wave amplitude and ECG lead on beat-to-beat QT interval variability (QTV) in patients with myocardial infarction (MI) compared to healthy subjects. Standard resting 12-lead ECGs of 79 MI patients and 69 healthy subjects were investigated. Beat-to-beat QT intervals were measured separately for each lead using a template matching algorithm. In addition, we extracted the beat-to-beat T-wave amplitude in each lead. We computed the standard deviation of beat-to-beat QT intervals as a marker of QTV for both healthy subjects and MI patients. Significant QTV differences were observed between the 12 ECG leads as well as between the groups of healthy subjects and MI patients. Beat-to-beat QTV was significantly higher in MI patients than in healthy subjects for half of the leads. Furthermore, significant T-wave amplitude differences across leads and between groups were observed. A significant inverse relation between beat-to-beat QTV and T-wave amplitude was demonstrated. The group differences in QTV remained significant after co-varying for the T-wave amplitude. In conclusion, the increase in beat-to-beat QTV that has been repeatedly reported in patients with MI is partly due to the lower T-wave amplitudes. However, QTV remains significantly increased in MI patients after covarying for this effect.

Heart rate complexity and cardiac sympathetic dysinnervation in patients with type 2 diabetes mellitus

Cardiovascular autonomic neuropathy (CAN) is one of the most severe complications of type 2 diabetes mellitus (T2DM). The aim of this study was to investigate associations of cardiac sympathetic dysinnervation (CSD; by (123)I-MIBG scintigraphy) with short-term heart rate variability (HRV) measured by traditional vs. complexity markers. ECG was measured in 31 diabetic patients during rest over a period of 5 minutes and HRV quantified in different domains (time and frequency domain, scaling properties, symbolic dynamics). (123)I-MIBG scintigraphy identified 16 patients with CSD. Resting heart rate was increased and HRV reduced in these patients. In a subgroup of 16 patients ECG was also measured during standing. Changes in several HRV measures upon standing demonstrated cardiac responsiveness to orthostatic stress. Strong correlations between HRV, measured during standing, and CSD were observed with metrics based on symbolic dynamics. In conclusion, HRV assessment during standing may be useful for assessing cardiac sympathetic dysinnervation in patients with type 2 diabetes mellitus.