Mohammad Hasan Imam

QT Variability Index Changes With Severity of Cardiovascular Autonomic Neuropathy

Cardiovascular autonomic neuropathy (CAN) has been frequently postulated to increase susceptibility to ventricular arrhythmias and sudden cardiac death in diabetic patients. The relation between the progression of CAN in diabetes and ventricular repolarization remains to be fully described. Therefore, this study examined QT interval variability and heart rate interbeat variability to identify any alterations of cardiac repolarization in diabetic patients in relation to severity of CAN. Seventy control participants without (CAN-) and 74 patients with CAN (CAN+) were enrolled in this study. Among 74 CAN+ patients, 62 are early CAN+ (eCAN+) , and 12 are definite CAN+ (dCAN+) according to autonomic nervous system function tests as described by Ewing. The results showed that the QT variability index (QTVI) was significantly (p <; 0.05) higher and positive in the dCAN+ (0.51 ±1.32) group than in the eCAN+ (-0.39 ±0.91) and CAN - (-0.54 ±0.72) groups. The QT variability to heart-rate variability ratio provides a measure of the balance between QT and heart interbeat variability. QTVI was more sensitive in identifying disease progression at all stages. Our study supports the hypothesis that QTVI could be used as a clinical test to identify early CAN and as a marker of CAN progression in diabetic patients and may help physicians in determining the best therapeutic strategy for these patients.

Analyzing Systolic-Diastolic Interval Interaction Characteristics in Diabetic Cardiac Autonomic Neuropathy Progression

Cardiac autonomic neuropathy (CAN), one of the major complications in diabetes, if detected at the subclinical stage allows for effective treatment and avoiding further complication including cardiovascular pathology. Surface ECG (Electrocardiogram)-based diagnosis of CAN is useful to overcome the limitation of existing cardiovascular autonomic reflex tests traditionally used for CAN identification in clinical settings. The aim of this paper is to analyze the changes in the mechanical function of the ventricles in terms of systolic-diastolic interval interaction (SDI) from a surface ECG to assess the severity of CAN progression [no CAN, early CAN (ECAN) or subclinical CAN, and definite CAN (DCAN) or clinical CAN]. ECG signals recorded in supine resting condition from 72 diabetic subjects without CAN (CAN-) and 70 diabetic subjects with CAN were analyzed in this paper. The severity of CAN was determined by Ewings Cardiovascular autonomic reflex tests. Fifty-five subjects of the CAN group had ECAN and 15 subjects had DCAN. In this paper, we propose an improved version of the SDI parameter (i.e., TQ/RR interval ratio) measured from the electrical diastolic interval (i.e., TQ interval) and the heart rate interval (i.e., RR interval). The performance of the proposed SDI measure was compared with the performance of the existing SDI measure (i.e., QT/TQ interval ratio). The proposed SDI parameter showed significant differences among three groups (no CAN, ECAN, and DCAN). In addition, the proposed SDI parameter was found to be more sensitive in detecting CAN progression than other ECG interval-based features traditionally used for CAN diagnosis. The modified SDI parameter might be used as an alternative measure for the Ewing autonomic reflex tests to identify CAN progression for those subjects who are unable to perform the traditional tests. These findings could also complement the echocardiographic findings of the left ventricular diastolic dysfunction by providing additional information about alteration in systolic and diastolic intervals in heart failure.

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 agematched 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 QTRR 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 (Cohens d > 0.75) showing the effectiveness of this modeling technique in detecting subclinical CAN. In conclusion, the EDRbased trivariate QT-RR-EDR model was found to be better in detecting the presence and severity of CAN than the bivariate QTRR 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.

A novel technique to investigate the effect of ageing on ventricular repolarization characteristics in healthy and LQTS subjects.

Ventricular repolarization(VR) characteristics is affected by ageing alongside several other factors like Heart rate(HR),respiration, modulation of autonomic nervous system, different drug effects, genetical factors affecting the cardiac ion channel characteristics, gender etc. Therefore, total VR variability (i.e. QT interval variability in surface ECG) consists of two components: one dependent on HR variability (HRV) and another independent of HRV. Analysis of QT interval variability (QTV) is crucial for both healthy and pathological conditions as increase in VR variability measured by QTV increases cardiac repolarization instability, which might lead to arrhythmogenesis. Analyzing the effect of ageing using a widely used measure of QTV (i.e. QTVI) is reported inconsistently in Healthy subjects whereas the same for Long QT Syndrome (LQTS) subjects is not widely reported. In this study, we propose a novel time domain measure from beat-tobeat QT-RR distribution to analyze how ageing affects VR in both Healthy and a group of genotyped LQTS1 subjects. A total of 139 Healthy subjects and 134 LQTS1 subjects of three different age groups (i.e. Young: age 20-35, Middle-aged: 40-55 and Old: age<;60) were analyzed for this study. The proposed measure is also compared with other existing widely used measures of QTV like SDQT and QTVI in differentiating different age groups. The proposed measure stands out to be more discriminatory than other existing variability measures of QT interval.

