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

A translational study for detection of cardiac autonomic neuropathy using fractal features: A bench to bedside approach

Cardiac autonomic Neuropathy (CAN) is an acute complication of Diabetes mellitus (DM) that does not exhibit overt symptoms in the subclinical stage. Researchers have developed several techniques that have proved to give higher efficiency in classification using software tools. The challenge in implementing the same using hardware for diagnosis fails when classification boundaries are mismatched, as there are more chances of misinterpreting the classes. In this study, we have introduced translational research between the complexity analysis using software and verifying the same by deploying it in hardware using a controller board by investigating the error percentage in classifying normal (N) and early CAN (E). The study reveals that among the segments specific to CAN diagnosis, RR and ST show more error percentages (12±8 %). In contrast, PR and QT show a lesser error percentage (6±4 %) between software and hardware implementation of Fractal dimension (FD) values.

The Relationship between Body Composition and ECG Ventricular Activity in Young Adults

This study aimed to determine the correlation between body composition (measured as weight, body mass index, and body fat percentage (BFP)) and electrocardiographic ventricular parameters (the QT and TQ intervals and the ratios between the electrical diastole and electrical systole (TQ/QT) and between the cardiac cycle and electrical diastole (RR/TQ), both for uncorrected and corrected intervals) in a sample of 50 healthy subjects (age interval 19-23 years, mean age 21.27 ± 1.41 years, 33 women and 17 men). Subjects' measurements were performed with a bioimpedancemetry body composition analyzer and a portable ECG monitor with six leads. Starting from the correlations obtained between the investigated continuous variables, we performed a standard linear regression analysis between the body composition parameters and the ECG ones. Our results revealed that some of our regression models are statistically significant (p < 0.001). Thus, a specific part of the variability of the dependent variables (ECG ventricular activity parameters for corrected QT intervals) is explained by the independent variable BFP. Therefore, body composition influences ventricular electrical activity in young adults, which implies a differentiated interpretation of the electrocardiogram in these situations.

Complexity Analysis in the PR, QT, RR and ST Segments of ECG for Early Assessment of Severity in Cardiac Autonomic Neuropathy

Early-stage detection of cardiac autonomic neuropathy (CAN) is important for better management of the disease and prevents hospitalization. This study has investigated the complex nature of PR, QT, RR, and ST time segments of ECG signals by computing the fractal dimension (FD) of all segments from 20 min ECG recordings of people with different severity of the disease and healthy individuals. The mean computed for each ECG time segment to distinguish between subjects was insufficient for an early diagnosis. Statistical analysis shows that the change of FD in various time segments of ECG throughout the recording was most suitable to assess the steps for severity in symptoms of CAN between the healthy and the subjects with early symptoms of CAN. The complexity of ECG features was evaluated using various classifier models, namely, support vector machine (SVM), naïve Bayes, random forest, K-nearest neighbor (KNN), AdaBoost, and neural networks. Performance measures were computed on all models, with a maximum neural network classifier having an accuracy of 96.9%. Feature ranking results show that fractal features have more significance than the time segments of ECG in differentiating the subjects. The results of statistical validation show that all the selected features based on ECG physiology proved to have an evident complexity change between normal and severity stages of CAN. Thus, this work reports the complexity analysis in all the selected time segments of ECG that can be an effective tool for early diagnostics for CAN.

Information Flow Between Heart Rhythm, Repolarization, and the Diastolic Interval Series for Healthy Individuals and LQTS1 Patients

Using information theoretic measures, relations between heart rhythm, repolarization in the tissue of the heart, and the diastolic interval time series are analyzed. These processes are a fragment of the cardiovascular physiological network. A comparison is made between the results for 84 (42 women) healthy individuals and 65 (45 women) long QT syndrome type 1 (LQTS1) patients. Self-entropy, transfer entropy, and joint transfer entropy are calculated for the three time series and their combinations. The results for self-entropy indicate the well-known result that regularity of heart rhythm for healthy individuals is larger than that of QT interval series. The flow of information depends on the direction with the flow from the heart rhythm to QT dominating. In LQTS1 patients, however, our results indicate that information flow in the opposite direction may occur-a new result. The information flow from the heart rhythm to QT dominates, which verifies the asymmetry seen by Porta et al. in the variable tilt angle experiment. The amount of new information and self-entropy for LQTS1 patients is smaller than that for healthy individuals. However, information transfers from RR to QT and from DI to QT are larger in the case of LQTS1 patients.

