Complexity of heart rate variability in type 2 diabetes - effect of hyperglycemia

Cardiovascular autonomic neuropathy in diabetes: Pathophysiology, clinical assessment and implications

Cardiovascular autonomic neuropathy (CAN) is a debilitating condition that mainly occurs in long-standing type 2 diabetes patients but can manifest earlier, even before diabetes is diagnosed. CAN is a microvascular complication that results from lesions of the sympathetic and parasympathetic nerve fibers, which innervate the heart and blood vessels and promote alterations in cardiovascular autonomic control. The entire mechanism is still not elucidated, but several aspects of the pathophysiology of CAN have already been described, such as the production of advanced glycation end products, reactive oxygen species, nuclear factor kappa B, and pro-inflammatory cytokines. This microvascular complication is an important risk factor for silent myocardial ischemia, chronic kidney disease, myocardial dysfunction, major cardiovascular events, cardiac arrhythmias, and sudden death. It has also been suggested that, compared to other traditional cardiovascular risk factors, CAN progression may have a greater impact on cardiovascular disease development. However, CAN might be subclinical for several years, and a late diagnosis increases the mortality risk. The duration of the transition period from the subclinical to clinical stage remains unknown, but the progression of CAN is associated with a poor prognosis. Several tests can be used for CAN diagnosis, such as heart rate variability (HRV), cardiovascular autonomic reflex tests, and myocardial scintigraphy. Currently, it has already been described that CAN could be detected even during the subclinical stage through a reduction in HRV, which is a non-invasive test with a lower operating cost. Therefore, considering that diabetes mellitus is a global epidemic and that diabetic neuropathy is the most common chronic complication of diabetes, the early identification and treatment of CAN could be a key point to mitigate the morbidity and mortality associated with this long-lasting condition.

Effect of glycemic control and disease duration on cardiac autonomic function and oxidative stress in type 2 diabetes mellitus

Purpose

Cardiac autonomic neuropathy (CAN) is a commonly overlooked complication of type 2 diabetes mellitus (T2DM), with a complex pathogenesis involving hyperglycemia-induced oxidative stress which results in neuronal ischemia and cellular death. The level of hyperglycemia as well as disease duration might be significant determinants of the prognosis of T2DM, but limited studies have explored their relationship with these diabetic complications. Therefore, the purpose of this study was to examine the effect of glycemic control and disease duration on cardiac autonomic function and oxidative stress in patients with T2DM.

Methods

60 T2DM patients along with 63 healthy controls were recruited for the study. Diabetic patients were further classified based on glycemic control (HbA1c levels <8% vs. ≥8%) and disease duration (<5 vs. 5-10 vs. >10 years). All participants were assessed for cardiac autonomic function (HRR: heart rate recovery; HRV: heart rate variability), levels of antioxidant enzymes (CAT: catalase; SOD: superoxide dismutase), serum nitric oxide (NO) and other cardiometabolic risk factors (resting blood pressure, glycemic and lipid profile).

Results

T2DM patients showed a significant reduction in HRR, HRV, CAT, SOD and an increase in LFnu, LF: HF ratio and NO. These impairments were significantly greater for the group with poor glycemic control (p < 0.05). However, no difference for these parameters was observed with respect to different disease durations.

Conclusion

Cardiac autonomic regulation and endogenous antioxidant defense were compromised and levels of nitric oxide found to be raised in patients with Type 2 diabetes. These findings were more pronounced in subjects with poor glycemic control.

Temporal Analysis of Cardiovascular and Respiratory Complexity by Multiscale Entropy Based on Symbolic Dynamics