Effect of premature activation in analyzing QT dynamics instability using QT-RR model for ventricular fibrillation and healthy subjects

Perturbations in the normal heart rate are generally represented by the presence of premature activation (PA) beats in the surface electrocardiogram (ECG). The presence of PA is one of the main reasons of instability in QT dynamics which could initiate arrhythmia. Analyzing Boundary-Input Boundary-Output (BIBO) stability of the short term linear autoregressive QT-RR model is a way of detecting instability in QT dynamics from the ECG. The aim of this paper is to investigate if PA is the only reason for instability in the ventricular repolarisation process, which is denoted by QT interval of surface ECG. Ten healthy subjects with normal sinus rhythm and seven patients with sustained ventricular tachycardia (VT) were analyzed in this study. 10 min long ECG data were collected from each subject of the healthy group and 10 min ECG before the start of VT were taken for each subject of the VT group. Autoregressive QT-RR model was derived for each non-overlapping 1 min long ECG segment of the 10 min long ECG data. Instability in QT dynamics was quantified by measuring the numbers of unstable segments in ECG data for each subject (Nus). Results of this study revealed that like the VT group subjects, QT instability detected by QT-RR model is also found in healthy subjects whose ECG segments are mostly free from PA beats. This finding indicates that BIBO unstable QT characteristics might arise from other inherent factors of cardiovascular system in addition to PA.

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.

A novel technique for analysing beat-to-beat dynamical changes of QT-RR distribution for arrhythmia prediction

Ventricular tachycardia (VT) leading to ventricular fibrillation (VF) is the major cause of sudden cardiac death (SCD) with subjects with or without any history of cardiac disease. Prediction of the initiation of ventricular fibrillation is crucial for both successful preventive measure and effective defibrillation therapy. A lot of studies have been done based on electrocardiogram (ECG) waveform analysis for VF detection but this field still needs more perfection. Both HRV and QTV related parameters were reported to be analysed for VT/VF detection and prediction with inconsistent results in different populations. In this study, we propose a novel time domain measurement tool to detect the pattern of dynamical changes of both RR and QT intervals in subjects having sustained VT/VF episodes form VFDB and AHA database (www.physionet.org). We also analyse the same pattern in some healthy subjects from Fantasia database and compare the distribution of patterns between healthy and VT/VF subjects. Our findings showed that the distribution of QT-RR dynamics are statistically significantly different (p<;0.05) in healthy subjects from VT/VF in particular before the start of VF episode. Therefore, distribution of change in QT-RR dynamics may provide insight of the underlying instability before VF events and can be used for better prediction of arhythmogenesis.

Influence of psychological stress on Systolic-Diastolic Interval (SDI) interaction characteristics measured from the electrocardiogram (ECG) signal

Stress affects the ventricular repolarization and the ventricular mechanical function by increasing the QT interval variability and changing left ventricular ejection fraction respectively. As QT and TQ intervals are considered as surrogates of mechanical systolic and diastolic durations, alteration of QT and TQ interval dynamics can be used to analyse stress related changes in the systolic and diastolic function of the heart. The ratio of QT to TQ interval within a cardiac cycle (i.e. QTTQ ratio) represents the synchronized contraction and relaxation operation of the heart. Besides QTTQ, the ratio of TQ to RR interval (i.e. TQRR ratio) can also be used as a non-invasive measure of the diastolic function to analyse ventricular dysfunction. The stress related alteration of ventricular function is reported in subjects with coronary heart diseases, but the same was not reported in healthy subjects widely. In this study, the effect of stress on systolic-diastolic interval (SDI) ratios is analysed to investigate the stress related alteration in ventricular repolarization in healthy subjects. The study results indicate that stress induction increases the mean QTTQ ratio (mSDIQT-TQ) and decreases the TQRR ratio (mSDITQ-RR) indicating the effect of stress on systolic and diastolic functions. The increase in mSDIQT-TQ indicates the increases in the probability of arrhythmogenesis. However, the difference between stressed and unstressed conditions for theses ratio parameters was not significant (p>0.05). Alternatively, the variability of SDI parameters (i.e. variance of QTTQ and TQRR ratios) increased significantly, which can detect the induced stress in healthy individuals and significantly (p<;0.05) differentiated the stressed condition form natural steady state relaxed condition of the same individual. The significant increase in variability in QTTQ and TQRR ratio indicate the increased probability of arrhythmogenesis due to sympathetic activation during stressed conditions.