Interdisciplinary approach to compensation of hypoglycemia in diabetic patients with chronic heart failure

Diabetes mellitus is a chronic disease requiring lifelong control with hypoglycemic agents that must demonstrate excellent efficacy and safety profiles. In patients taking glucose-lowering drugs, hypoglycemia is a common cause of death associated with arrhythmias, increased thrombus formation, and specific effects of catecholamines due to sympathoadrenal activation. Focus is now shifting from merely glycemic control to multifactorial approach. In the context of individual drugs and classes, this article reviews interdisciplinary strategies evaluating metabolic effects of drugs for treatment of chronic heart failure (CHF) which can mask characteristic hypoglycemia symptoms. Hypoglycemia unawareness and cardiac autonomic neuropathy are discussed. Data suggesting that hypoglycemia modulates immune response are reviewed. The potential role of gut microbiota in improving health of patients with diabetes and CHF is emphasized. Reports stating that nondiabetic CHF patients can have life-threatening hypoglycemia associated with imbalance of thyroid hormones are discussed. Regular glycemic control based on HbA1c measurements and adequate pharmacotherapy remain the priorities in diabetes management. New antihyperglycemic drugs with safer profiles should be preferred in vulnerable CHF patients. Multidrug interactions must be considered. Emerging therapies with reduced hypoglycemia risk, telemedicine, sensor technologies, and genetic testing predicting hypoglycemia risk may help solving the challenges of hypoglycemia in CHF patients with diabetes. Interdisciplinary work may involve cardiologists, diabetologists/endocrinologists, immunologists, gastroenterologists, microbiologists, nutritionists, imaging specialists, geneticists, telemedicine experts, and other relevant specialists. This review emphasizes that systematic knowledge on pathophysiology of hypoglycemia in diabetic patients with CHF is largely lacking and the gaps in our understanding require further discoveries.

Cardiovascular Autonomic Neuropathy Is an Independent Risk Factor for Left Ventricular Diastolic Dysfunction in Patients with Type 2 Diabetes

Aim

This study aimed to evaluate the association between cardiovascular autonomic neuropathy (CAN) and left ventricular diastolic dysfunction (LVDD) in type 2 diabetes patients.

Methods

315 type 2 diabetes patients from inpatients of Drum Tower Hospital were included and classified into no CAN (NCAN), possible CAN (PCAN), and definite CAN (DCAN) based on cardiovascular autonomic reflex tests. The left ventricular diastolic function was assessed by tissue Doppler imaging echocardiography.

Results

The distribution of NCAN, PCAN, and DCAN was 11.4%, 51.1%, and 37.5%, respectively. The proportion of LVDD increased among the groups of NCAN, PCAN, and DCAN (39.4%, 45.3%, and 68.0%, P = 0.001). Patients with DCAN had higher filling pressure (E/e′ ratio) (10.9 ± 2.7 versus 9.4 ± 2.8, P = 0.013) and impaired diastolic performance (e′) (6.8 ± 1.7 versus 8.6 ± 2.4, P = 0.004) compared with NCAN. CAN was found to be an independent risk factor for LVDD from the multivariate regression analysis (OR = 1.628, P = 0.009, 95% CI 1.131–2.344).

Conclusions

Our results indicated that CAN was an independent risk marker for the presence of LVDD in patients with diabetes. Early diagnosis and treatment of CAN are advocated for preventing LVDD in type 2 diabetes.

Beat-to-beat ECG restitution: A review and proposal for a new biomarker to assess cardiac stress and ventricular tachyarrhythmia vulnerability

BACKGROUND

Cardiac restitution is the ability of the heart to recover from one beat to the next. Ventricular arrhythmia vulnerability can occur when the heart does not properly adjust to sudden changes in rate or in hemodynamics leading to excessive temporal and/or spatial heterogeneity in conduction or repolarization. Restitution has historically been used to study, by invasive means, the dynamics of the relationship between action potential duration (APD) and diastolic interval (DI) in sedated subjects using various pacing protocols. Even though the analogous measures of APD and DI can be obtained using the surface ECG to acquire the respective QT and TQ intervals for ECG restitution, this methodology has not been widely adopted for a number of reasons.

METHODS

Recent development of more advanced software algorithms enables ECG intervals to be measured accurately, on a continuous beat-to-beat basis, in an automated manner, and under highly dynamic conditions (i.e., ambulatory or exercise) providing information beyond that available in the typical resting state.

RESULTS

Current breakthroughs in ECG technology will allow ECG restitution measures to become a practical approach for providing quantitative measures of the risks for ventricular arrhythmias as well as cardiac stress in general.

CONCLUSIONS

In addition to a review of the underlying principles and caveats of ECG restitution, a new approach toward an advancement of more integrated restitution biomarkers is proposed.

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.