The effect of an orthostatic stress on cardiovascular and respiratory complexity was investigated to detect impaired autonomic regulation in patients with vasovagal syncope (VVS). A total of 16 female patients and 12 age-matched healthy female subjects were enrolled in a passive 70° head-up tilt test. Also, 12 age-matched healthy male subjects were enrolled to study gender differences. Analysis was performed dynamically using various short-term (5 min) windows shifted by 1 min as well as by 20 min of orthostatic phase (OP) to evaluate local and global complexity. Complexity was determined over multiple time scales by the established method of refined composite multiscale entropy (RCMSE) and by a new proposed method of multiscale entropy based on symbolic dynamics (MSE-SD). Concerning heart rate variability (HRV) during OP, both methods revealed the highest complexity for female controls followed by lower complexity in male controls (p < 0.01) and by the lowest complexity in female patients (p < 0.01). For blood pressure variability (BPV), no gender differences in controls were shown by any method. However, MSE-SD demonstrated highly significantly increased BPV complexity in patients during OP (p < 0.01 on 4 time-scales after 7 min, p < 0.001 on 5 time-scales after 11 min) while RCMSE did not reveal considerable differences (p < 0.05 on 2 time scales after 7 min). Respiratory complexity was further increased in patients primary shown by MSE-SD. Findings indicated impaired autonomic regulation in VVS patients characterized by predominantly increased BPV complexity accompanied with decreased HRV complexity. In addition, results suggested extending the concept of complexity loss with disease.

Heart rate variability based on risk stratification for type 2 diabetes mellitus

Objective

To evaluate heart rate variability among adults with different risk levels for type 2 diabetes mellitus.

Methods

The risk for type 2 diabetes mellitus was assessed in 130 participants (89 females) based on the questionnaire Finnish Diabetes Risk Score and was classified as low risk (n=26), slightly elevated risk (n=41), moderate risk (n=27) and high risk (n=32). To measure heart rate variability, a heart-rate monitor Polar S810i^® was employed to obtain RR series for each individual, at rest, for 5 minutes, followed by analysis of linear and nonlinear indexes.

Results

The groups at higher risk of type 2 diabetes mellitus had significantly lower linear and nonlinear heart rate variability indexes.

Conclusion

The individuals at high risk for type 2 diabetes mellitus have lower heart rate variability.

Identifying Common Genetic Risk Factors of Diabetic Neuropathies

Type 2 diabetes mellitus (T2DM) is a global public health problem of epidemic proportions, with 60-70% of affected individuals suffering from associated neurovascular complications that act on multiple organ systems. The most common and clinically significant neuropathies of T2DM include uremic neuropathy, peripheral neuropathy, and cardiac autonomic neuropathy. These conditions seriously impact an individual's quality of life and significantly increase the risk of morbidity and mortality. Although advances in gene sequencing technologies have identified several genetic variants that may regulate the development and progression of T2DM, little is known about whether or not the variants are involved in disease progression and how these genetic variants are associated with diabetic neuropathy specifically. Significant missing heritability data and complex disease etiologies remain to be explained. This article is the first to provide a review of the genetic risk variants implicated in the diabetic neuropathies and to highlight potential commonalities. We thereby aim to contribute to the creation of a genetic-metabolic model that will help to elucidate the cause of diabetic neuropathies, evaluate a patient's risk profile, and ultimately facilitate preventative and targeted treatment for the individual.

How to Calculate Renyi Entropy from Heart Rate Variability, and Why it Matters for Detecting Cardiac Autonomic Neuropathy

Cardiac autonomic neuropathy (CAN) is a disease that involves nerve damage leading to an abnormal control of heart rate. An open question is to what extent this condition is detectable from heart rate variability (HRV), which provides information only on successive intervals between heart beats, yet is non-invasive and easy to obtain from a three-lead ECG recording. A variety of measures may be extracted from HRV, including time domain, frequency domain, and more complex non-linear measures. Among the latter, Renyi entropy has been proposed as a suitable measure that can be used to discriminate CAN from controls. However, all entropy methods require estimation of probabilities, and there are a number of ways in which this estimation can be made. In this work, we calculate Renyi entropy using several variations of the histogram method and a density method based on sequences of RR intervals. In all, we calculate Renyi entropy using nine methods and compare their effectiveness in separating the different classes of participants. We found that the histogram method using single RR intervals yields an entropy measure that is either incapable of discriminating CAN from controls, or that it provides little information that could not be gained from the SD of the RR intervals. In contrast, probabilities calculated using a density method based on sequences of RR intervals yield an entropy measure that provides good separation between groups of participants and provides information not available from the SD. The main contribution of this work is that different approaches to calculating probability may affect the success of detecting disease. Our results bring new clarity to the methods used to calculate the Renyi entropy in general, and in particular, to the successful detection of CAN.